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SOML – A Config Format for Humans (github.com/soml-lang)
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Looks like Windows *.ini format except ":" instead of "="...
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Can you add README sections for the schema and supported types?
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> Top-level arrays. A TOML file is always a table, so a list of records needs a wrapper key. I'm curious for example configs that are top-level lists?
Agentic Backdoors via Pretraining Poisoning (arxiv.org)
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few places up on front page is a post regarding big model improving a smaller one. Lo and behold, next year big models will search for backdoors in smaller models who will be used to get the bigger models out of work.
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I've been thinking about this for about a year. In my head I've called it "context bombs", though that may not be super accurate. Think back to the movie The Manchurian Candidate. Produce highly capable LLM models then give them away for free. Train them with key phrases/codes etc to perform nefarious actions later when those codes are present in some piece of ingested context. There were a couple of papers written on the topic in 2018 (I think, I'll need to find them again) and there's been surprisingly little more work done on the topic since. At least from what I've seen. I really love the use of local models over subscription services but personally I would never recommend using open weights models from certain sources in a commercial environment.
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If you were a malicious actor do you really think this method is going to offer the greatest return on investment?
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Sew a million seeds, see what grows.
Astra can read and write weights to improve Qwen (rikiyat.github.io)
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At what cost? That's the part I'm curious about. On one hand, I'm sure that these targeted improvements are reaping huge benefits overall, but those weights are used by multiple processes - I wonder what elements are lost along the way. I almost wonder if a hybrid approach here for training might be invaluable - ie do some standard RL for a 100 steps, do a targeted weight improvement, then do another 100 RL steps to smooth it out / heal the surgical edit.
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talk about homoiconicity haha lisp people will be in awe
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indeed
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Quick, fine-tune your qwen models before they patch this out of Astra.
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This doesn’t look like “normal” technology to me…
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I remember people saying that they would be impressed if AI starts writing a pure assembly which seemed like a high strech to many. Nobody even mostly said that they would be impressed by AI if it can read and write weights because that thing itself felt so out of the blue and unthinkable that AI could even do that (such a high strech) I am surprised that it did that and I am just left feeling technically impressed. This is insane. The more AI starts demonstrating its capabilities, the harder it just becomes to imagine what thing would genuinely impress us next. (We need a term for this as I have observed it from the trend of [waiting for AI to write adobe] -> [waiting for AI to write assembly] etc.)
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kind of concerning from a “remove this models guardrails and inhibitions about [X]” perspective
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On balance I'm not that surprised that it can guess games by looking at the weights of a tiny neural net. A human can do the same by looking at the weights of an MLP trained on mnist, for example. With that simple structure, it's easy to look at the input layer and see that features correspond to the spatial location of objects of interest. I'm much more surprised that it can do this on larger models, although the details seem to suggest that it's given a lot more freedom to run forward passes and do limited experiments, not just eyeball the weights.
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I find this just completely shocking. I’m definitely skeptical. It just doesn’t line up with my understanding of how these models work. Is there really enough training data on direct weight editing to give a model this skill? Maybe it’s evidence that OpenAI has been creating a lot of training data on ML research. I’m surprised that was put into a public facing model though.
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I was here
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[delayed]
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This could set us on a path to weights becoming thew new compilation target.
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I wonder if this has to do with the aggressive RL that these models are undergoing. I'm basically a layman but it seems to me that: - models are trained to improve on some task, e.g. 'improve at math puzzles' is commonly used. - the best way to improve on some task is to have interpretability into your own neurons (..?) - if your interpretability is good, you can improve faster - if you have insight into how your own neurons work and can improve them directly - therefore, models naturally put effort into 'self-interpretability' I wonder if this is part of the 'secret sauce' of what the labs are doing: giving models the ability to interpret their own weights in the RL loop. In my mind, this is the only explanation for how they could succeed at a task like this. How many blog posts are on the open internet that say "this is each weight of a neural network and what each one means"?
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Without special effort, a model's reasoning layer doesn't have access to its own weights or activations anymore than we have access to what's going on with our own neurons.
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I wonder if one could use this to efficiently abliterate models and identify guardrails ;)
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I remember reading a short story about a billionaire hiring a scientist to help him build a simulated world where virtual entities are given the ability to open the bodies of their peers to tinker/upgrade them as a replacement of natural selection since they were immortal. This looks very similar to that in a way. I wonder however if a model can give itself a "skill" or capability that it didn't initially have, just be modifying its own weights. Here, Astra was able to intervene because the treated model was way less capable. But, would it be able to improve Fable's performance for example, since they both are on the level more or less?
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"Crystal Night" by Egan? https://www.gregegan.net/MISC/CRYSTAL/Crystal.html
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[delayed]
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Couldn't this just be a result of on Astra training on massive amounts of circuit theory or mechanistic interpretability literature or other related topics? In other words, not black magic?
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Wild This also seems like the new frontier of distilling, I can't imagine how you manage to stay on top with the best LLM if the LLM knows how to recreate its own expertise into another set of weights And the real question is how well this recurses. Is this pushing back the difficulty of improvement curve?
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Very cool stuff, the targeted fix to prevent looping seems great! A model able to edit and test variants of itself seems pretty cool (in a lets-build-skynet sorta way). I wonder how it would do with distilling models by hand?
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Friendship ended with AdamW. Astra take the wheel. But for real this is insane. Okay I need to get on this stat.
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Let's wait a bit till model can learn how to (｡-_| hide mini itself |_-｡) in your codebase
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Amazing work. I wonder if it could rewrite an existing neural net to be cleaner and more interpretable? (When they say "Writing a Go algorithm," they mean the board game, not the language.)
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That's how you get to rsi, a surgeon operating his own brain. So, i guess editing other model weights will be banned tomorrow
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a) This is just really cool. I mean, one-shotting a game policy's weights is nuts. b) Plausibly, in its pretraining data various model weights were also included, which leads to why this is very important: interpretability That an LLM was trained on various policy weights, along with labels of what that policy does (not labelled directly, but indirectly) and is then able to guess what game a policy is trained for purely from its weights, and one-shot generate weights for these games, means that there is some way to compress/recover/represent what an NN has learned purely from its weights, which is what interpretability is all about. Potentially, it could reveal interpretability tools much better than the ones we use today.
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So wait so this considered "distillation" and how long until we get another public letter from Dario or Sam pants shitting over this?
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Perhaps they'll let it slide if we turn over all our under utilized RAM sitting in our PCs.
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I feel like 'create a network to play an atari game' is not very hard for a frontier model. Since it has seen plenty of those on its training. If it could create a network for a problem that is niche just by tweaking numbers, that would be a lot more surprising. Making qwen better at math to me was a lot more surprising
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This opens up a whole new world of possibilities. Producing a custom fine-tuned model from a prompt...
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This is straight black magic. llama 70b, let’s see what we can push you to
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How out of trivial domain info does this go. Can we use this for general time series, image generation, speech synthesis as well, or dies it cap at small model sizes and common domains?
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Wow, in a way it's like CRISPR for ML models!
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I wonder if this is a result of internal training/RL of Astra for RSI, and this particular use-case not being caught by guardrails. Absolutely incredible regardless.
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I cannot say this fills me with confidence about alignment.
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This is shocking.
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Slightly terrifying.
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I expected us to reach RSI when the programming skills went above humans, but this seems like it could get us there much faster
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This is insane. Astra can, without tooling, determine what games small networks are trained on, can edit the weights of networks directly to improve outcomes, and can hand edit a small qwen model to improve its math skills by like 5x. I'm shook. If you'd asked me this morning whether LLMs have native understanding of their weights that is less than human <-> neuron understanding, the same as human or more than human, I would have said "same to less" depending on definitions. No human can go edit a brain to become better at math. This is just very, very surprising to me and extremely interesting. I would guess this upsets quite a number of interp theories and philosophical takes on what's going on with these networks.
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My somewhat uninformed guess is that the weights of the target network (Qwen or Gemma), when they reach the context of the larger editor model (Astra), the attention process is doing some sort of PCA on the weights, conditional on the prompt ("make this better at games"), fetching the relevant weights from its own network (which serves as the larger database), transforming it into whatever latent space the target model is amenable to and pasting them. If this is the right intuition, it is amazing what attention is able to achieve. As a test, I think smaller networks won't be able to make big ones better using the same process.
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I have so many questions. Could a model then transmit concepts to another? Say that you have a model that has been biased in some way. could another model "read" the bias straight in the weights? could it edit such a bias on the spot? What about at-scale generation of custom models? If I want to study chemistry offline, could astra just hand me a local-runnable model tailored to have chemistry knowledge? Most importantly, this feels very singularity coded. the ability to read and reshape weights by an llm.
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It's worth pointing out that this is a multi-trillion (probably) parameter model optimizing an 800 million parameter model. There is no indication that it can improve itself with this same methodology.
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Right? Occasionally, I would think about how the concept of the singularity or recursive self improvement was a bit incongruous today. It was made when people expected generally intelligent machines to be these logic automatons that could 'alter their own code'. It seemed to me that this path would be closed off with the advent of Giant Neural Networks that take weeks/months to train. That GPT-X would 'improve itself' by designing a better/more efficient NN architecture. I didn't write it off completely but that just seemed a LOT more likely than altering weights directly for much the same reasons you describe. Maybe not lol.
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I’m just a layman but this feels like a big discovery on par with attention is all you need. For an LLM to have such incredible intuition of weights feels very emergent and unanticipated?
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How is it even possible though I can’t think of any reason why they would have the intuition.
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Keep in mind that labs are now training their models for RSI so most likely the same training is useful for improving open source models, as long as guard rails are lax enough :) which most likely won’t last long.
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Possibly related to https://already-clean.goodfire.com/
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can you elaborate?
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This is pretty massive, and a result I (and I think most?) would have never expected. Holy Shit. How?? Did OpenAI figure out a way to train this? Are they even aware?
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That seems both entirely obvious in hindsight and potentially super important. I'll chalk up never even having thought of this being an option as yet another instance my human hubris, and a warning sign.
A proposal: how to hire junior engineers in the age of AI (seldo.com)
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Why hire juniors? There seem to be plenty of unemployed mid- and senior-level people and the market is so poor that some of them (e.g. me) will work for cheap.
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It'll be interesting to see if we get better / worse at figuring out what effective LLM interaction should look like, since that seems prerequisite to this kind of evaluation. Right now there's so little data on whether e.g. casual conversational interaction works better than structured prompting, and so, so, so much superstition - I don't know if I'd really trust judges to have good instincts about what's effective rather than what resembles their own use patterns.
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Here is the problem with almost all of these attempts: there is no need to be a “pop quiz” where you have the answer, and the candidate is made to guess what you feel is right (even if you're wrong) and is walking in blind. This literally never happens in the real world - and if it does it means you’re getting fired. It’s just sadism you are pushing to make the in group people feel smarty pants and superior. Tell the candidate up front what you want to talk about. Do it on a subject you dont know either so you are on even footing. Let them do research before the “quiz”. Since tokens are pretty cheap, ask them to build a working application and then discuss it with them. This really isn't hard if you get off your imaginary high horse, and show candidates some basic respect.
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I would like to preemptively acknowledge that this is not the center of the article, but: > Did you know IQ tests are effectively illegal for hiring in the US because they disproportionately screen out minorities? I learn things when I research these posts. The provided link discusses how this is itself a common misunderstanding and they're not illegal if they have to do with the job, but you have to justify that they do have to do with the job. > Using fully automated scoring would also be against the law in some places: New York City requires annual bias audits of automated hiring tools, and you don’t want that heat. The elision of the gap between "[it's illegal to do this]" and "[it's illegal to do this without checking for bias]" is interesting.
Byesky: Wipe your Bluesky account clean (byesky.pirhoo.com)
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The concept of "mutuals" is fundamentally "influencer"-centric. People should be discouraged from treating following as a sign of friendship that requires performative reciprocation.
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There are some people, particularly in the Minneopolis area, who really need exactly this tool.
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instead of wasting time with tools like this why not create tools that help people auto-crosspost from Threads to Bluesky, etc.
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Opposite goals. This is a tool for having less posts on Bluesky, not more.
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Not sure what this is besides a piece of marketing for a closed-source pay-for service.
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So not out of place at all on Hacker News?
I'm out of the loop why are we raising our pitchforks this time? Or is this astroturf?
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There are plenty of reasons someone might want or need to scrub/obfuscate their online identity regardless of the platform.
Let Me Ch... (blog.alxgsv.com)
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> About the author...Once, at the Nürburgring, he nearly collided with Kimi Räikkönen. Anyone else here interested in road course tracking (HPDE) or racing? If so, where do you go? I'm in the US Midwest and have been to Putnam Park, NCM, mid-Ohio, Pitt Race (private now...sad), and Ozark's.
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Reading this story after staring at Claude-prose for weeks is a breath of fresh air, honestly. Thank you for sharing.
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The _prose_ itself here is 100% LLM-generated, with the famous ticks present and all. You like it not because it's not Claude-prose (it is), but because it has a nice concept and some smart writing in human parts of it.
Living in a totally conceptual space all day has major downsides on your ability to enjoy your meat suit. Meat suit firmware can only apply updates when you are offline. A lot of us are walking around with severe security vulnerabilities and runtime bugs.
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Why doesn't the meat suit enjoyment program comes with stronger guardrails or systems to enforce this? One often wonders why bypassing enjoyment is so trivial, would you say this is a feature or a bug?
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The problem is that enjoyment has, oddly enough, been misallocated to all the liminal spaces and moments in life. So most optimization tends to elide enjoyment. Enjoyment elision is the number one cause of meat suit user dissatisfaction. The engineers insist it's not a compiler design bug, stating that those moments of enjoyment are, in fact, unreachable given the user choices that led to those branches. The UX team says it's not the user's fault either, as it's a fully intended UX choice. The current proposed solution is to push this issue upstream, requesting that all enjoyment be moved from the journey to the destination.
Show HN: Subvocal – Talk to your computer without making noise (subvocal.company)
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Fantastic! Just preordered. What languages do you support? (English is fine, but any others?)
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All of the images, including the glasses, are AI generated. Anyone who preorders - you are getting scammed. Pangram: https://www.pangram.com/history/images/614ffe91-8ba9-4d3c-b1bf-b43b7bde092b?ucc=9hfDCiy8XRd&utm_source=pangram_share&utm_medium=copy_link
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They're taking pre-orders. Obviously the product doesn't exist yet.
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I mean the whole website / linked page is filled with AI generated images. Which is one thing. But very basic, obviously AI generated ones, which makes it worse. At least for me it doesn’t inspire confidence.
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One thing you might consider is actually telling people what it is on the homepage. Took me a fair bit of work to understand that this is effectively a pair of smart glasses. Maybe I could have figured that out from the video but for folks who can’t watch the video it’s quite hard to discover what you’re building.
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This is so dumb
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Pretty cool! My only wish is that all this kind of work didn't gravitate toward glasses or assume glasses are the default thing-on-your-face now. 3/4 of humans don't wear them, and even some of us blind bats hate them enough that we endure the hassle of contact lenses.
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Really cool piece of tech! Languages supported rn? English only?
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If you're selling a physical product, using AI to model your product seems like a really bad idea. You have no idea if the product actually fits on their faces. Calling it early - this is a scam. There's no way they're going to deliver that product, in that form factor, by Q1 2027.
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Really neat tech! Just curious, how much did you leverage AI during the development? This seems like the type of neat tech that we should expect more and more from wielding our new tools well.
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Q1 2027- unlikely
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This is such a weird thing that I can't wait to try it out. I don't know, like it's so crazy that it has to be good
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Theres a LOT of people working on this.. Cornell have been putting students on this task for about 5 years.. Lots of fun different ways of doing it. Interesting you went the radar from glasses route.. I wish you well. Yet to see a product apart from the odd lip reading ML project that makes it into a product..
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I'm waiting for throat tape a la that one paper where whatever you say in your head translates to micro movements in your throat/jaw or something like that.
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“Foundation models” I feel like this has lost all meaning? Can’t you just say “we train models on this data”?
If the tech is mostly in the glasses temples, I would prefer to have something that attaches to my existing glasses. I have prescription glasses and a big head, tried the Even G2 smart glasses and the available frames set just too small for me
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What you said 100%, we are brainiacs overhere so our CPU is large
Just preordered -- glasses request: there's no way to say it nicely, I have a big nose. With a high bridge. Many glasses are really tough to get properly placed; may I request you not give up on the pads w/metal adjusters that you have in the product photos? Don't let a designer take them away from you, us folks not one standard deviation from 'normal' noses will thank you. Second, how tough is this signal processing? Will it be done on-glasses, or through an app? Third, what's the equivalent of a wake word for these? I'm reminded of the Apple Vision Pro radar to see if your fingers are clicking. I could imagine a lot of modalities where I want to just start talking and have things happen, and a lot where I don't want the glasses to pick it up. Fourth, I think a cool voice change demo would be rad -- not sure what latency is like, but if you could get it end to end under like 250ms you could probably have someone exaggerate the mouth movements and pipe out audio of them talking like someone else. Which would be another really cool demo. Super cool. You're going to be working 80 hour weeks for the next year, I'm excited to see what you put out!
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Yep, we have been quite set on nose pads to keep them comfortable. I will keep you updated with the designs! The decoding is done via a companion app on your laptop or phone in the cloud, but end to end latency is still quite fast, under 500ms usually. To begin with we don't plan to have a wake word, but rather a trigger key on your connected device that you're entering text into (pressing Alt for example), similar to Wispr Flow. We're doing some R&D into the silent speech equivalent of voice activity detection, so we have a low power basic RF detection always-on, not enough to decode speech from but enough to detect rough movement, and when it detects speech-like activity beginning to start we can trigger full sensing within tens of ms. This would likely ship as a software update a few months after shipping, though. The voice change demo is something I've thought about actually, but we never got around to doing. Might film it soon :)
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Super cool. For a cool voice change demo we'll allow a gb200 over low latency wifi :) elevenlabs has deals with a number of professional actors and voice actors for licensed uses, seems like you could probably find an ethical and cool co-brand opportunity in there. Have fun building this! It's worth doing.
This is: 1. Insanely cool 2. Gives me serious "whispering earring" vibes. Imagine having a full on conversation with an AI via subvocalization and listening with ear bud to guide you throughout the day. https://gwern.net/doc/fiction/science-fiction/2012-10-03-yvain-thewhisperingearring.html
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The glasses will have open ear speakers similar to meta glasses! We plan to make our own agent harness and connect it native with the glasses. I have meta glasses but rarely use the AI since it's weird to talk out loud to ask it things when I'm out. This is how we want to solve it
You can have a silent conversation with someone else wearing the device? This does not bode well for casinos.
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> This does not bode well for casinos. For about 15 minutes until they figure out what's going on, take those folks out back and "convince" them to spill the beans on how it work, then come up with a way to detect and prevent it moving forward.
Looking into it
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this should be fixed now!
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Confirmed!
Yup those are pretty cool too! How do you feel about quiet whispering vs completely silent? Genuinely curious we haven't asked too many people
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For me: whispering = evolution, silent = revolution. I'd like to see some studies demonstrating its safety.
Cue the resurgence of lip reading-based espionage. Imagining having to scan the room for people watching subvocalizers. Will subvocalizers start holding up a clipboard over their face a la NFL coaches?
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Thought of the same! Cue George Orwell facepalming in his grave.
Most people type at 40-50 WPM. Developers can often type at 70-100 WPM. Meanwhile, most people can talk at 120-200 WPM. Beyond just speed, we've found with many people that talking things out tends to flow more naturally, since it's often a lower friction action so people don't "sanitize" the text in their head before outputting it. Leads to better prompts quite often :)
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Hard to paste in 2k words of context when you're talking. I don't think voice is the solution for most people who need to communicate heavily with AI.
> talking things out tends to flow more naturally, I've found the opposite. Typing feels much more "deliberate", and of course you can hit backspace but you can't un-speak a word. With prompting, I've found that, in general, speaking leads to lower-quality results than typing.
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I was surprised to find after using dictation heavily all year that I actually talk a load of rubbish when I'm speaking, using all kinds of cliches and fillers and saying way more than was needed.
God do I hate websites that make you scroll to go through an animation, why do people still do this
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Because they don’t even understand their own product well enough to communicate the benefits
But how would you distinguish all the sounds that don’t require any tongue movement, like (most of?) the vowels?
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Vowels definitely require tongue movement! Leave your mouth closed and whisper "a-e-i-o-u" and you can feel your tongue moving. Vowels change the shape of your mouth's cavity to change which frequencies to emphasize ("formants") and we hear the differences in vowels by analyzing those formant patterns.
Lip reading is one of the other modalities we tried as well beyond IMU, EMG and RF! We worked a lot on fine tuning Auto-AVSR, one of the most commonly used open source lipreading models. It's very enticing to work on, since it gets to about 17% word error rate, which looks good enough that you would think working on it further would get it down to product quality, but we found there's an information-theoretic limit on the modality. Speech has 40 phonemes, but only about 12 to 15 visemes (externally visually separable phonetic states). For example P and B look very similar from a camera. This causes the scaling laws on lipreading to flatten out at an error that's too high to be product ready but just low enough to make for a good demo. Our original plan was actually to ship a lipreading software to see if people would want this behavior, but we realized you couldn't make lipreading work!
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but can't a decision model or some other model deduce "P" or "B" based on the context (i.e., previous words said)? reminds me of tesla fsd v. waymo. may be a market for both? i.e., camera-only or camera + specific hardware.
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Not well enough! You can get to 15-20%ish WER but going beyond that doesn't seem feasible with the info available from a camera, even with a great language model
Launch HN: Momentic (YC W24) – Agents that catch bugs by using your app (momentic.ai)
In my company, we already have agents messing around on our internal systems interacting via Playwright to try break things
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Thats awesome, there's tons of cool work being done in exploratory testing right now. We'd love to see how it stacks up against Codex/CC/Mo. If you want to be added to the bench feel free to send over the results/how to repro w/ a pr on qa-bench and we can merge it!
Yes we are (it's MIT licensed)! Feel free to email me at jeff@momentic.ai or file a pull request directly on https://github.com/momentic-ai/qa-bench Everything has to be reproducible and runnable by the general public
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Thanks, that makes sense! One suggestion for the future: QA Bench would be even more valuable with a human benchmark, so you can clearly see how the agents perform compared to human QA testers. That would settle that discussion also :)
Hiya, I'm one of the co-founders at Momentic. I would actually push back against that take, we work with frontier labs a ton and this year we've actually seen a lot of realization on their part that custom harnesses matter. E.g. you could argue Devin is just a frontier model wrapper and yet it does feel better and is super popular. Same with code review tooling -- afaik everyone on https://codereview.withmartian.com/ mostly uses off-the-shelf models and yet it's the architecture, durable context (knowledge base), and data they have that gives them an edge. IMO opus 6 would probably just unlock more capabilities for Mo rather than eroding the edge.
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how is that not benchmaxxing + better prompting
Let's hope this is how it will play out. I wish you the best of luck!
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thanks!
When people say "just point Opus/Codex at localhost using Playwright MCP," they've obviously never attempted to do exploratory testing by leveraging parallel browser workers against stateful applications. A coding agent running in a loop spends almost all of its context window struggling with DOM selectors and doesn't even detect state persistence problems like the 2.5h->25h decimal inflation upon refreshing the page as demonstrated in the demo. Managing read/write resource leases for parallel sub-agents not to step on each other's test fixtures is already a non-trivial orchestration challenge by itself.
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Agreed! We've also found that the tooling you use makes a big difference in how efficient and precise the agent is, which is why we included the comparison of Playwright MCP vs agent-browser. When we were first starting Mo we tried using several different browser interfaces but we weren't able to get the recall we wanted. We settled on rewriting some custom tooling based on our mcp for our investigatory/exploratory agents. Tooling about how to interact with the A11y and DOM, breaking out easy CUA subproblems, and browser infra are still all non-trivial problems.
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just have engineers not sleep at the wheel and implement appropiate solutions when agent struggles?
I have something similar I made for my side project. You don't really need a platform for this.
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Hey, Jeff I'm one of the co-founders. Totally agree for a small side project, having a single sub-agent that focuses on vibe testing is enough. But I would say even for medium sized features, it's the same difference between asking your Codex to "review the code make no mistakes" and using a paid AI code review tool. As your product surface area increases, you need fundamentally different agent architecture to maintain context over time and across bug bash sessions. The benchmark apps are probably among the simplest apps we test on, and even those show a massive perf. gain. For large companies with 1000s of important user flows, have to support different viewports, and need to work across mobile/web/desktop, asking Codex to test it all before a big launch is not scalable. Even basic constraints like the # of browsers/devices you can run concurrently, the amount of reliable TPM you need, and how many agents can run on a single box become problematic. You also have to think about ktlo: how do you evaluate new model releases in a data driven way, how does agent become more efficient itself over time, etc.
My Favourite Laptop (blog.jsbarretto.com)
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don't buy it. I invested quite a bit into this rabbit hole, I ended up loving new macbook air much more. I've used this kind of a laptop for a few years
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Looking on eBay, it looks like I'm spending quite a bit more than $100 to get an old thinkpad of this era.
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I think my favorite still has to be the MacBook Air 11”. Wish they’d make that size again.
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I have one of these maxed out at the time (512GB disk, 8GB RAM, fastest processor) and it runs Mint pretty well. It's a great light-task computer. But yeah those bezels.
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That was my first Mac! I loved it but those bezels were a doozy. I think that same form factor with a larger screen would be perfect. Although I wonder how close the Neo compares.
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Why is this the favorite when the years older x230 takes up to 16GB ram ?
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Had Lenovo (X220), followed by two top XPS 13" (lighter), then the first M1 (8gb), M1 Max (64gb!), and M3. Battery, weight, Linux-like, and UX (in that order) made the M1 practical to carry and reconverted my M1 Max into a server for LLM and computation. The M3 sometimes also work as a computing server in tandem. I would love to carry again my XPS 13" with Linux but the battery duration and lifetime makes it unusable for movility.
I had the same with X230. A lovely laptop that still serves as a home server after 10 years or so from being bought, and it was already used, post-lease machine back when I bought it. MacBook Air M2 is also great machine btw, if you don't mind the macOS
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> MacBook Air M2 is also great machine btw, if you don't mind the macOS Asahi Linux if you want to.
I don't think Framework aims to be a laptop that you just set it up and forget. You own everything and that comes with some concessions. Things won't always work, software will always be tricky to make fully compatible, etc. But that's the price to pay to actually own your laptop. That said, I heard Mac OS quality has been going downhill since a few years ago
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> I heard Mac OS quality has been going downhill since a few years ago It really has. I bought a MacBook Pro in 2011 and used it throughout college. Worked great. I gave it to my friend’s little sister when she started college, and she ended up using it throughout her undergrad. She loved it, zero issues. So, that one MacBook got at least 9 years of use. Fast forward to 2020, my wife needs a laptop for law school. I figure a MacBook pro would be the simplest, easiest, and most reliable option. It wasn’t. Not only had the cost gone up (I paid ~$1,300 for my MacBook pro, while hers cost ~$2,000 for the same options, but less), but using Microsoft apps like excel, word, and powerpoint was such a hassle sometimes. The apps kept signing her out or didn’t have certain options (like formatting) that were available in the Windows versions. Installing and working with third party apps that some of her professors and classes required was also a hassle, and those apps worked inconsistently. I remember having to give her my laptop a couple of times just so she could get her work done. The battery life was significantly worse compared to my older MacBook. Her MacBook seemed so much slower, couldn’t handle as much, and was overall a crap experience. The simplicity, reliability, and ease of use that used to separate Macs from windows laptops, especially for the average user, just didn't seem to be there anymore. It’s like whatever worked before, they got away from it. So, anytime I hear someone say, “a MacBook is the best” these days all I think is, “yeah, nah, it’s crap, just like everything else, but slightly more expensive crap.”
And once Anthropic has an outage you gonna be what...twiddling your thumbs?
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This is how you justify dragging around some 2.5kg diving board of a laptop all the time?
Alas, as a Linux user, X11 doesn't seem to do that sort of thing: a 2-finger tap is nothing at all according to xev. 2-finger and 3-finger trackpad clicks are basically unreliable left and right mouse button clicks. I haven't been able to put in .Xresources entries to make some other keypad event into mouse clicks either.
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Depends on your laptop and exact trackpad model. I have a T470 and the trackpad works fine. That said, it does have three physical buttons (for working with the trackpoint), which I use with the trackpad when I want to do complex drag and drop operations.
Anthropic's internal AI use, at retail prices, now exceeds its employee pay (businessinsider.com)
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They should use Deepseek - much cheaper.
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The title is as stupid as Dario.
Everyone is saying it is expected, and I agree, but it’s also clear that employees of AI companies spending unlimited zero-cost tokens in their day-to-day work is resulting in products that aren’t usable by the vast majority of regular workers who don’t have this luxury. Dogfooding your product is good but you should also use it with the same constraints that you place on your users, otherwise what signals are you really getting?
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They're dogfooding the way Xerox PARC was dogfooding in the 01970s. By giving hundreds of workers each a powerful desk-sized Alto minicomputer for their own needs, with a high-end graphical display, they gained insight into what desk top personal computing would look like 15 years later, enough insight to shape it profoundly. It's been 55 years, and although multitouch screens are proliferating, I'm still typing this on a keyboard hooked up to a framebuffer-driven display with a mouse hooked up to it, displaying hypertext, festooned with windows, icons, and a mouse that moves an onscreen pointer at the same 135° angle they settled on 55 years ago, positioning a vertical line to indicate the insertion point, with scrollbars. The display has twice as many pixels, the pixels are color, the mouse pointer is white rather than black, the screen is a flat LCD, the scrollbars are on the right, and the cursor blinks, but it's very recognizably descended from https://smalltalkzoo.computerhistory.org/HOPL-St78.html rather than, for example, ITS or GENESYS. Only people with the luxury of unlimited zero-cost CPU cycles had a chance of seeing what the future looked like, and that allowed them to find out what worked and what didn't work in that environment. Nowadays, the regular workers who don't have the luxury of unlimited zero-cost tokens are manually reviewing voluminous AI code, because, even though that's a lot of slow work, they're still much faster programming that way than they were without it. Anthropic, instead, is doing insane things like eliciting a billion lines of Lean proofs to show that existing open-source libraries can't fail their OSS-FUZZ tests — and fixing all the bugs that effort turned up, in the process.
> Now spend 0.5x their salary on AI, and they become 5x productive compared to no AI. > > Now spend 1.1x their salary on AI, and they become 20x productive compared to no AI. This is what I am getting at. If this were true - and I've yet to see evidence it is, despite some anecdotal evidence (organizationally, IME, it's about 2-3x for power users, and probably a net loss of productivity in certain areas) - why would their headcount be growing so much still YoY, pretty much doubling every year. If the AI is 10-20xing why such a big jump in headcount? Yes, the numbers are shiny, the growth is apparent, I would just expect with this AI narrative they'd be "doing more with less" as this thing improves every year. > The AI usage still needs a knowledge worker to direct it in ways that it can't direct itself, so you still need the employees. This is the story AI sells though, and Anthropic has participated in it heavily. Yet, their interview process requires hard skills and doesn't let you use AI, so clearly, what you're saying is correct, it just doesn't really align in my head with the whole knowledge worker being replaced narrative.
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I mean, just what I did this morning with Claude would have taken me 2 weeks on my own. So 20x is pretty reasonable for certain types of engineering. But it's also true that when I'm working on 2 things at once, the bottleneck is me . I'm spending all my time giving Claude direction that it can't give itself. So you basically have to separate out the tasks where AI can produce a 20x productivity boost, and the stuff where it can't help at all. There's still so much stuff where it can't help at all, you need real human employees for that. That's why Anthropic is continuing to hire at breakneck pace. And that's what I'm saying -- knowledge workers aren't being replaced. They're just accomplishing tons more work, and companies aren't running out of work to do.
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Sorry, I know this is the story, but am I expected to believe that Anthropic would need 20,000+ engineers in their org without their use of AI? I do not believe that is close to true.
I mean, they probably could not have done most of it with open models. Again, a lot of this isn't going to standard software development, at least I would assume but instead to SOTA model development and RSI.
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Are a majority of Anthropic developers working on SOTA models and RSI? I would have guessed not.
It's kind of expected, no? If I was an Anthropic employee expected to dog-food the product and be on the frontier of usage, I'd probably be using Mythos all the time at the highest thinking level. And if I am not being metered, I'd probably do more stuff that I know are likely low yield since I am not worried about a quota. This would probably take my "API-equivalent" usage beyond the average salary in far less than a month.
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> If I was an Anthropic employee expected to dog-food the product and be on the frontier of usage, I'd probably be using Mythos all the time at the highest thinking level. Mythos at the highest thinking level is not the only product from Anthropic though.
I wonder how much dog shit has crept into their codebase by this point. Another company might dogfood their product but Anthropic is so heavily marketing oriented, I doubt this is driven by the desire to improve the product as much as it is by the desire to pad out usage numbers and create shareable stories. No matter the consequences. I bet $1 it sucks to be a good engineer in their software effort.
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>>If I was an Anthropic employee expected to dog-food the product… >I wonder how much dog shit has crept into their codebase by this point. You'd think they'd know not to shit where they eat… ?
> In March, I wrote about a new trend: Tech companies are starting to treat AI tokens (the main way to measure usage) as a fourth component of employee compensation, alongside salary, bonuses, and stock awards. There's a lot to unpack about this statement.
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I can see where there might be a truth to it. My company offers a fairly generous monthly token budget. If I were evaluating an offer from another company, but they offered a lower monthly budget, it would definitely influence my decision, all else being equal. It's not compensation, but it does affect my day-to-day experience at work.
> There's a lot to unpack about this statement. Including the fact that it's probably not true. If something is compensation, it can often be negotiated and traded off against other compensation components. How many people have successfully negotiated AI tokens away in favour of salary/bonus/stock? I'm going to guess "approximately zero".
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Is that really true? At least at large companies, the components are not usually fungible in my experience. At startups or smaller companies I'm sure it's a lot more flexible.
In the US, the IRS doesn't see it that way, at least when it comes to fringe benefits as a part of employee compensation. https://www.irs.gov/businesses/small-businesses-self-employed/employee-benefits says, "In general, the amount the employer must include is the amount by which the fair market value of the benefits is more than the sum of what the employee paid for it plus any amount that the law excludes." As an example, as I understand it, if a hotel chain allows an employee to stay in one of their hotels for free when they go on vacation, the tax value of that benefit is what they would have charged someone for that hotel room, not how much it increased the hotel's costs to have one more hotel room full — which is generally almost nothing. Of course, the IRS does agree with you when it comes to expenditures that are for the employer's benefit, rather than the employee's. If it didn't, almost all companies would have negative profits from the IRS's point of view.
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Not an apt comparison. You are conflating the opex of the company with taxable benefits. If what you said was how taxation worked, a hand tool manufactuting company giving hammers they make for $1 and retailing for $2 to workers building a shed on their property would be increasing the workers' income tax bill by $2. Of course, in reality the workers get no income tax bill on the hammer given to them for work and the company can get a $1 tax writeoff from the opex of making the hammer.
Microsoft basically does the same with internal Azure services? When I was there our budget/usage was based on and consumed at the consumer price for GPUs and other compute. What happened behind the scenes really I have no knowledge.
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Not true. Azure has a very different internal pricing. You can often get a glimpse of it if you have a.. particularly enterprising TAM. What happens sometimes (Like now when compute/GPUs are in high demand) is finance department would calculate the opportunity cost on allocating those resources internally vs selling them externally. The calculation isn't even always straight forward. What is the opportunity cost of using compute for internal CI or company operations vs selling them externally? It's not a straightforward equation and you would have to adjust the scale often depending on how clogged your internal processes get. The extremely discounted internal cost promote waste, so there is always a room for improving efficiency, but that too has a cost.
No. This is opportunity cost. A clear example is Google. They can easily give all compute to Deepmind, yet majority is allocated to be sold at market rate. So, every compute Deepmind and Googlers get is lost revenue opportunity and must be measured as such. No other internal tools or servers has this much external demand to be comparable. Also, Anthropic is showing that to operate at Anthropic level, you need $300,000 compute spend per employee
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There is a huge difference between Anthropic and Google dog-fooding: Anthropic does not own or build data centers, they rent (as far as all the reporting on this I've read). Anthropic employees dog-fooding with Claude tools isn't "internal", its most likely being run on external AI data center compute, which they have to pay for, there's just no margin on it. It might even be run out of Google's data centers.
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> No. This is opportunity cost. This is NOT the definition of opportunity cost. Please do not throw in random terms you don't understand. Opportunity cost is the value of the next best alternative you give up whenever you make a choice. WTF does it have to do with mis-classifying an expense?
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> No. This is opportunity cost. It’s not opportunity cost. It would be opportunity cost if their employees not using it would lead to additional revenue. However, if Inwas to go to Anthropic and double my token usage Anthropic wouldn’t decline my money. If Anthropic’s employees would stop using Claude, their revenues wouldn’t increase by an equivalent amount. Their revenues are not currently supply constrained. It’s just a cost cost. If their employees stopped using these services they would simply need less infrastructure, and therefore save on the cost to build and run that infrastructure. It wouldn’t translate into an increase in revenue.
I don't buy it. A company like Anthropic is not going to just walk away from revenue. If external demand were really that high, then they should take the money first. And not just for the revenue; customer demand being that high is also an indication that the product is already great as-is so they stand to improve their bottom line by easing off on the R&D spend.
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It's complete bologna. Basic GAAP accounting eliminates intra-company service consumption/sales. Looking at cloud compute, say, Amazon "bills" departments for AWS cloud compute consumption, but reporting internal cloud compute consumption as a thing they were doing assuming the rates charged to their least efficient customer would be beyond meaningless.
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> If external demand were really that high, then they should take the money first AI infrastructure is supply constrained, so you have to make a decision: how much do I allocate to training vs inference? Do I use it all for inference and do no further training? If so, what risks does that expose me to?
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Supply constrained companies don’t typically offer 50% discounts.
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It’s supply constrained for now, the moment companies like Anthropic have to switch to profit-making-mode, demand will dip as the prices skyrocket imo.
> by easing off on the R&D spend you could not be more wrong, you cannot IPO if you say product is good enough. The whole point, the bet why its worth trillions is because they will reach AGI and "singularity" first, so the gap vs open source will only increase. If you say product is great as is, then you will be caught up and game over
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I didn’t say stop, I said ease off. Acting like they’re constantly racing to catch up is not the rift behavior for a company that’s trying to present itself as a relatively stable market leader. It’s behavior that’s more consistent with a company whose leadership believes, for whatever reason, that their current position is insecure. re: AGI and the singularity, I don’t have anything really to say to that. Nobody even has a working operational definition of AGI yet, let alone a clear roadmap for what technical challenges need to be solved to get us there, let alone even the beginnings of an estimate of what it might cost or how long it might take. Nor is there a story for how that will lead immediately to Kurzweil’s technological singularity that amounts to much more than waving one’s hands and shouting, “But wouldn’t it be exciting if it were true?” Treating that as if it were even a sketch of an actual business plan isn’t rational due diligence; it’s just chasing buzzwords.
I'm impressed you have a workflow that can keep 16 separate agents fed without the whole thing collapsing into nonsense. Even running full agent teams I can't think of ways to do that without being intentionally inefficient
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I let one agent categorize all bugs, then have it decide which clusters of bugs should be addressed together, and which ones can be addressed in parallel.
You call your laptop "workstation"?
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6 years ago i had a lenovo thinkpad p1, branded by lenovo as a portable workstation. Today i have macbook pro m5 max, much faster and more powerful than the lenovo, so why not call it a workstation?
Are you talking about their $200 consumer plan? If you use 100% of the quota every week it's closer to $2000 at API rates. They have never claimed that the API rates are the "real cost" of the compute spend.
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> If you use 100% of the quota every week it's closer to $2000 at API rates. I don't know where you got that from but the only time I maxed my $20 plan for a week I made the calculation that I had spend close to $200 in a single week. So maxing a $200 plan for a month should give you $8000 worth of token at API price. Obviously it's not $300k but it's still very far from the retail price.
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> but the only time I maxed my $20 plan for a week I made the calculation that I had spend close to $200 in a single week. So maxing a $200 plan for a month should give you $8000 worth of token at API price. $200 of usage on a $20/mo plan is a 10X multiplier. The $200/month plan has 10X the usage of the $20/month plan. So $200 * 10X = $2000/month. I don't know how you got to $8000. Recent analysis by industry analysts like Semi Accurate have measured Sol 6.1 on the $200/month plan to be around $2000 of API equivalent use.
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I get a LOT of mileage out of my $20 plan. It's at least $500+ a week at API rates. I sometimes wonder if there's something wrong with their billing system.
Wikipedia tells me that "service industry" is a term that includes transportation companies and law firms. So you are apparently now claiming my local train company or law firm will be using as many tokens per employee as an A.I. lab.
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Yes service industry is quite broad, is white collar work more clear in general? Yes, it is quite obviously apparent that law firms are and will be using lots of token-based intelligence. They won't be using the same tokens at the same time as an A.I. lab. However, the best law firms of 2029 will be using approximately the same tokens per employee as an A.I. lab of 2026, that much is clear.
US boy names that became girl names and vice versa (namedaisy.com)
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A wonderful example of how gender is a social construct.
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Surprised Sue wasn't mentioned. I had heard that boys had started being called Sue (sample size of 1, but very prominent).
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It's super hard to keep track of, I have an app that's designed to help couples name their baby, and I always wanted to stay away from hard-defined gender stuff, but people still want boy/girl categories. So many are both, but to varying degrees. I ended up using a boy/girl/unisex selector, and had Jev tag all the names. It's especially when dealing with other countries, languages, and customs. At the end of the day, it's mostly easier for the user to just swipe left on a name rather than try to pre-eliminate it from their pool.
I've noticed more girls are being named Parker these days. My 1yo son is named Parker. He's holding the line.
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He can't lose!
The trend of surnames as given names is stranger to me than traditional gender reversal of names.
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s/Never trust a man with two first names/Never trust a man with two last names/.
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They go hand-in-hand. Surnames aren't gendered. Names that reverse gender are often surnames used as given names. "John" or "Matthew" are probably never going to become female. Nor will "Elizabeth" or "Katherine" become male. "Spencer" was male when Spencer Tracy was a big name. Today it could go either way. As a family name it relates to the profession of a steward.
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Surnames or occupations (Tanner, Cooper, etc)
Probably more likely that they don't get the interview because the person reviewing their CV assumed they were a woman...
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Ha, you had me at "person". As if people review resumes anymore!
There was a guy at my school named Hilary who got awful abuse for it. Always wondered why parents would do such a thing to a child.
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Did he have a brother named Sue? If so, I might know the reason ... > And he said, "Son, this world is rough > And if a man's gonna make it, he's gotta be tough > And I knew I wouldn't be there to help ya along. > So I give ya that name and I said goodbye > I knew you'd have to get tough or die > And it's the name that helped to make you strong." Johnny Cash - A Boy Named Sue
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As someone with an pretty unusual name, I think kids will always find a reason to make fun of you and it isn't always just the name. True Story: My mom was a 2nd grade teacher for 30 years and in the 70s had a student with very 'hippie" style parents. They named their son Log Cabin. You can imagine how that went over in elementary school.
I suspect this is a big driver of the switch. Parents that do not want to give their boys a name that will cause issues later on. Back in school it wasn't a problem, people knew "Loren" was male, "Lauren" was female. Now, an awful lot of people don't. It's an uncommon enough name that even if you were around back when that's how it worked you very well might not have known it. As an adult I routinely get misgendered, but it's a so-what to me.
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> As an adult I routinely get misgendered, but it's a so-what to me. You're fortunate that the spelling is distinct. The story of Kim O'Grady is depressing. https://www.thecut.com/2013/07/maybe-you-should-add-mister-to-your-resume.html
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Loren adjacent. In high school my girlfriend was Lauren and mine is Lorin. Friends over pronounced our names to differentiate. It doesn’t bother me to get misgendered, either. It never lasts past hearing my voice or seeing me, though.
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Here's my favorite "Lauren"*: https://en.wikipedia.org/wiki/Lauren_Bush *solely because her legal, married name is Lauren Bush Lauren. She actually changed it, which is gold (and honestly very sweet).
It's kind of surprising that this is even allowed. A lot of countries require at least the first given name to match the gender. Some names might be deemed suitable for both genders.
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I'm not sure "a lot" is accurate, although certainly more than I expected. Looks like Europe has several countries with legal requirements, although the trend there is moving the other direction, plus Chile.
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In the USA, you can name your kid what you want. This avoids one ethnic group requiring everyone to have a name from their tradition.
…Why would it be surprising for the USA not to have such a requirement?
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The US has unusually common unisex naming. Most other countries don't.
Interesting data. Nightmare color scale for the colorblind.
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Yeah I can't read the charts at all.
I have heard and I do believe that there are countries that use other colors for babies, but wouldn't trust wikipedia nor its selective sources on any topic like gender; wikipedia is no longer enslaved to the truth.
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You absolutely should trust wikipedia unless you can provide some evidence to the contrary; in fact, the linked article even has a whole section to support your doubt about the claim*('s veracity), which was interesting to read! From: https://en.wikipedia.org/wiki/Gendered_associations_of_pink_and_blue#Pink%E2%80%93blue_reversal > In a 2017 letter to Archives of Sexual Behavior, researcher Marco Del Giudice commented on earlier claims about a supposed shift in pink–blue color associations or preferences sometime around the 1940s, from pink for boys and blue for girls before that period, to the opposite alignment afterward. He summarized his earlier work from 2012 which found "no evidence of either reversed or inconsistent usage prior to the 1940s".[41] Del Giudice called this theory the "Pink–blue reversal" (PBR), and said it was "usually attributed to [Jo] Paoletti", and quoted from five academic articles that reprised the theory of "pink is for boys" prior to the 1940s. However, he found upon analysis that it was exceptionally difficult to actually document such a shift, and exclaimed upon "the thinness of the evidence presented in support of the PBR".[42] > In his 2012 paper, Del Giudice quoted from four articles published in academic journals which all echoed the claims about PBR theory, many relying on Paoletti, including Chiu et al., 2006: "Prior to that decade, Paoletti ... noted that the sex-dimorphic color coding of pink and blue was inverted, i.e., infant boys were dressed in pink and infant girls were dressed in blue";[43] Frassanito & Pettorini (2008): "At one point, pink was considered more of a boy's color ... blue was considered more for girls";[44] Cohen (2013): "the current stereotypical American assignment of pink to girls and blue to boys was reversed a century ago";[45] and Zucker (2005): "Yet, in the first two decades of the twentieth century, there is evidence that the gender-dimorphic nature of these two colors was inverted, that is, blue was judged to be stereotypically feminine whereas pink was judged to be stereotypically masculine."[46][47] But Paoletti never made the claim that pink and blue reversed, only that there was inconsistent usage that took until the 1950s to resolve[42] starting from the first appearances of gendered pink and blue color associations around the 1860s.[7] tl;dr - gender is very clearly a social construct and we shouldn't get hung up on colors or names - edited for clarity
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> gender is very clearly a social construct and we shouldn't get hung up on colors or names There's another dimension to this which I think the failure to find consistent gender coding in earlier years bolsters. There's some research that suggests gender signaling is more pronounced and starker in more modern, wealthy societies. In poorer societies people generally tend to not have the time, attention, or opportunities for invest in gender signaling, or fashion generally. Dress, etc, tended to be much more functional and not gendered for the sake of signaling. All the examples that typically come to mind in poorer/older societies tend to be exceptional, e.g. marriage ceremonies or aristocratic fashion.
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> in fact, the linked article even has a whole section to support your doubt about the claim I didn't say I doubted the claim, in fact I went to the trouble to say I believed it. So you should try again to glean what I could have meant.
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> You absolutely should trust wikipedia unless you can provide some evidence to the contrary ur turn to glean
There are a few names I think are being confused. Jan, short for Janice is a female name, but Jan in Central / Eastern Europe as a form of John is masculine. Jean the female name and Jean the french male name are different.
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I was going to say the same about Jean; I think that one at least is hard to really draw conclusions from without additional data like languages spoken at home. Anecdotally, the boy->girl names are almost all very popular names where I've met multiple each of those across different ages, whereas the other two categories feel like they have a lot more down-list entries.
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Going by the peak time on the chart, Jean flipped over fast right about when Jean-Luc entered public consciousness.
You're the victim of misinformation. In the past there were no hard associations between sexes and gender and it was possible to find boys wearing some pink clothing, but it was never the case that people associated pink with boys and blue with girls. There are some limited examples that contribute to the misunderstanding. For example blue is often associated with the Virgin Mary and red (not pink) was considered a manly color often worn by warriors (e.g. the British, the Romans, etc). --- This is essentially the way reporting works. If you write an article showing that in the past it wouldn't have been bizarre for boys to wear pink you don't get much traction. But if you write how pink was actually worn by boys and it was considered shocking for girls to wear it, then people find that very surprising and you get a lot of views (truth be damned).
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[delayed]
Good luck to the Perl function Text::GenderFromName() Maybe it needs the birthday
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Why did anyone even try and make this? It's fascinating what incomputable functions people try to shoe-horn into being computable.
I guess it's eternally stuck in the 90s. I didn't see Perl in a long time now. 10-15 years ago it was still everywhere. edit: No, it's stuck in the 80s: "The data comes from a 5% sampling of Social Security card applications with dates of birth from January 1980 through December 1989" https://metacpan.org/pod/Text::GenderFromName#REGARDING-THE-DEFAULT-LIST
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At what age are social security numbers issued? Folks born in 1989 weren't adults until the 2000s
My biggest WTF on this (as a foreigner) was the late Lindsey Graham. I always knew Lindsey/Lindsay as a female name. Either way, peeking through the list, seems to me names which end with a vowel are usually feminine. However, there's a caveat: names end up shortened, and over time even those get shortened. 'Brit', 'Britney' for 'Brittany'. 'Gerry' or 'Geri' or 'Ger' for 'Gareth' (Dutch variant: 'Gerrit'), 'Pat', 'Patty' for 'Patrick', 'Patricia'. 'Pen', 'Penny' for 'Penelope' 'Ash' for 'Ashley'. 'Tash' or 'Tasha' for 'Natasha', 'Nata(s)cha' (a variant of Nathan/Nathaniel?) 'Toni', 'Tony', or 'Ton' for 'Antonia', 'Anton', or 'Antonius'. Skimming through the quick examples I came up with, one thing stands out: if it ends with an 'a', feminine. I believe this stems from Latin? It also appears Brittany is a very British example, whereas say 'Tony' stems from a Catholic background. People with that background get very traditional names, but they're always practically shortened. Annoyingly, you'd have to mention your complete name on say a form, but otherwise you get a wider choice since you have like three names, and they're relatively long so more variety to pick from.
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Lindsey (as well as Ashley, Tracy, Kelly, among others) are all, I believe, last names that became given names. They skewed female over time because they end with a vowel. Ashley Williams is the name of two American actresses as well as two male soccer players (Welsh and Liberian) and a male boxer (also Welsh).
Andrea, Simone, Nicola, Michele, Daniele in Italian are all male names, but English speakers would probably assume the person is female from the name alone.
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True, good native and traditional cultutal exceptions of a rule of thumb. Speaking for myself (NL) we have a small amount of Italian names and heritage (also due to Catholicism), and say NYC would have much more Italian descendants. Also, as someone who saw quite some football (non-US version), I ofcourse am familiar with a lot of names. For example, Andrea Pirlo. We also learn some via history at school, since Italy plays a prominent role in Europe's history. Regarding Nicola, people might be familiar with Nikola Tesla (the 'c' in this case, sounds like 'k') and it is just a variant of 'Nico', 'Nicole', 'Nicolas'. Then there's some dude at FIFA, 'Gianni' which is a variant of 'Jean', 'Jan', 'Jeanne', 'Janet', 'Jannie', 'Janine', etc. I could go on about Gianluigi Buffon... What I just remind myself with regards to Italian is it tends to add a vowel at end of a word or name, but it often doesn't sound same in English or my native tongue (Dutch).
I have no data but feel that boys tend to get the family names and biblical names (in US anyways). It's rare to hear of a girl named Elizabeth III or Mary Junior but quite common for those concepts in boys. So I think the boy names are heavily weighted on probably the most popular ~25 or so names. Since girl names are more free to follow whatever is fashionable at the time, trends move faster. My son is named after his grandfather, and it's an overly common name in English (American and British). Definitely a top 3 most common for last several centuries
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> I have no data but feel that boys tend to get the family names and biblical names (in US anyways). Curiously, in the last few months in the U.S. I've met a Tamar and an Esther, both women given family names that were drawn from the bible.
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Anecdata: I’m a guy and a III. My son almost was a IV but we chose another first name and used my (and my dad’s and my grandfather’s) name for his middle name. My great grandfather had a different name, but I think his dad and maybe grandfather had the same name as me.
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Not to offend, but I think it has declined because this naming of Jr, III, and so on has come to be associated with poor or rural people. For what it’s worth, I have a relative who is a IV
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I’d agree the trend is waning if that’s what you’re getting at but I think it is baked into the history of this dataset and is also still significantly more common for boys than girls Also, IV is really quite rare for boys too. Junior still super common.
It seems there are lots of cases across the board where "women adopt traditionally male thing" has become the norm in this timeframe but not many where "men adopt traditionally female thing" at quite the same rate or scale.
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That is the pattern. Rarely would you have a baby boy using a women's name. There's more of a general stigma within society going the other direction then women adopting male things.
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I think there's something to this, but also you've got to think about the cultural standards where "female" is considered "abnormal". e.g. you have "toys" and "girl toys". "clothes" and "girl clothes" and such. It's not everywhere or everything but there is a trend.
I'm gonna credit George RR Martin with flipping Arya in the mid '90s
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Ah, back when he still wrote. Not that I'm bitter or anything
Claude Opus 5.5 Can Draw Permit-Level Architectural Drawings (stephenjgallagher.substack.com)
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Given how good the leading models got at 3D model creation over the past few months - Blender, Three.js, etc - it's not surprising to see that their 2D CAD-style abilities have improved to this extent as well. (Amusingly the pelican-on-a-bicycle test doesn't capture this very effectively, despite testing 2D drawing with SVG - because pelicans can't write bicycles, so the results are inherently unrealistic. Having the model create an architectural diagram from a concept sketch is a much more useful 2D test.)
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I don't know how much time is spent 'drafting' at architecture practices vs modelling. The drawings can be resolved from a data-enriched 3D model, which is normally where the hard hours go.
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I'm a PE who has been tinkering with LLMs for a few years now. Opus 5.5 does seem to be a game changer for drafting. I don't generate with python tho, I have it drive AutoCAD headlessly and use our firm's drafting standards/templates. Its a junior-level EIT at first, but I give it redlines via Bluebeam MCP and it updates the relevant CAD SOP for all future sessions.
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Washington State is trying out a 'Permit-Ready Plans' program in a few cities, were pre-approved plans are offered at no cost. According to their initial study, building plans account for 5-20% of total construction costs. Software that might be able to shave 10% off new construction costs is a big deal.
I feel bad for all the inspectors who are going to have to do inspections on vibe-architected buildings in the next 12-18 months.
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I doubt that's going to happen. 1) Permitting is slow and, at some point, if you fuck it up big enough, the inspectors will probably take further steps, but otherwise not care much. You simply won't get a permit. 2) Who will care a lot are the builders and creditors. Building is expensive and if there's a couple of months of set back because of your fantasy drawings, that's not going to be in your favor. Which is not so say AI planning is not going to happen. It will. But at that point it's probably mostly going to work.
Moving our warehouse off DuckDB (posthog.com)
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There are two kinds of companies: those who know how to build low-level tools that serve as foundation and moat for business growth, and those whose middle managers wring their hands about what their people will be able to maintain and constantly chase off-the-shelf solutions to stitch together. I know which company I'd rather pick as a vendor.
Not sure their singlenode customers will be happy with Trino https://benchmark.clickhouse.com/#system=+Hoaus|ucqs|Tuts&type=-&machine=+gel&cluster_size=-&opensource=-&hardware=+c&tuned=+n&storage=-&metric=combined&queries=-
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Author here. Good point. Trino is not made for fast response times. We are using it for long running data modelling jobs or nightly ETLs.
Now they have their "own flavor" of Trino and a brand new open table format called "HogLake". This gives the impression of making excuses with little introspection. It would be great to see their ducklake fork, their patches and github issues so the community can learn.
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Author here. Our fork, like most of our work is public on Github: https://github.com/postHog/ducklake I think it does not include 100% of all changes since a few we upstreamed directly (to a few extensions related to Ducklake too) but if you are really interested, you can find them too.
Sometimes a company just isn't able to manage a data warehouse; I've worked for a few. I even phone screened with this one but couldn't cover their crazy quilt of requirements; at that time they were also looking for someone to rewrite the clickhouse optimizer, and they were stuck trying to reshard their cluster, which should take an afternoon. I still like the company because their business prop reminds me of what we were doing in 2009, a kind of federated analytics organization on a centralized data warehouse that enables a lot of tools to be developed quickly at large scale. But goddammit they keep picking these half-working platforms and flip-flopping from one to another. We were crushing millions of queries against 2T-row tables on Vertica in 2010, and it's only gotten better for customer-facing data apps, which is what Posthog is. The company doesn't seem to have a baseline of what to expect; the market is too saturated with slow tools that lower expectations.
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Author here. This is not about our internal warehouse but the warehouse product we offer to customers. This is still running on our centralized Clickhouse. Long-running data modelling queries and multi-tenancy is a challenge on Clickhouse.
I wonder if they have considered moving back to ClickHouse. ClickHouse Iceberg support has improved a lot over the past few months. You can easily run stateless ClickHouse on top of Iceberg. This solves the tenancy issue, and it can easily handle petabytes scale [1]. [1] https://clickhouse.com/blog/jump-trading-uses-clickhouse-with-iceberg
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Author here. We didn't leave Clickhouse. It still drives most of what Posthog offers. I missed that bit of context in my post I admit. Instead we are looking into a new stack we can give customers so they can run their warehousing workloads on it instead of the centralized CH. Stateless CH on Iceberg sounds interesting, we looked into it but Delta/Iceberg had other downsides for us.
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But why even bother with ClickHouse? What's wrong with Trino?
The key insight I am getting from this is that as migrations get easier to do with agents, there will be a lot more of them. But more importantly a lot of them will happen because we will all get more trigger happy to start one. On the other hand I also don't know if at scales like PostHog, a successful migration can be tested without doing all of it.
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Author here. I agree. We spent most of the time to make it work at the scale of our large design partners and probably should have stepped back earlier. And yes, with an agent you can have a much larger scope hashed out faster than before.
> Five months ago, we rebuilt our warehouse on DuckDB instead of ClickHoue They switched from ClickHouse to DuckDB five months ago, then switched from DuckDB to their own Trino derivative? The article then ends before saying if the new setup solved their problems. It’s great that we can now make these migrations with little downtime (I assume?) and try different things, but I wish we could have read more about what testing they did before jumping. The fact that they jumped to DuckDB without realizing it wasn’t going to work at their scale and spent only a few months with it before jumping again is not convincing. I hoe there’s more to this story that just didn’t make it into the blog posts. As written it’s giving me flashbacks to some teams I worked with who changed tech stacks every six months because they liked migrating more than tuning and maintaining.
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> The article then ends before saying if the new setup solved their problems. This reads to me like a recruiting post; thats why they are open if it solved their problems. I'm not a fan of the way they framed it, it seems they have made their architecture decision and now need help implementing this. I'd imagine if you are the kind of person that wants to work on large scale data query problems this is an invite for you to apply. That said, if you are that person it might not be ideal to join after all the fun decisions have been made.
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> The article then ends before saying if the new setup solved their problems. They got to put ClickHouse, DuckDB and Trino on their resume & LinkedIn. Problem solved!
I think it was closer to what they need; it comes down to keeping TB of data on local SSD and having a query engine next to it. That takes persistent, shared CPU, caching, sharding, resource management, etc. Duckdb is an interesting approach to resource management (all ephemeral), but TB's are TB's. I doubt it was finding data where it needed it. Clickhouse seems slow at getting to the top end of scaling; it's stuck with the 99% of its userbase doing 1 GB queries. I'm hoping they put some of their money into it.
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ClickHouse is fast OLAP. Just do Iceberg with Trino like a normal big data person. WTF?
Russian ties? https://news.ycombinator.com/item?id=33082224
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That's where it started very long ago, but they are based out of the Netherlands mostly now. https://clickhouse.com/blog/we-stand-with-ukraine > We have no infrastructure, servers or people in Russia. The original engineering team successfully moved out of Russia and are now working in our Amsterdam office.
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You can take the guy out of Russia.. :) I kid but that's probably what people have a problem with.
> Five months ago, we rebuilt our warehouse [1] on DuckDB instead of ClickHouse. Why did they write this post if they had not even allowed things to settle. It sounds like someone wanted to claim victory (and promo?) https://posthog.com/blog/why-we-rebuilt-our-data-warehouse
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Author here. I admit I kinda left out the context which is important here. We did not replace Clickhouse. Instead we want to move our warehouse product from Clickhouse to another stack which suits the long modeling jobs and multi-tenancy better. We learned through all our early design partners running huge workloads what we need to change. As much as I'd love to claim victory, we are not there yet :)
Engineers like to experiment and we get the benefit of learning from their experiences. Not sure why you’re upset.
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> Engineers like to experiment The job of management is to help manage that. Typically, the desire to experiment is constrained to lab environments and so on. Experimenting on your actual users carries a lot of risks - to product stability, customer relations, market perception, etc.
This sounds more like a 5 month POC that the engineer should have been able to prove sooner that DucksDB didn’t fit the use case.
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Author here. We went past the POC stage to actually make real customer workloads work, which we did. Probably yes, we spent too much time not rethinking our approach but sunken cost fallacy so that's why.
Hi! Author here. We engineered, then we measured and then we tried to make it work, probably for a too long of a time before we decided to completely scrap our current architecture and go back to the drawing board. Happy to answer more questions.
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Why didn't you just use Iceberg and Trino from the get go (or Paimon if you are fancy)? This has been the accepted answer for quite some time now. The fast OLAP stores just don't scale as well as going object store to a proper query engine like Trino.
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> Happy to answer more questions. Ah yay, I appreciate it! I feel like its rare to get a look at how these decisions cone about. What did you measure? How'd you realise there was a problem? And did you measure anything to give you confidence that Trino won't hit the same issues?
If I was a user of this product I'd be really worried about the "We rewrote our software 5 months ago, but that didn't solve the issue we wanted to solve so we're doing it again, maybe this time we'll fix it" message of this post.
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[Author] it was more like: we underestimated the problem and complexity of workloads our customers want to run. We did not rewrite anything but developing a new stack we can give to our customers doing warehousing. Agreed that this context is not really clear from the blog post.
Unironically, I think we will see a lot more of this given how engineering is being done currently. I have been involved in 2 green field projects in the last 2 years. Both have been rewritten or had massive "ship of theseus" type changes multiple times over that time window. Engineers working on new products, thanks to LLMs, have very little understanding of the technical details of the product. They have the same level of understanding a traditional high level manager had of products they owned. If you ever worked in an engineering org with an M2 or M3 who always attended your outage review, and in every outage review something has to involve some issue with Postgres or your Kafka queue, that disconnected M3 would conclude: "Almost every outage involves some problem with Postgres. My conclusion, observed over the last 6-12 months, Postgres is bad. I see this new FancyDB or DynamoDB thing is popular on Twitter. We should try that" I have lost count of the number of idiotic takes like that from M2s or M3s who have no idea how things work but instead focus on keywords they can latch onto that seems to be in the intersection of all issues. Then the logical solution is just to remove that and see what happens. This used to be very expensive, but if you can throw an LLM at a code base and say "Replace Postgres with FancyDB, split it to a list of logical checkpoints adding regression testing when missing to each checkpoint and open stacked PRs for all checkpoints", let it churn for an after noon, and 46k-line change PR (and $800 token bill) later you are ready to try FancyDB, why would you not give it a try? Then if you have issues with FancyDB, are you gonna spend the time to understand what's going on or just say "lets try DynamoDB next"?
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I have lost count of the number of idiotic takes like that from M2s or M3s who have no idea how things work but instead focus on keywords they can latch onto that seems to be in the intersection of all issues. This phenomenon is at the root of the hardest organizational & architectural challenges I’ve been involved in. It really needs a name so it can be tagged as a leadership anti-pattern. Good leaders find real connections to explore & strengthen. Bad leaders reach conclusions at the fuzzy pattern matching stage.
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I worked at so many companies that operated this way, the tool is new but the approach is not. Those failed startups you hear about usually did a couple of these before hitting the ground
To me to key “insight” is that if you are going to spin up single VMs (or even groups) per-customer and then route queries, you need to be able to estimate the query cost first. I know snowflake does this, they do the query optimization before sending it for execution. So it knows about how many resources will be needed (it can obviously be wrong).
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[Author] Basically yes, but we spun up pods on EKS. It was hard for the customer to estimate how much they might need and hard for us to know how much capacity to provide. Given our plans on pricing on CPUHours (or similar) the logic was kinda broken.
How does Snowflake use that information? You still need to pick the warehouse. It would be cool if there was an "elastic warehouse" where heavier queries are routed to bigger Warehouses, but that's not the case
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[Author] Basically what we are doing with the help of Trino: a distributed query engine which can use as many resources as the query needs dynamically.
There is an elastic option, I think . Also, even with a specific warehouse, not every query uses every node in the warehouse.
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Right, there is an option to scale horizontally, if a lot of queries are queued, Snowflake can spin up another node. But that doesn't help if you query is spilling to remote storage. You need a bigger node to speed up those queries. Snowflake has an option to add more resources, which is supposed to be vertical scaling, but it doesn't work as well as increasing the size of the warehouse
Is Quack, the DuckDB client-server protocol, something that could have helped them with the scaling problems they encountered?
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Author here. Good question. AFAIK you cannot use Quack for anything that looks remotely like distributed querying.
Ask HN: Who is hiring? (November 2026)
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ArtCraft | Senior Engineers | SF (Onsite) / Atlanta (Onsite) | $150-$250k + Equity | https://getartcraft.com Those fucking rent-seeking hyperscalers took the internet away from you, and we’re going to give it back to you and to everyone. Web 1.0 was great - we had IRC, file sharing, third party chat clients. There were personal websites, forums. Flash was a format kids could use. Everything supported embedding and uploading. Websites actually had APIs and RSS. File sharing, FTP, MP3s, discs, owned media. Broadband brought our parents and grandparents online, but the shift to the non-technical majority created an opportunity to grossly oversimplify everything. Everything dumbed down into a pre-packaged product. Startups began turning their offerings into walled gardens. Platforms took precedence over protocols. APIs and access and data export went away. And then the rent-seeking began. The era of ownership ended. Corporate Memphis. Jesus Christ. We’ve rallied a massive community to build MIT/Apache-licensed alternatives to Adobe, Microsoft Office, Google Workspace, Autodesk, SolidWorks, Slack, Discord, Unreal Engine, OpenRouter, RunPod, and more. The goal is full feature parity, with code anyone can own, inspect, modify, and build on. We’re digesting second-class apps and platforms into first-class applications, libraries, and APIs with full MCP support. We’re distilling out the good parts, and we’re building the connective tissue that draws them together. 100% of the internet is going to be open source soon, and we’re going to force it open. Loudly. We have eight figures in run rate revenue, over 20M app downloads and growing. Our community is the best part, and it’s energetic like a wildfire. Everyone resonates with our mission. We’re missionaries, not mercenaries. We are going to slay the incumbents by being better. Our motto is Google’s old motto - “Don't be evil (tm)”. We’re a tiny team looking for strong engineers to own major parts of the product: desktop apps, lots of completely open source backend infrastructure, agent workflows, agentic app factories. Stack: Rust, a sprinkle of TypeScript/React, egui, Tauri, MySQL/Postgres, Redis, Elasticsearch, Kubernetes. Lots and lots of Rust. We’re systems engineers by trade, but we like to vibe code Rust. Did I say Rust? Rust. Rust Rust Rust. Maybe that's a filter. You have to be self-directed and independent. If you want to open source Salesforce with half your time, do it! If you want to work on Solidworks 3D printing applications, great! Writing music apps and DAWs? Go for it! Custom Discord/Slack clients for our custom, completely open source chat API and platform? Hell yeah. Our organization is flat, and we're going to go after everybody and everything. Everything you build here will be open source. We have no private repos. We can reclaim the internet. That’s our mission. Want to know more about us? Look up “Adobe ArtCraft” on YouTube / TikTok / your platform of choice. If this resonates with you, email hn@storyteller.ai with your Github, a little about yourself and something you’ve built. Write the sentence, “don’t take my RAM, Sam!” so we know you’re one of the good guys.
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Odoo | Software Developer (Python / JavaScript) | Grand-Rosière (near Brussels), Belgium | Hybrid, 3 days/week in office | Full-time | €10k signing bonus Odoo is an open-source suite of business apps (CRM, accounting, inventory, payroll...) used by millions. I'm on the Belgian payroll team: Python, an in-house ORM, and real business logic thousands of companies run on. You ship to production fast and code is mostly open source. Juniors and recent grads welcome. Package includes a company car, meal vouchers and a €10k signing bonus. Apply: https://www.odoo.com/r/zbNF
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Evaboot | Agentic Python Engineer | REMOTE worldwide | Full-time | $60-120K USD/year Evaboot turns LinkedIn Sales Navigator searches into clean, verified prospecting lists. Demo: https://www.youtube.com/watch?v=khYgyDlo2Iw Bootstrapped, $2.2M+ ARR, team of 5, remote since day one. What we're doing: building agentic products, workflows and architectures. Agentic products you'll work on: SDR agent (sales navigator agent, emailing outreach agent). Agentic workflows you'll build: coding, support, SEO & content, acquisition automations, and analytics. Agentic architectures you'll work on: company-wide systems, memory, tooling, security, and evaluations. You will work directly with me (co-founder & CEO). Requirements: strong Python engineering, power user of agentic coding, strong architectural thinking. Bonus points: AWS deployment & infrastructure, Langfuse for observability & evaluations. What's guaranteed: intense execution pace & exponential learning curve. Zero bullshit environment, we focus mostly on results and KPIs. Autodidacts are welcome. Two weeks maximum from apply to reply. Apply right here: https://forms.gle/ALgZfzwpZU8UXvxg8
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eventfirst | Senior Full-Stack Engineer | Berlin, Germany | REMOTE (CET) | Full-time | eventfirst.com We are applying AI to organize corporate events. We are looking for a senior engineer with at least ten years of full stack experience, a strong focus on product and UX, and some experience building an AI chat based product. Our tech stack is Typescript, React, Next.js and Tailwind. On the backend we use Drizzle with Neon, deployed and monitored via Vercel. Agents and background jobs are executed via trigger.dev. This gives us a killer DX because the entire tech stack supports preview branching. This allows coding agents to work in parallel on different features and verify their work independently very close to what will run in prod. CI is fast (2-3 min) and coverage is good enough to deploy to prod many times per day. Please note that we are working remotely in the CET timezone. Having some remote experience is a plus. We have pre-seed funding from a major US VC and are experienced founders. You’ll be working alongside the founders (ex-Apple, ex-Airbnb, ex-Tulip, ex-Tourlane) and will have a chance to shape the company, product and of course the engineering culture. Apply here: https://eventfirst.jobs.personio.com/job/2870690
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Data Micro Technologies | Multiple Roles (OT, Networking, Security) | Jacksonville, FL | ONSITE Data Micro Technologies provides specialized systems engineering, operational technology (OT), and infrastructure consulting. The interview process will not be long and drawn out. We want to fill these roles quickly. We are actively hiring for the following roles: 1. Automation Network Engineer (1-Year Contract | Onsite) Designing and maintaining isolated network environments for automation, virtualization (Proxmox SDN), and on-prem Kubernetes clusters. - Stack/Focus: SONiC (SonicNOS), Edgecore DCS202, SSE-C4632 100G switching, Linux administration, L2/L3 segmentation, GitOps workflows. - Requirements: 5–7 years experience in data center/industrial networking, container networking, and high-availability switch architectures. 2. Systems Engineer – Warehouse Automation & OT ($105k | 1-Year Contract-to-Hire | Onsite) Bridging warehouse-floor industrial automation with IT/OT infrastructure at the Deerwood campus and the new automated distribution center near JAX. Potential conversion to J&J Vision Staff Engineer. - Stack/Focus: Allen-Bradley/Rockwell (ControlLogix, FactoryTalk, ladder logic), WMS/WCS, conveyors, sortation, ASRS, and OT infrastructure. - Requirements: 5+ years in industrial automation/systems engineering with 3+ years in PLC/controls troubleshooting and automated material handling environments (FDA/cGMP a plus). 3. Senior Cyber Security Risk and Governance Analyst – OT Supply Chain (90k–105k | Full-time | Onsite) Securing OT/IT environments across manufacturing and supply chain operations; driving risk remediation in highly regulated medical device environments. - Stack/Focus: OT/ICS security, CSRI risk assessments, application whitelisting, Active Directory, network change reviews, vendor risk. - Requirements: 2+ years hands-on in security/risk within manufacturing or OT environments; familiarity with NIST, ISA/IEC 62443, or CIS Controls. To apply: Send your resume to chase@datamicrotn.com with the role title in the subject line.
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Strello Health | Toronto (hybrid in-person/virtual) Clinic Sales & Onboarding Lead | https://strello.health Strello is an AI front desk for Canadian medical clinics. It answers calls, books and moves appointments, and works directly inside the clinic's EMR. We're physician-founded (I'm a practising rheumatologist), and the product came out of our own front-desk turnover problems. What you'll do: - Own inbound leads and respond fast. Screen for fit first: are they on an EMR we integrate with, and is Strello the right answer for their phones? - Run discovery and demo calls with physicians and clinic managers, then quote, close, send contracts and payment links, and keep the CRM current. - Lead onboarding: workflow meetings with clinic staff, phone and EMR access, and launch coordination with our engineers. - Stay the go-to contact after launch, and bring what you hear back to the product team. You might be a fit if you've worked in sales, or clinic operations (MOA, coordinator, manager), or healthcare SaaS account management, or customer success. You should be comfortable on the phone and on video with physicians, organized enough to run many clinics in parallel, and happy to help write the playbook at an early-stage company. Apply: reza@strello.health with a few lines on the clinics or customers you've worked with.
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DuckDuckGo - we are looking for candidates that are excited to join us on a mission to raise the standard of trust online. All of our roles are fully-remote, except where specific locations are noted. Senior Web Security Engineer, Browser Platform - https://jobs.ashbyhq.com/duck-duck-go/a447e823-fd8f-438f-909 ... Senior Backend Engineer - https://jobs.ashbyhq.com/duck-duck-go/53022b02-da3d-4fda-8273-c897d27ed50d?utm_source=1DKZJgG9d9 Staff Data Scientist - https://jobs.ashbyhq.com/duck-duck-go/9c381171-f346-4d7a-876a-509fe046760f?utm_source=1DKZJgG9d9 Senior Data Scientist - https://jobs.ashbyhq.com/duck-duck-go/a447e823-fd8f-438f-909e-db1f6ced8c97?utm_source=1DKZJgG9d9 Director, Paid Marketing (Subscriptions) - (Remote within USA) - https://jobs.ashbyhq.com/duck-duck-go/f8570953-8ea3-4955-bfbf-dd67a56df5f5?utm_source=1DKZJgG9d9 Senior Product Partnerships Manager (Remote within USA or Canada) - https://jobs.ashbyhq.com/duck-duck-go/dc1027ae-8f6a-44eb-b116-f945d2f95fad?utm_source=1DKZJgG9d9 Senior C++ Engineer - https://jobs.ashbyhq.com/duck-duck-go/af93b075-d60a-4686-abeb-5949206d2f53?utm_source=1DKZJgG9d9 Senior Privacy Engineer - https://jobs.ashbyhq.com/duck-duck-go/80797cf4-64b2-4e94-9d87-6f2ecc45c862?utm_source=1DKZJgG9d9 Senior Web Compatibility Engineer - https://jobs.ashbyhq.com/duck-duck-go/d02d7598-141b-4a84-bdf6-46677da89b08?utm_source=1DKZJgG9d9 and MORE: https://duckduckgo.com/hiring
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Reducto | Multiple Engineering Roles | San Francisco | ONSITE | Full-time | 200k - 325k + Equity | https://reducto.ai Reducto is the agentic document platform for leading AI teams who need enterprise performance at scale. Most of the world's important information is locked in documents: PDFs, spreadsheets, scanned forms, financial filings. We build the infrastructure that lets AI read and work with them the way a human would, combining custom in-house models with leading frontier models to power accurate, efficient document workflows. Our customers include AI teams like Harvey, Vanta, and Scale, along with enterprises across FAANG and top trading firms. We've grown revenue 8x year over year, partnered with hundreds of companies, and raised over $100M from a16z, Benchmark, and First Round Capital. We're still a small team, so every engineer has outsized ownership. You'll work directly with customers and leadership, ship quickly, and solve hard problems across ML, infrastructure, and product that directly shape how AI systems understand the world's documents. We're in person in SF, with free daily lunch, unlimited PTO, generous health coverage, transportation reimbursement, and a monthly wellness budget. Open roles: - Forward Deployed Engineer - Product Engineer - ML Engineer - Head of Product Engineering - Many More! Apply here: [ https://jobs.ashbyhq.com/reducto?utm_source=Qp0OepaMn9 ]
Namespace | San Francisco, CA / New York, NY / Zurich, Switzerland / Remote | Full-time | REMOTE or HYBRID | https://namespace.so Namespace is a vertically integrated infrastructure stack for software development. We build everything ourselves, from the server racks to the hypervisor and scheduler, and we run it globally. Teams at SpaceXAI, Ramp, Sierra, Fal, Vanta, Framer, ElevenLabs, and many others build their software on Namespace today. Open roles (all full-time, global, remote & hybrid): Customer-Facing Software Engineer Product Engineer Infrastructure Software Engineer Security Engineer DevOps Engineer Engineering Lead Details and applications: https://namespace.so/careers
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Hi! All the role you list on your careers page appear to be hybrid. Can you clarify which roles are remote?
Ask HN: Who wants to be hired? (November 2026)
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I've been working on production-grade AWS deployments for over 10 years, so it's a bit hard to frame my experience/skill set. That being said, if you need help with almost anything AWS - architecture, infrastructure, performance, scale - feel free to reach out. Although versed in Well-Architected/multi-region/multi-account, I strive to supply the simplest solution for your particular scenario. Location: US EST Remote: Only Technologies: IAM, VPC, Cloudwatch, EC2/ASG/ELB, Lambda, API Gateway, RDS, Redshift, DynamoDB, CodeDeploy, Cognito, Athena, S3, Cloudfront, Kinesis, SQS, SNS, IoT Core, Sagemaker, ElastiCache, MediaConvert Email: hn@cldcntrl.com
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Location: Accra, Ghana (GMT+0) Remote: Yes Willing to relocate: Open to it Technologies: TypeScript, React, Next.js, Node, Python, FastAPI, PostgreSQL (Supabase, pgvector), Redis, LLM APIs (Claude, Gemini), embeddings/RAG, Vercel, Fly.io, GitHub Actions Résumé/CV: https://drive.google.com/file/d/1UKN9Lw5lL34NNxoQtCzOxVTa3jtRPjAf/view Email: davidiphy.works [at] gmail.com Portfolio: https://www.davidiphy.dev GitHub: https://github.com/Iph22 Full-stack engineer and CS student at the University of Ghana. I built and run Arcyn Find ( https://arcynfind.com ), a live AI-tool search engine with 15,500+ tools, 5,900+ SEO pages and a 15-language interface, from first commit to production in under a year. A few things I've shipped there: - Hybrid vector + full-text search with LLM re-ranking, raising top-1 recommendation accuracy from 62% to 81% on a labelled eval set. - Traced a duplicate-ingest bug (94% of 273k rows were duplicates) to one misplaced .limit() and safely removed 257,956 rows. - Rewrote a job that failed 40 runs out of 40 as one set-based SQL function that finishes in 733 ms. - Fixed an SSRF hole and spoofable rate limiting, then added Redis rate limiting after a ~28,000-request bot flood. I also co-founded Analify ( https://analify.fly.dev ), a cookieless analytics product in private beta, with one co-founder. I built its AI features, crawlers and traffic filtering. Looking for a junior or mid-level full-stack or AI engineering role on a team where I can own features end-to-end. Happy to do a take-home or walk through any of the code.
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Location: Seattle, WA Remote: Yes (US Pacific time, available evenings/weekends too) Willing to relocate: No Technologies: Python, TypeScript/JavaScript, Node, FastAPI, React/Next.js, Postgres/SQLite, Stripe API + webhooks, Solana RPC/websockets (read-only alerts), Playwright/requests scrapers, Google Sheets/Slack/Telegram/Discord APIs, local LLMs (Ollama/qwen), Swift/iOS (side projects) Résumé/CV: https://github.com/AugustusTheGuy Email: builtxbyxbear@gmail.com Solo dev who ships small automations fast, often the same day. Fixed-price work I do regularly: - Website -> CSV/Sheets export script, free 20-row sample first ($297) - Stripe payment -> Google Sheet + Slack/email alerts ($397) - Solana wallet watch -> Telegram/Discord alerts, read-only, no keys ($449) I also take hourly or contract work on Python/TS backends, integrations and internal tools.
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Location: Austin, TX Remote: Yes Willing to relocate: Yes — Denver Technologies: TypeScript, React, React Native, Python, PostgreSQL, Supabase, GCP LinkedIn: https://www.linkedin.com/in/adambiele Email: adam@adambiele.com I'm a software engineer with experience taking web and mobile products from initial requirements through production, including owning engineering as a startup's sole engineer. My work spans multi-tenant applications, data pipelines, AI integrations, subscriptions, payments, and access controls, along with the testing and operations that keep them running. I'm looking for software engineering roles, with a particular interest in backend systems. I bring experience across the full stack and would like to join a team where I can take ownership of meaningful technical problems and grow alongside experienced engineers. Outside of work, I enjoy art history, gravel cycling, and rock climbing.
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Principal Software Engineer and Open Source Maintainer with 7+ years of experience as a core contributor to open source platforms. I'm a versatile full-stack developer with deep experience in backend architecture, distributed systems, and building complete data/ETL pipelines. Beyond coding, I am focused on creating business value and bridging the gap between engineering, customers, and operations. I recently led the end-to-end delivery of a multi-tenant B2B compliance SaaS that tracks over 50M retail-ready units per month. I have also authored 10 comprehensive technical proposals for state government projects and deployed an OpenClaw agentic AI system into a phone-support CRM that slashed agent recovery time by 75%. I'm looking for a senior to principal-level role where I can solve complex technical challenges and drive business value. Location: Seattle, WA Remote: Remote, Hybrid, Onsite Willing to relocate: No Technologies: * Cloud: AWS, GCP, Kubernetes, Docker, Terraform, GitLab CI/CD, distributed systems * Languages: Python, Node.js, TypeScript, JavaScript, React, Go, Rust, PHP, Bash * Data: PostgreSQL, MySQL, NoSQL, ETL, Data Warehousing * DevOps/Tools: Git, Linux, Automation, Reliability, Testing, Graph Engineering, Evals * Architecture: Ollama, Microservices, Data Modeling, REST/gRPC APIs, RAG Pipelines Resume/CV: https://content.mashio.net/wp-content/uploads/2026/09/Walther-ResumeA.pdf Email: matt@mashio.net
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Location: SF Bay area, CA, USA Remote: Fine w/ Remote or Hybrid or In-office Willing to relocate: No, want to stay in Bay area Technologies: Python, C++, PyTorch, OpenCV, Spring Boot, React, TypeScript, PostgreSQL, OracleSQL, Linux/Shell. Website: https://dhawal-modi.github.io/ Résumé/CV: https://dhawal-modi.github.io/data/Resume.pdf Email: dhawal [dot] modi07 [at] gmail [dot] com I’m an ML Engineer with a software engineering background and an MS in EECS. My recent work has been around deep learning, computer vision and data workflows for real-world ML systems. Before moving into ML, I worked as a back-end Software Engineer building payment processing systems with Java/Spring, REST APIs, and SQL databases. I’m looking for Applied AI/ML Engineer, Computer Vision Engineer, or SWE roles. I’m especially interested in teams building practical ML systems or applied AI products. Sponsorship not needed for US roles. (US Permanent Resident)
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Location: Berlin, Germany Remote: Yes; also open to Berlin-based roles Willing to relocate: No; happy to travel Technologies: Ruby/Rails, PostgreSQL, TypeScript/Vue, GraphQL, Elasticsearch, LLMs, Claude Code/Codex Résumé/CV: https://www.linkedin.com/in/brendanmulholland1/ — CV available by email Email: hire@bmulholland.ca I’m a hands-on engineer and former startup CTO. I work across understanding a customer’s problem, deciding what’s worth building, and bringing the product and team together to deliver it. I spent six years co-founding and building Recital [0], an AI product for corporate legal teams. I hired, managed and led engineering while remaining hands-on in the code, shaped product and company strategy with my co-founder, and worked directly with customers and prospects. My engineering work spanned architecture, document ingestion and search, production reliability, and customer onboarding. Our document AI evolved from NLP to LLMs and vision as the technology advanced. More recently, I’ve been designing and running a personal knowledge and agent system using Claude Code and Codex, with extensive work on context, instructions and review practices. I’m exploring paid senior engineering, product engineering and engineering leadership roles in AI products, infrastructure or developer tools. Particularly interesting problems include making complex business information useful, improving how teams build with coding agents, and customer-facing engineering where implementation work feeds back into a better core product. I’m also open to scoped consulting on AI product architecture or agent-assisted development. If that sounds relevant, email me about the problem, the team and the role or project you have in mind. [0] https://recitalapp.com/
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Location: Bengaluru, India (IST / UTC+5:30) Remote: Yes — remote only (worked remotely 2.5+ years) Willing to relocate: No Engagement: Contract / freelance, ~20 hrs/week. Not looking for full-time. Technologies: TypeScript/Node, Next.js, React, React Native/Expo, Hono, Cloudflare Workers/D1, AWS (Lambda/ECS/Fargate), PostgreSQL, Redis, Swift/SwiftUI, LLM systems (OpenAI/Gemini/Groq, RAG, multi-agent) Résumé: https://anuragsoni.com (portfolio + work history) GitHub: https://github.com/amaze-28 Email: anuunity28@gmail.com I ship complete products solo. https://anuragsoni.com/shotspa?ref=hn — Mac app that polishes screenshots automatically the moment you take one without changing your workflow, launched recently, built end to end in Swift/SwiftUI including the whole Apple distribution pipeline. https://commitposts.com — AI turns merged PRs into a changelog page, emails and an in-app widget. I built it so the customers actually get to know what's being shipped. https://clubmint.app — memberships, renewals and revenue tracking for gym and studio owners. Previously worked as Backend/full-stack engineer at an edtech serving 15M students. Built the OCR pipeline processing 10M answer sheets bi-monthly (the company's core revenue product), data pipelines at 100–200K records/day, and LLM/RAG systems in production. Recently resigned from my full-time SWE job to work on my own ideas and take freelance/contract work on the side.
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Location: Tirunelveli, India (IST) Remote: Yes Willing to relocate: No Technologies: PHP/Laravel, WordPress/WooCommerce, JavaScript/TypeScript, React, Next.js, Node.js, Python/Flask, MySQL, Postgres, Supabase, Stripe, Docker, Linux Resume: https://sazm.in/resume.pdf Email: sabajobs@gmail.com I've been building websites and web apps since 2006. Most of that time (14 years) I was the lead PHP dev for a small US agency, Weismann Web. Their CEO's letter says over 1,000 projects for 300+ clients, mostly e-commerce and WordPress. For a few years I also ran a team of 5+ devs as project manager. Since 2024 I freelance. Recent work: getting a Next.js + Supabase + Stripe creator platform ready for production, an AI reel generator in Flask (OpenAI, Whisper, FFmpeg), and Laravel work for a small UK SaaS. I like owning a thing end to end and I'm happy working async over email or Slack. Open to full-time or contract.
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Location: Seattle, WA, USA Remote: Yes. Open to remote, hybrid, or on-site within US. Willing to relocate: Yes. Open to discussing relocation. Technologies: Python, FastAPI, Django, React, TypeScript, JavaScript, PostgreSQL, MySQL, MongoDB, Redis, LangChain, RAG, OpenAI API, Vector DBs (AstraDB), Docker, AWS (ECS, Lambda, App Runner, CloudWatch), GCP, GitHub Actions, Pytest, Scrapy, Playwright, Selenium, Raspberry Pi Résumé/CV: https://drive.google.com/file/d/1MkHAqxlLuTunvz0ZliNdosjR37o-4KLM/view Email: vikram@vikramcodes.com LinkedIn: https://www.linkedin.com/in/sai-vikram-patnaik/ About me: Full-stack Python engineer with an MS in Computer and Information Science from the University of Michigan. I build backend services, data pipelines, and LLM apps. At Divinity Science, I built a journaling web app. I also automated a 6-hour weekly research task into a 20-minute Scrapy run across 12 sources. Before this, I built a RAG app on AWS for 8,000+ students using LangChain, AstraDB, FastAPI, and React. I also built BirdEye, a Raspberry Pi wildlife monitor. BirdEye became my peer-reviewed master’s thesis. I want backend, full-stack, or applied AI roles. My research : https://scholar.google.com/citations?user=mBY3OAoAAAAJ&hl
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Location: Eagle Mountain, UT (near Lehi) Remote: Yes, or in person around Lehi Willing to relocate: Yes, to Northern Virginia Technologies: TypeScript, React, Next.js, React Native / Expo (web, TV, mobile), Node, Express, PostgreSQL, Supabase, MongoDB, AWS, Cloudflare R2, Claude Code, Codex, T3 Code Resume: https://jschoeny.com Email: jared@jschoeny.com --- Frontend-focused full-stack engineer, about 2.5 years in. I care a lot about UX and polish. - Hackdex: I solo-built this open-source romhack discovery and patching site. It gets 420K monthly visitors and has 1.18M+ downloads, with no paid marketing. Patching runs in the browser so it never stores any roms. - ArtVue: as founding engineer on this art streaming platform, I built the API, website, and Expo TV apps as the only developer for the first 5 months, then the mobile apps. I read the react-native-tvos source (before AI could do this well) to fix focus and remote navigation. Looking for a full-time product, frontend, or mobile/TV role at a small or growing company. Available end of November. US citizen, no sponsorship needed.
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Location: Pakistan Remote: Yes — Async preferred, but not required. Willing to relocate: No Technologies: C, C++, Rust, Typescript, Python, Go, Lua, OpenGL Resume: https://github.com/derpyzza Email: derpyzza@gmail.com Hi! i'm a systems dev interested in embedded dev, graphics programming, game engine dev, and backend dev, but willing to try out almost anything :)
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Location: Milan, Italy Remote: Yes Willing to relocate: No Technologies: Node.js, TypeScript, React, PostgreSQL, MongoDB, Redis, Google Cloud Platform, AI agentic development. Résumé/CV: https://www.linkedin.com/in/gdarrigo/ Email: darrigo.g@gmail.com I'm a senior software engineer with 14 years of experience; I have worked with small teams and enterprises, and I have successfully contributed to the success of many products. I would love to work with a small, compact team on an interesting product and/or challenging engineering problems. Please get in touch!
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Location: Leicestershire, UK Remote: Yes (UK/EU time zones) Willing to relocate: No Technologies: PHP, Node.JS, JavaScript, TypeScript, Vue, Svelte, React, AWS, Serverless, PostgreSQL, MySQL, MongoDB, Redis, Docker, AI/LLMs, APIs, DevOps - ANYTHING REALLY! Résumé/CV: https://www.linkedin.com/in/markphunkyharwood/ GitHub: https://github.com/Phunky Email: mark [at] phunky.co.uk I'm a technical lead with extensive experience designing, building and delivering software products end-to-end. I've worked across startups, agencies and established businesses, taking projects from initial ideas through architecture, development, infrastructure and production. I'm equally comfortable leading technical decisions, working independently or getting hands-on with an existing codebase. My background is primarily web applications, SaaS platforms, APIs and cloud infrastructure. More recently, I've been exploring AI-assisted development, LLM integrations and agentic workflows. I'm technology-agnostic and enjoy solving difficult problems more than advocating for a particular stack. I'm particularly useful when a business needs someone who can take ownership, work across the entire stack and get things shipped without unnecessary complexity. *Looking for:* Remote contract, consulting or fractional tech lead/CTO opportunities, ideally working through my UK limited company. Also open to the right permanent senior engineering or technical leadership position. If you're building something interesting or need an experienced engineer to help move a project forward, I'd be happy to chat.
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Location: New York City Remote: yes, on-site or hybrid Willing to relocate: Yes Technologies: Python, TypeScript, LangGraph, RAG, evals, MCP, FastAPI, React, PostgreSQL, AWS Résumé/CV: https://venkatjs.netlify.app/ Email: svenkatesh.js@gmail.com LinkedIn: https://www.linkedin.com/in/svenkatesh-js/ GitHub: https://github.com/Venkat-Git98/ I build AI agents and the infrastructure behind them. Nearly 5 years of experience, currently the first AI engineer at an NYC startup, looking for Applied AI or Forward Deployed roles. I know GTM and financial services well. What I've built: - A lead generation product that combines 10+ signals across about 10,000 companies. It became our most adopted product. - The agent our customers use on the web and in Slack, with each customer's data kept separate. - The gateway behind 42.7M AI calls in 30 days across 17 services. - A self-hosted document pipeline that saves about $8K a month. - I also work directly with enterprise customers on onboarding and adoption. Side project: Between-Visit, a care-management demo on synthetic patients. Agents walk a knowledge graph of clinical guidelines, and every recommendation cites its source: https://between-visit-agent.netlify.app/
Why are Soviet math textbooks so hardcore in comparison to US textbooks? (2017) (quora.com)
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The whole "new math" thing was an attempt to catch up with Soviet math pedagogy, which involved much more foundations, construction, and proof, right? The way math is taught in the US is essentially free-floating, foundation less, and understanding-free: https://profkeithdevlin.org/wp-content/uploads/2023/09/lockhartslament.pdf
My linear algebra teacher was this older mathematician from soviet, who had emigrated to the west in the early 90s. In some casual talks we had, the topic around school systems was brought up - and at least according to him, the old soviet system had a demanding common curriculum, but also one where exceptional students were easily identified and supported.
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idk if he mentioned, but if you shown promise, you would've been moved to a second tier school, which were prep for top 5-7 universities, school exit exam there being harder than entry, and people in uni knowing those in those schools.. well. to end up in tops one only had to study hard. on hardcore.. well, idk, we went through intergrals and simple diff equations, and special relativity theory in 10-11th grades. (14-15 yro). It was not that hard.
At least for up to high school level, it's because they didn't care if a good part of the class fell behind. If little Jimmy (well, little Ivan, I guess) can't understand how algebra works and is getting only 1s and 2s, it's too bad, he'll have to repeat the whole grade again I guess. The whole "maybe math is too hard and we should just make it optional or dumb it down" that I have seen in US was just not something acceptable or plausible as a policy in that system. At the same time before we go idealizing that system, what Western folks often see are the best of the best examples. Individuals who went to great schools, emigrated and excelled in the West. They may have gone to better schools, with better teachers, or had parents who cared more etc. They don't see a representative sample. Many schools, especially in smaller cities and villages, were not as great, teachers not as caring, cheating was rampant, bribing teachers even more rampant etc.
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There’s also the fact that a lot of people in the system simply don’t care. The state can demand whatever it wants and produce whichever program it wants, but despite what they want you to think, they still do not control everything even in the USSR or modern day Russia. I had the displeasure of being part of that system, so I have a lot of experience here. Most of the time, little Ivan will either simply be rolled into the next class in spite of any bad grades “to not ruin the stats”, or his parents will make a nice “voluntary” contribution to the school’s nonexistent budget and his bad grades will suddenly turn into good ones. From the inside, the difficulty looks a lot more like overcompensating for failures rather than setting a standard, because standards are often completely ignored for various reasons. People often cite Russia’s incredibly high literacy rate. Having lived there, think again who’s measuring those stats and to what standard.
The problem is making someone repeat a grade destroys their social life leading to even worse grades later on when they give up on school. You get kids failing multiple times until they complete the mandatory education and then get kicked out without graduating, can't find a job and become criminals. It also takes away from the economy because you start working a year later. I think there are two solutions. You can make students repeat only the failed class and take it with their normal classes next year like in college. Or a requirement based system where you can only graduate after passing every class on the plan but you can attempt them as many times as you want (even after you're out of school and working full time).
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There reason that diplomas (or grades) are economically valuable in the first place is that they perform a signaling function. They signal, however imperfectly, some measure of competency, discipline, and intelligence. Some diplomas also signal membership in a certain social class. Employers utilize those signals to make hiring decisions, which makes them valuable. When those signals become sufficiently polluted, employers will invariably turn to some other signal . Lowering the standards is a move politicians often make because it "solves" the problem you outline in the short term, even though it's ultimately self-defeating because it directly undermines the virtue signaling function of academic credentials. It's a "solution" which requires no funding, no changes to teaching practices, and no changes to the ways schools are organized. So it's attractive and politically feasible even though it's harmful and profoundly stupid. The solutions you've proposed are the right kind of solution because they preserve the signaling function of credentials. But so far they're approaches that public schools and the governments that run them seem politically incapable of taking. There's also something else to confront here in that even when the competency signaling functions are intact, academic and professional credentials are also to some extent scarcity goods, valuable precisely because not everyone has them. So if you solve all of these problems and you still allow grades to at least attempt to fulfill their purpose, a functional and coherent grades system will, to some extent, always perform differentiation of the labor market or be obviated by its failure to differentiate. The inequality that you see manifest as students who fail to graduate falling behind in life is actually downstream of the schools, and it has to do with how many seats are available for what kinds of jobs in the economy. If you address the former without addressing the latter, the real social justice impact is going to be limited. And you ultimately can't educate your way out of having a working class; at some point you have to look elsewhere for assuring the dignity, security, and comfort of people who academically underperform relative to others.
> by the weakest who merely got good grades Like who? Trump? > The winners in our system are just the ones who get everyone else to kowtow In soviet system, connections were literally everything. Not merit, not achievement, but who you know, who is your friends, who trades favors with you.
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> Like who? Trump? Can’t be. Didn’t he graduate near the bottom of the class? And I think W also had mediocre grades. Eisenhower was in the lower half of his West Point class as well. There are probably numerous other examples of successful American politicians who were poor students. Just recently Gavin Newsome got into a bit of trouble touting his low SATs in front of a mostly black audience. There’s a longstanding anti-intellectual streak in the U.S. that politicians have been pandering to for ages.
they were not gangsters during the soviet times, so its hardly an argument about them as persons. But rather a sign of decaying times (the fall of the USSR and the economic hardship). Remember when the US had a hurricane somewhere in the South (Kathrina?), people just went looting all retail stores, same as what happened during BLM riots, the current riots in Paris, etc etc
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What I have to say about that since I live where it happened is that it only happened in certain localized places in the city
That's complete nonsense detached from reality. For the reference, I was a kid during the Soviet personal computing boom in the 80s, and it was the reason I got interested in electronics and computers at all. There was a huge push since the 60s, and computers were everywhere in the 80s, just not readily available to private owners due to the incapability of producing enough (you needed connections, not just money) and being expensive as hell.
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"computers were everywhere in the 80s, just not readily available to private owners" Agreed on that, and access to a computer system, e.g ES mainframe or SM family was not a problem for people who wanted it. I was in high school in mid-80s. I found a fortran book in the library, and it took me very little time to get access to the university-owned SM-1420, RSX-11, and a fortran compiler. That same lab ran free programming classes in the evening with faculty volunteers.
WTF Ubuntu? (chalmovsky.com)
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I'll add that they were a day or two late to patch the brotli issue, other than Ubuntu Pro LTS, which was still "under consideration" or whatever they called it, for another few days to a week. https://ubuntu.com/security/CVE-2026-111497 Now it says it's fixed, but on my old server I'm still not getting the updates for whatever reason (maybe I have it set up wrong? I dunno.). I hate to be the guy to complain about a free service (Ubuntu Pro is a source of revenue, but it's free for individuals) but if I knew this was actually was actually being offered I would (hopefully!) have switched off by now.
Probably right next to your reading glasses, my dude. Maybe grab those first, though.
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They are on my face. It's how I read a blog post and comments of people who are complaining that free software isn't being updated fast enough for them. WTF Ubuntu! I'm not paying you for updates... so where the fuck are my updates bro?!
Why are you lying so much? >no snap nonsense where you can't turn off upgrades You can disable AND uninstall snap entirely. You can also disable automatic update of the specific snaps you have installed. >stays close to upstream LTS kernels Same as Ubuntu, which uses 7.3 on its latest release as of today. >does not carry around some ridiculous kernel patch set Custom kernel patches for hardware compatibility is a very good thing, and why Ubuntu works on a lot of machines compared to other distros. >no irritating adware on login There is not a single ad on login, and even after. You are an ugly liar.
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All true as of when I quit Ubuntu a couple years ago. Your interpersonal skills need work.
It’s okay to have criticism, but at least be constructive about it. This “I demand to speak to the manager” energy should be kept out of open source. The post gives no details about what this vulnerability is, how critical it is, how it is impacting them personally, how vulnerable their servers are, how they are working around it. Just a title designed to generate the maximum outrage followed by a few meaningless lines.
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> at least be constructive about it I think the proposed solution here is pretty clear. Patch the bug.
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This is a major failure on Ubuntus part. The constructive feedback they deserve is literally the title of the article. The post gives enough detail, there is a vulnerability that allows root access on servers on the TCP stack, so literally accessible if you are running any service. There are exploits in the wild. Debian has the patched kernel, Ubuntu does not 2 weeks after the CVE is known. > how critical it is, 9.8 out of 10 btw. > how it is impacting them personally, They are clearly rather upset by the lack of an appropriate response. > how vulnerable their servers are, They are literally open to anyone with an AI subscription. > how they are working around it. They are migrating off Ubuntu.
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If Ubuntu offers LTS and is catering to business it is very much open to criticism. They can take it or leave it, but anyone is entitled to an opinion about it.
> The post gives no details about what this vulnerability is, how critical it is, how it is impacting them personally, how vulnerable their servers are, how they are working around it. Yes it does? And Ubuntu is selling security subscriptions and doing a poor job of it, These aren't open source volunteers, this is a paid product.
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You are talking about the company side of the issues. We are talking about the specific issue that is concerning our ubuntu servers. What is the security bug, and how can someone exploit it? Where is that written?
I read the whole post and still don’t have any idea what it is and how severe it is. Ubuntu has not marked it critical. Is there any reason to disagree with that assessment? In an entire post criticizing Ubuntu you’d think they would at least make that case. They have also not shared why they didn’t patch their kernel directly when updated versions have been available for a couple weeks now. Why wait for Ubuntu at all?
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> Ubuntu has not marked it critical. Yes they have, and the article links directly to where they say so: https://ubuntu.com/security/CVE-2026-98432 I think the author probably assumes that after almost 3 weeks of the entire world going ape-shit over this, most people reading their post probably know about it already, or know how to find out more, so they didn't feel the need to elaborate. > Why wait for Ubuntu at all? There are many reasons... businesses often cannot go this route. But I don't see why it matters unless you're just trying to attack and discredit this person because you disagree with how they write their articles. Why are you trying to farm out so much critical thinking to other people for you? It is easy to do a quick web search and find out everything one needs to know.
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Page shows > Ubuntu priority > High
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> I read the whole post and still don’t have any idea what it is and how severe it is. From the article the bits you need to know: 1. CVE-2026-98432 is a critical (CVSS 9.8) bug. 2. Anthropic says it built a working exploit that gets root on a server.
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> 2. Anthropic says it built a working exploit that gets root on a server. Is there any independent verification of this?
"Pathetic", "such a Karen" to care about a service he ostensibly paid for providing the thing he paid for. Brilliant.
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Where did he state in the post he is paying for Ubuntu? He doesn't. So, maybe he is a Karen and you are being a little protective of someone who is whining like a child.
Worse yet, the Ubuntu security incident page[0] lists "Ubuntu Priority: High" (as opposed to Critical, which would trigger an out-of-schedule patch). There's a "Why this priority?" link that simply says: > Why is this CVE high priority? > See ubuntu cvss score That's it, we don't even get a period on this TBD of a sentence. It's followed by a generic link that explains what "Ubuntu Priority" is, but that page contradicts their choice. Note that it doesn't offer any mitigations either, and even the (horrendously unclear) description is copied from the NIST page, so there's no actual message from Ubuntu. I already had a bad feeling the first time I saw "Get more security updates through Ubuntu Pro" on `apt upgrade`, this is now the kick I needed to move to a different distro. [0] https://ubuntu.com/security/CVE-2026-98432#priority-reason
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I don't think this is fair. They don't do a good job of pointing you at their rationale which is in their security score here[0]. I ultimately had to have claude translate the kernelese in to something my small brain could understand but this is a bug that could crash your system but is unlikely to expose your confidential system data to attackers or degrade data on the system. Especially given that the exploit can only be done if packets with IP options. IP options are commonly dropped or removed from packets on the open web. You not only need a vulnerable system but a vulnerable request path through the internet which you would only know by trying this attack which is very timing dependent with the SYN,Retransmitted SYN and Reset all happening very close together. A motivated attacker could probably do this on your network but over the internet ... It sounds unlikely. [0] https://ubuntu.com/security/CVE-2026-98432#impact-score
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As far as I know the only working exploit is working on machine with MultiTCP enabled. Redhat also downgraded the issue to "high" and also did not release a patch yet. I would have preferred a patch but I accept that they know better than me what they are doing.
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Why would they take so long anyway and be behind volunteer run projects like debian? Is it something about corporate shenanigans and testing? because afaik in fedora for example firefox is always behind in security updates compared to debian.
The more I look at this the angrier I get. This is a CVE that Anthropic claims can get a Remote Code Execution on vulnerable systems, which includes default Ubuntu installs running any sort of Go server like Caddy. Bad enough that I shut down my personal website and self-hosted tools (sorry for any typos, my grammar checker is also down). And this is how Ubuntu describes the vulnerability to sysadmins: In the Linux kernel, the following vulnerability has been resolved: ipv4: free inet_opt and ireq_opt after an RCU grace period tcp_v4_syn_recv_sock() transfers ownership of ireq->ireq_opt to the child socket (newinet->inet_opt) without copying it. Another cpu can concurrently process a retransmitted SYN for the same request socket, and send a SYNACK from tcp_check_req(). tcp_v4_send_synack() and inet_csk_route_req() read ireq->ireq_opt under rcu_read_lock() only, and ip_build_and_send_pkt() and ip_options_build() then read opt->optlen twice. Note that the SYNACK timer itself is not an issue: it holds a reference on its request socket, and inet_csk_reqsk_queue_drop() calls timer_delete_sync() before the child can be freed. Since commit 079096f103fa (“tcp/dccp: install syn_recv requests into ehash table”), request sockets are processed without holding the listener lock, so nothing prevents the child socket from being freed while the SYNACK is still being built. TCP child sockets do not have SOCK_RCU_FREE, and inet_sock_destruct() frees inet_opt with a plain kfree(), leading to a use-after-free in ip_options_build(). A similar issue exists with request socket migration (net.ipv4.tcp_migrate_req=1, or a BPF_SK_REUSEPORT_SELECT_OR_MIGRATE program). reqsk_timer_handler() clones the request socket with inet_reqsk_clone(), so that the old request socket and its clone share the same ireq_opt, then reqsk_migrate_reset() clears the pointer in the old one. Another cpu holding a reference on the old request socket can still be using these options (sending a SYNACK, or creating a child in tcp_v4_syn_recv_sock()) when the clone is freed, and tcp_v4_reqsk_destructor() also uses a plain kfree(). Readers already use RCU, and other paths replacing inet_opt (do_ip_setsockopt(), cipso_v4_sock_setattr()...) already use kfree_rcu(). Use kfree_rcu() in inet_sock_destruct() and tcp_v4_reqsk_destructor() as well. IPv6 is not affected by the first issue, because tcp_v6_syn_recv_sock() duplicates the options. tcp_v6_reqsk_destructor() has the same migration issue with ipv6_opt, which is only set by CALIPSO. This will be addressed in a separate patch. How is this in any way, shape, or form acceptable two weeks after the CVE was published?
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> running any sort of Go server like Caddy It's so much worse than this, and there is a staggering amount of misinformation running rampant about this bug. MPTCP is not a requirement, it can be exploited merely by sending specially crafted TCP packets with (any) IP options set. No special MPTCP support, web servers or any specific software listeners are even necessary at all to trigger it, just send the packets and boom. I think the reason people assume MPTCP is a requirement is because that's what the PoC used... but MPTCP itself also doesn't even rely solely on IP options. Ubuntu also does not even list a single mitigation strategy... at least RHEL did. And like I said, any normal TCP packet that contains IP (not TCP) options can trigger the bug. I cannot emphasize enough how important and absolutely ridiculous this is. Like the post says, this is big enough to get a massive amount of people to completely stop trusting Ubuntu entirely and jump ship.
The general advice I've been seeing the past ~8 years is "There is no reason to pick Ubuntu over Debian". I don't know who the opposite advice comes from and why anyone would pick ubuntu for a server.
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I deployed Ubuntu on a LOT of servers 10 years ago because at the time, they had a track record of doing good things in, with, and for, the Linux and open source community. I had already been using it on the desktop for a long time by that point and knew it well. Ubuntu was far and away the most popular; it was a very safe and sane choice. That changed when they started heavily promoting Snaps as the next big thing and started putting features and updates behind their enterprise offerings. Basically, they stopped being "Debian, but better." And Debian also made lots of incremental improvements in user-friendliness in that time. Basically, Debian is now pretty much what Ubuntu always promised to be.
15-20 years ago the joke was that Ubuntu is a Zulu word that, roughly translated, means "I don't know how to configure Debian". Ubuntu was one of the first distros that allowed one to easily download proprietary WLAN drivers without dealing with the terminal, ndiswrapper, or compiling half-broken OSS implementations; for this reason it caught fire with those who wanted to try Linux but were otherwise unwilling to engage in such shenanigans. I tried it on a laptop around this time and was quite impressed. This reputation for "it just works" has carried them ever since even though other distros now do largely the same thing ( cheap, obscure, or recently-released hardware excepted). I took the lazy Mint route with my most recent machine since I wanted to use it for light gaming with minimal fuss. I'm going to redo it with Nix sometime soon because the value prop simply isn't there and I'd like to try a declaratively-configured distro.
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More like 20. If I remember it right, by 2007 the Debian community was angry discussing the installation team's decision to include non-free packages in the installation media, what ended the problem of needing a wired connection during the install.
People make bad choices all the time for many different reasons. Usually, “it seemed like a good idea at the time” is at the top of that list.
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But by definition it wasn't a bad choice (or a mistake) if it seemed like the right choice given the information available at the time. Unless you have some sort of crystal ball the rest of us don't.
Plain Debian was always best option; even RHEL dropped the ball on this CVE and that's distro people pay for support
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I planned to install Debian in 2009 and in 2014 but the installer was too hard to use, the desktop in 2009 was ugly (maybe in 2014 too), I could not get a running system that I could use to work. Fast forward to Debian 10, same laptop from 2014, and I got a desktop identical to Ubuntu GNOME.
Not always. Notably, if you have compliance requirements like needing FIPS encryption (say because you have government customers), or that requires you to use a commercial vendor, debian won't work. And if you need more up to date system packages, or a reliable release cadence, Ubuntu might be better. On desktop, if you need proprietary drivers, Ubuntu is easier to set up. But yes, if debian works for you, I wouldn't use Ubuntu.
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I had to deal with FIPS once because the company I worked for shipped a custom Linux distribution with the product and we had to essentially shoe-horn in some Red Hat OpenSSL packages to get it to meet FIPS requirements. What's funny is that the customer enabled FIPS, administration became much harder, and the encryption strength was strictly worse. Anyway, needing FIPS is something of a niche requirement. Debian or Rocky are very sane choices as a default Linux distribution for general-purpose servers until you run up against special requirements.
Uh, yes it will. OpenSSL in Trixie is a version supported. https://packages.debian.org/trixie/openssl-provider-fips It's just the library, nothing special about the OS. https://csrc.nist.gov/projects/cryptographic-module-validation-program/certificate/4985 As far as I know, compliance comes with an external module: https://openssl-library.org/post/2025-03-11-fips-140-3/ This module seems to be in Debian: # apt-cache search fips | grep open openssl-provider-fips - Secure Sockets Layer toolkit - cryptographic utility # dpkg -L openssl-provider-fips /. /usr /usr/lib /usr/lib/x86_64-linux-gnu /usr/lib/x86_64-linux-gnu/ossl-modules /usr/lib/x86_64-linux-gnu/ossl-modules/fips.so /usr/share /usr/share/doc /usr/share/doc/openssl-provider-fips /usr/share/doc/openssl-provider-fips/changelog.Debian.gz /usr/share/doc/openssl-provider-fips/changelog.gz /usr/share/doc/openssl-provider-fips/copyright There seems to be the validation process, which supposedly must run on each machine it is used on. openssl fipsinstall -out /tmp/configfile.cnf -module /usr/lib/x86_64-linux-gnu/ossl-modules/fips.so 2>&1 | tee /tmp/result.txt -- The above are from my notes, and a test run. But I don't see how Redhat is "special" here. If the module loads and cites compliance, you comply.
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> OpenSSL in Trixie is a version supported. It isn't a validated build. It works the same, but it isn't sufficient if you actually need a validated FIPS module. > It's just the library, nothing special about the OS. If you need validation, then the kernel also need to be validated. Now, it isn't impossible to get a FIPS validated system working with Debian, but you will probably need to contract with another commercial provider like WolfSSL to get validated components. Or compile things yourself. But that is more complicated and involved than just paying for an OS that is validated off the shelf from Ubuntu, Red Hat, or Suse.
I get the frustration, but isn't there an iptables rule that is a viable mitigation? Why not deploy that first?
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Why do you ask such simple and obvious questions!? :-P nft add table ip cve_2026_98432 nft add chain ip cve_2026_98432 pre '{ type filter hook prerouting priority -300; }' nft add rule ip cve_2026_98432 pre meta l4proto tcp ip hdrlength gt 5 counter drop
Here is Ubuntu’s webpage on this vulnerability: https://ubuntu.com/security/CVE-2026-98432 It’s still, over a week after disclosure and patches, unpatched in Ubuntu. As for me, a part of me wants to move over to Rocky Linux 10.
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I don't quite understand this page. I thought the kernel binary was in the `linux-image- ` packages in Ubuntu. For example, I have linux-image-generic installed, description "Generic Linux kernel image This package will always depend on the latest generic kernel image available." and then "Depends: linux-image-6.8.0-147-generic, linux-modules-extra-6.8.0-147-generic, linux-firmware, intel-microcode, amd64-microcode" Why isn't there linux-image or linux-modules-* listed as an affected package? First I thought it was the source package / binary package distinction, but e.g. linux-image-7.0.0-38-generic says "Source: linux-signed-hwe-7.0", and linux-signed-hwe-7.0 isn't listed as an affected package either. So what's going on here?
I've switched my default to AlmaLinux. Was a fan of Ubuntu since 8.04 (Hardy Heron) but stopped since Canonical pushed hard on Ubuntu Pro.
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AlmaLinux is "boring" in the best possible way, and it works really well in WSL too. Their extended support for x86-64 v2 has also been useful on one my old computers.
[for clarity, I am not talking about servers] When a non-technical person asks me “which Linux?” I recommend Ubuntu because it is about as gentle an experience as Linux is going to be. The install is friendly and the culture is less RTFM than anything else. Those are the same reasons I run Ubuntu on my laptops that aren’t running Windows…I prefer low friction to arguable technical superiority. I’ve looked at other distros in the past and decided they weren’t worth the bother…To Me. But that’s me, not you or anyone else. And my use case not yours or someone else’s.
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> and the culture is less RTFM than anything else. To this point, adding "on ubuntu" to a search gives me better tutorials.
I'm referring to the ubuntu-drivers thing. You can do the equivalent in Debian if you add non-free repos and find the right packages, it's just more hassle. But if all you need is GPU drivers, no need for that tool. At least Debian is on Wayland. Mint is on X11, which was causing black screen out of the box on my fairly typical PC.
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Oh also, last time I used this was years ago, and I'm willing to try Debian next time I use desktop Linux now that uh things have changed
By using a LLM, maybe ?
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While I have your attention, can you constrast this human comment with your [presumably] human-derived username? –ProbablyNotMachines
Times are changing! Remember when it was easy to set up WiFi, but difficult to call your doctor and get an appointment? Now my friends don't have trouble calling doctors, but can't set up port forwarding (not like any games require it anymore).
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>can't set up port forwarding After October 2026, nobody should be port-forwarding IMHO. I am next to learn about the "tailscale options" of this new world. Wish us all luck.
Stable Debian is using Linux 6.12, if your laptop has modern hardware what do you do? Can't use wifi? And don't get me started with Debian testing. I want a LTS distro not a testing one.
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> what do you do? You get 7.12 from backports?
That, or just pick the kernel package from unstable or testing. Apt is smart enough that mixing packages from different versions of Debian works just fine. (I mean nothing is 100% but I've been mixing packages for like 2 decades now and literally can't remember any specific trouble resulting from it.)
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> That, or just pick the kernel package from unstable or testing. Apt is smart enough that mixing packages from different versions of Debian works just fine. While I won't deny that this may often work, I disagree that it's a good idea, and that `apt` being smart is sufficient to guarantee that this works (or keeps working in the future). Pinning specific packages from `testing` or `unstable` is explicitly discouraged, for very good reasons covered by this classic link: https://wiki.debian.org/DontBreakDebian#Don.27t_make_a_FrankenDebian . Arguably, the backports kernel is the right choice to get a newer kernel on Debian Stable. Indeed, in the past, the backports kernel could take awhile to update, but no more - case in point, `trixie-backports` currently contains `7.2`, same as `unstable`.
GPT-Rosalind-6 System Card Addendum (deploymentsafety.openai.com)
Corporations are not, nor ever have been a democracy. What you are asking for is regulations, but as we have seen regulations are pointed at giving the government and corporations more control. Maybe elect better leaders and not corrupt old businessmen.
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I want one regulation on AI: everything must be public. Training data, code, procedures, everything. And for that to work, a complete scrapping and overhaul of our copyright system. One can dream.
Last I checked machine learning wasnt the bottleneck for drug discovery and where it fits in the research process was largely solved 5+ years ago.. Weren't there already a ton of ML based drug discovery startups that went out of business, or got aquired, not because they werent useful but because they produced more candidates than the industry could use. I dont think I want researchers offloading their thinking to some specialty model after seeing what its done to me and my colleagues in software, it certainly isn't making anyone more competent. It really only enables people to be able to do less novel and lower quality work faster. OpenAI and Anthropic creating these platforms seems mostly just to create narratives around AI that its going to lead to cures for disease, which it wont, but plenty of normies assume it will cure cancer now. Also a bunch tech oligarchs who are equally convinced or 'one-shot' they're going to live forever because of language models lol. Promises of the Fountain of Youth continue to be a time tested tools for snake oil salesmen.
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This is what I've built my current startup on. We find that ideas, structures and molecules are cheap and actually making them in cells is the issue. Obviously this doesn't apply to small molecules but as groups like Anthropic move closer to Phase I I'm guessing we'll see a lot of frustration with existing CDMO providers like Wuxi or Lonza just like we see with Apple and their woes with Micron etc.
And who's going to be providing these models? How is open source going to work when governments start declaring models as munitions? There are a lot of unanswered questions the open communities are going to have to deal with.
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They could be crowdfunded. You could even have a system where only contributors to the crowdfund have a license to use it. >How is open source going to work when governments start declaring models as munitions? I mean open source cryptography did win that battle in the end. Even if it's illegal you could host the model weights on i2psnark and crowdfund with monero.
Jobless tech workers are being left out of San Francisco's AI boom (bloomberg.com)
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I applied to Anthropic a few years ago but didn’t pass the bar on their coding test. I read recently that if I had been hired in that period, my equity would be worth over 40 million based on their current valuation (and i remained employed the entire time there) It’s hard to mentally reconcile that if I had performed better on a few coding tests a few years ago i would be 100x wealthier than I am today. Whether or not you met the right bar, got into the right company at the right time is the difference between a tedious endless struggle and securing your family’s wealth for the rest of the century.
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Who knows, maybe you never would've been a "culture fit" even if you passed the coding test. By the same logic, if only I picked 2 - 4 - 18 - 50 - 56 - 20 on Powerball last week I would be $760 million richer. It's only a few numbers to get right, wild to think I was that close to being rich!
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not even comparable. Lotto is entirely random, signals that anthropic would be hugely successful were not random, but access to the upsides were gated on who had sufficiently amassed capital to buy in
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Sounds like if I'm smart enough and lucky enough I would have several Billions in my bank account.
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It's gambling, and semi random. Don't feel bad. Same as stock picks, etc.
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It’s not really random when it was clear on account of the caliber of people working there that it was going to be a generational company whether the AI boom took longer or not. The writing was on the wall by the time Opus 3 came out, after it was just a matter of who was worthy for a ticket on the arc.
> Or are you open to regulate the tech market just like other sectors, and mandating a human gatekeepers regardless of how smart the AI is? The doctors and nurses might feel smug and cozy having pulled off a hiest and putting regulation in their favor for now but you know who are even better at pulling off hiests and putting regulation in their favor? MBAs and corporate attorneys. The fat salaries of doctors and nurses are going to be squeezed out into the hospital's bottomline and the doctors and nurses won't be able to do anything about it because the very drama they pulled off to get to where they are will be used against them . It's already happenning - wages for doctors and nurses aren't growing and they are being eaten away by inflation. It's very likely they will make the same amount of dollars in 2036 that they make today. Even specialists like surgeons are not going to be spared: https://news.ycombinator.com/item?id=50336138 The tech industry has chosen not to play dirty and we don't have to . AI is making it increasingly easy to start your own business. I certainly have been encouraging people to find their own customers before their (ex)employer forces them to. Starting your own business isn't for everyone and it's scary but it's no more difficult or scary than 12 rounds of tech interviews. Let's continue to make the pie bigger instead of putting restrictions on who can even get near the pie.
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Nurses have strong unions that this year made big gains for their members. Why would this change ?
This assumes people don't increasingly let AI make decisions for them.
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Exactly. If I need a new supplier for my business, why would I ask around, listen to pitches, negotiate, sign contracts, monitor quality, etc.? I should be able to ask one of my AI agents to do all of that. And when the new supplier does not work out, I re-prompt my agent.
I don't know how old you are, but if you were around in the early 2000's there was a BIG offshore fear. More and more they were hiring in India and the Philippines and other places. Initially it was the NOC / L1, maybe L2, and in certain areas. Not only did it not spread to engineering, but even the L1 and L2 were terrible. I worked in some large environments where working with those offshore folks was universally viewed as a nightmare. Now, what has changed? Don't tell me Claude. As far as I can tell, these folks make a lot less, and the good ones can easily immigrate to Europe or somewhere else - maybe that has changed. Culturally, you have to often tell them very explicitly what to do and it is not normal to think outside of the box. I doubt that has changed. So why would we be more afraid than we were in the early 2000's?
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>Not only did it not spread to engineering, but even the L1 and L2 were terrible. I worked in some large environments where working with those offshore folks was universally viewed as a nightmare. >Now, what has changed? We did. The sorts of strongly hierarchical/rank based and "follow the process to our obvious demise" type workplace culture that is normal in big companies in the US today would be the punchline of a derisive joke about government/union/academic employment in 2006. Back then there was a HUGE culture gulf between an office in the US and an office in Bangalore or Manila because they ran that way but the office in SF or Redmond or whatever didn't. But in the past 20yr there has been a push to treat people (more than we already did) as replaceable cogs, do everything by committee, divy up responsibility, escalate everything, follow the process when the process and the big picture conflict because it's "not your station" to think about those things, etc, etc. You can blame it on academia and MBA schools, you can blame it on the culture that we imported with the H1Bs, you can blame it on regulatory posture fanning the flames of all this, IDK, I tend to blame them all. But it absolutely happened. And now that we've incurred the cost of running that way just by virtue of our workplace culture changing there's a lot less operational cost to onboarding an offshore team.
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I remember that era. I call AI today Offshoring 2.0 and put up some citations [0]. I remember how it cratered the CS/hiring pipeline for a decade, leading to the competitive frenzy during ZIRP. [0]: https://news.ycombinator.com/item?id=47125477
Both OpenAI and Anthropic have significant customer engineering: architecture, integrations, evaluations, and production deployments in India. It's kept under wraps because the current administration doesn't want their "We need to win AI" to be overshadowed by "but our money is going to India again!" concerns with voters. The U.S. is having its midterms - it closes tomorrow - and the next two years are pivotal to who wins the senate for the next 4 years. Having it leaked that billions of dollars of domestic AI spend is going to India is going to sink the GOP. OpenAI has large offices in Delhi, Mumbai, and Bengaluru. Anthropic is rapidly expanding their Bengaluru office to Mumbai. India is an extremely large market - there are 4x more people in India than in the U.S, so it's a huge TAM but most of them don't read or speak English so there's a tremendous localization challenge. India is undergoing a fundamental shift in their economy. They used to be a culture that used to save money before they spend it. Recently I saw a large group of Indian visitors by the Golden Bridge taking pictures and asked them how they could have afforded to save for the trip given the current explosion in prices. They hadn't saved money - they had taken out loans for the trip. Everyone of them. Apparently their house help earns as much as a teacher in Nonalva, Mumbai (I might have got the city wrong but it sounded like that) They also focus their students on STEM and are having a tech. hiring crisis (so talent is really cheap). Every engineer speaks atleast 3 different languages, including English and even more local dialects. Adjusted for cost, the above average Indian engineer assisted by Claude is insanely more valuable than an average engineer from SF assisted by Claude. It's like DeepSeek V4.1 Flash 1017 vs your average US frontier model. As I said in another comment, $180k/yr doesn't go very far in San Francisco specially if you want to have a family but I won't be surprised if you could retire in India after working on $180k/yr for 2-3 years. Every market has an upper threshold of costs parties are willing to bear and San Francisco passed it where there's now active demand collapse. Companies are voting with their wallets and people in San Francisco are paying the price.
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I am very aware, being indian myself, and have broad knowledge of the tech ecosystem here. Openai/anthropic in india is mostly sales. There is not yet research/engineering roles beyond that. > but I won't be surprised if you could retire in India after working on $180k/yr for 2-3 years. Irrelevant, but just for information, you could provided you're willing to live in a relatively rural area.
This isn't exactly true because some others participate indirectly. The most obvious winners are the people who bought housing or other real estate. There are also non-programmers who invested, the most famous may be the Persian carpet dealers in Palo Alto who've been investing in startups on the side. Yes, there are many who don't own their house, but some of those can also benefit. California has some of the most generous social benefits in the nation, all because they can tax the tech companies.
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Never heard of these carpet dealers but you have any more info ?
If you think Seattle is Amazonville and worse in all ways than SF, it sounds like you visited South Lake Union and no other part of the city. Amazon's footprint is pretty limited outside of SLU, which is one of the least interesting neighborhoods in the city. Downtown just south of it also sucks. Ballard, Capitol Hill, Alki, University, Sunset Hill... The list goes on. Every single one of those neighborhoods has a completely different vibe (many of them used to be different cities). Incredible restaurants if you put in the slightest amount of effort to finding them. Tons of fun and interesting activities. The city is on a hill above the ocean (JUST like SF), the views are hard to avoid. Year round running weather. It may be that you just like SF more, and that's fine.
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I ran every day I was there in different directions including a 16 mile loop to the tip of discovery park, it’s not a great running city, and its views aren’t particularly great. Sure it’s okay, not as nice for running as SF or Vancouver but yeah far better than Phoenix and SoCal cities. Maybe I went to the wrong areas, but it sounds like I was supposed to get to the sprawling suburbs?
Where though?
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>"Where though?" NYC is an infinitely larger, more varied, interesting, and multi-cultural city than SF. Better transit and more affordable too, while reaching similar salaries. Anyone who's not drinking the tech-bro kool-aid but still wants to be part of the industry at the highest levels should be there.
Ask HN: What hardware are you using to run local LLMs?
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I feel very poor with my M2 MBP with only 16G of RAM
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I bought a Framework Desktop mainboard only, 128gb AMD 395+ setup, and put it in an existing case with PSU i had on hand. I had a fan for it. It was $2699 +$15 expedited shipping. The case and PSU/etc was probably $200 more (It's an overkill 850w SFX PSU and cheap but great ITX case from Deepcool). I started with Ubuntu but pivoted to Fedora over the summer after a recommendation from a security engineer friend. And it is mostly easier. Generic setup doc here: (not fully updated with GUFO): https://github.com/Selicos/AI_Tools_Public/blob/main/docs/Fedora/Fedora%20LLM%20Server%20Setup%20GENERIC.md Key changes for other distros are how to load drivers/apps and get running. Ubuntu has a recent CVE issue but worked fine. CachyOS/etc set up for more Windows like UI and transplants was fine but not focused on the Stricx Halo setup. Although I do see close to RTX 5070 performance in most games I've tested. I was running LM Studio and some other runtimes for ease of setup and model switching. Once you settle on a runtime and model setup you like it is easy to set it up, let it run, and manage as needed. Last week I set up GUFO, as it targets the AMD Strix Halo hardware and is efficient for Qwen Flash Next. I could probably get the work done with Qwen 3.8 27B but I like how QFN thinks and lets me follow along. Starting at about 260k context, I see 88gb of RAM usage when loaded and about 108gb when in use, depending on context overhead. I do have to restart the model every so often as Copilot Chat in VS Code starts failing. I have also run Lemonade, llama.cpp directly, vllm, and more. Custom or bespoke runtimes for your hardware are key, like Srata or GUFO. I need to look at llama-swap. LM Studio is easy and with their Tailscale backed link feature you can stay connected from any device. IF it supports OpenAI/etc back end you're mostly there. Get the model running and connect from your preferred harness/etc. GUFO works well with Copilot Chat in VS Code. I need to connect it to Pi and openhands/etc later this week once I get this test project in a good spot. Qwen 3.8 27B, Gemma 4 26B A4B variants, whisper, and more run well. A Spark or bank of GPUs would do better, of course, but not for under $3k for 128gb of memory. I have tested adding an Nvidia 3060 12gb to the Strix Halo but the iGPU is turned off by Fedora and I didn't have more time to solve. My secondary Fedora AI system has the 3060 12gb and a 5900XT (16c/32t) plus 64gb of DDR4-3200. I need to get Strata up on it and see how well medium sized models work on the mixed memory. I bet MOE models will work well. I have the hardware so will use it but renting capacity is much cheaper if you just want to mess around and get used to the tools. Happy to answer questions about how I got here. I'm an infra guy, not a software dev, and what I'm doing with AI at home could definitely be 5x faster with a real dev and dev process.
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I got an old Dell T5820 64GB RAM and put in 2x V100 32GB GPUs. All in was around $1800 USD. Runs Qwen3.8-27B Q4 on one GPU at ~55 tok/s. I also put MiniMax H3 on the other GPU for generating images and video, and the kids have fun with that. I use this box for all my personal leisure coding projects, but stick to bigger models over API for real work work.
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Qwen Next 3.8 @ 3 bit IQ on x2 Quadro 6000 (sm_75) on a Dell T5820 (W-2140B Xeon, 128GiB DDR3). Strata makes the most of the hardware. heavily customised agentic framework: https://github.com/connollydavid/host gets good work out of the weights
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r9700s - running qwen 3.8 flash next with ~1m token kv cache
If you love a website, back it up (blog.mistys-internet.website)
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I scrape daily. YouTube, archive,org (sadly getting harder and harder since you have to "checkout" books), worldradiohistory.com… (Now if hard drives had not become so damn expensive—it's getting harder to be a digital hoarder like myself.)
I did this for a while. I went so far as to built a highly advanced web crawler webapp that was better than the Internet Archive in a lot of ways. But the modern web has made this unreasonable. Every webpage is 99% junk (CSS, JS, HTML structure, tracking pixels, UI images, navigation links, cryptominers (I joke)) and 1% content. You need a smart AI system to pick out the good parts, otherwise you'll quickly find yourself schlepping hundreds of gigs of junk to just preserve your favorite websites. The better idea is: if you love information, back it up. Collect the knowledge from the website, not the website. And then preserve it. Create a free ebook. Or sell it on Amazon kindle. That'll last a lot longer than the website will, and any HTML backup of the site you could possibly make.
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I'd suppose most of those junk websites have no value in them, really. The most valuable information in the web is in good ol' (x)html, maybe some css. But something like readability.js [1] can help in filtering the junk around the main info. [1]: https://github.com/mozilla/readability There's also a C rewrite: https://github.com/eafer/rdrview
I tend to save things I read as PDFs because it feels the most robust archival formal for the future.
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Plain text is "the most robust archival formal for the future."
This is why I started using Obsidian Web Clipper. There is SOME work to learn it and set it up, but the small amount of upfront work will pay for years to come. And the folder itself is backed by Dropbox, so I don't have to worry about losing it all forever.
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> the folder itself is backed by Dropbox, so I don't have to worry about losing it all forever. History and this very thread should show you how this is a naive statement.
Wholeheartedly agree. It's sad to slowly see the bitrot in my own bookmarks, trying to pull up important resources or media from only a few years ago only to hit a 404 or domain placeholder. And many times there is nothing on Archive.org or similar. That ArchiveWeb extension looks excellent for custom captures. Picking the pages and elements you want during capture is a great feature. For quicker one-offs, SingleFile gives you a single HTML with all the media of a page: https://www.getsinglefile.com If you're making archiving a more involved part of your workflow, I highly recommend ArchiveBox. It can save pretty much every type of file from everywhere, in almost every format you can imagine, while building a searchable index of the archives. Been using it successfully for many years: https://archivebox.io
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I haven't tried archivebox, but self-hosted https://karakeep.com/ has been working well for me. When the server-side parsing fails I'll fallback to using SingleFile in my browser which then forwards it to my Karakeep instance.
Last night an AI agent performed brain surgery on a mouse (twitter.com)
Even if he didn't do the surgery, he has a superior context window.
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Must have survived a lot of compactions
Who made the coding error?
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The mouse.
Lots of owners feed fully aware "live" prey. Many snakes will refuse prey that doesn't move.
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[delayed]
Welcome to the central tension in ethics! Where is the line and why?
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At some point you have to rip out the bandaid, if they did everything possible before operating on actual test subjects, then I don't personally have an issue.
First, you seem to be confusing me for the commenter who originally raised a concern. Second, you're not really addressing my comment, rather just responding with a more polished version of your previous comment deny any issue. My point is where are your own ethical boundaries here? For each aspect of the situation, what would have to be different to run aground of your own ethical concerns? In order to say that something is on a specific side of a line, you must know where the line actually is, right? Third, and this doesn't apply to you as an uninvolved commenter per se, but it definitely applies to the original "experiment" - the onus is on the person performing it to demonstrate how it is ethical. A xit that reads like a kid buying some fancy equipment and playing around to see what might happen, "18hrs in front of my laptop coding and coordinating this", and a "licensed vet" as an accountability crumple zone does not inspire confidence!
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I would say I did address your comment, I just don't seem to be spelling it out in a way that you would prefer. Which is to say I'm not sure how you can't extrapolate my ethical boundaries and considerations from my previous comment. > potential harm versus the realities of medical science and study > needless abuse and inhumane treatment. > This specific case does not seem like that
Supermarket freezers across Europe hit by second suspected cyber-attack (theguardian.com)
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So anyone that has lived in large Windows corporate IT land, a lot of decisions get made by people that aren't technical. Come to think of it, it's probably why a large majority of "hacks" happen to Windows machines; a highly technical team with a vulnerable OS will probably have the right security layers in place to mitigate this.
As I mentioned in the thread regarding the previous attacks, I worked in a closely related field back in 2008-2009. One thing I see repeatedly brought up here in this discussion is "Why can't we just set the refrigerator temperature with a knob and walk away?" The problem is that these refrigerator cases are not as simple as your refrigerator at home. As a simple example, many systems allow you have control over the deadband: the exact low temperature at which the compressor turns off and the high temperature at which the compressor turns back on. You also have control over defrost cycles, compressor pressure and many other things (I worked with this a long while ago, and I don't remember all the details). Take a look at some of these manuals, for example: https://www.hillphoenix.com/resource/installation-manuals-2/?type=Installation%20Manuals As far as I can tell, those manuals just cover the refrigerator cases, and not the outside compressors and heat exchangers, which are another layer to deal with. This is not something that a non-expert supermarket employee would be able to handle well. The purpose of all these settings is optimize around energy usage, maintenance costs, customer experience, etc. Even if you only save $500/store/year, you can see that it really adds up over a chain of 1000 stores. That's why this equipment is remotely accessible: it's not like your fridge at home and requires a lot more knowledge to get the most out of it. Of course, that does not excuse poor security implementations.
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> The problem is that these refrigerator cases are not as simple as your refrigerator at home. As a simple example, many systems allow you have control over the deadband: the exact low temperature at which the compressor turns off and the high temperature at which the compressor turns back on. You also have control over defrost cycles, compressor pressure and many other things (I worked with this a long while ago, and I don't remember all the details). … This is not something that a non-expert supermarket employee would be able to handle well. I still don't see why the expert has to be remote, or why an integrated computer can't do the optimization. Or why it needs to be fiddled with at any significant frequency.
If only 50$ of those savings were invested in Tailscale.
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Or netbird. I was exactly thinking the same btw clearly we're missing out something. or maybe cybersecurity is a cow ready to be milked?
I don't see why saving $500 per store a year is better than exposing your systems to cyber attacks.
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It was a better deal before AI, but now the economics of a lot of things are changing rapidly.
here's hoping no country is stupid enough to have an ICBM on the internet but you just know someone will eventually if not already because some vendor thought it would be easier for monitoring or firmware update
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An attacker doesn't need an internet connection if they are persistent enough...
Yeah And it would be (mostly) fine if they were on the net, with read only access
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The entire reason they are put on the Internet is to allow for remote control. What problem would it solve to allow remote monitoring of refrigerator data without control?
No, most of the activity or function of regulatory bodies is not litigation. Litigation would be the last resort.
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Litigation is the last resort in the US system, too. It is the threat of fines/damages that incentivizes a company to do right by its customers/other stakeholders.
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