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Gitea 28.0.0 Is Released (blog.gitea.com)
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For anyone curious why they should choose one over the other: https://forgejo.org/compare-to-gitea/
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Thanks! Currently going through this decision process myself.
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I suggest browsing through the release notes of the last 4-5 versions to see what you like more.
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they skipped 26 major versions, ai is truly amazing
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> Gitea drops the historical 1. prefix from its version numbers, so this release is 28.0.0 rather than 1.28.0.
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> This release contains security fixes. To give everyone time to upgrade, details will be added to this post in about a week. Is this something that has been happening for a while or a new trend due to LLM concerns? I understand the reasoning, it just made me do a double take because I haven't really seen that before.
Senate Democrats block bill to limit lawmakers' stock trades, citing voter ID (cbsnews.com)
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I'm not in the US , but we and everyone else has strong voter I'd. Even banana republics. I see no reason to be against it unless you're attempting fraud.
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It was a Trojan horse for voter disenfranchisement based on a bill provision. I’d agree with you if it was a clean bill focused on lawmaker stock trading restrictions alone.
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Actual title: Senate Democrats block bill to limit lawmakers' stock trades, citing voter ID provision Which makes a lot more sense than the submission title (in fairness, the original is too long) but it could have been made to fit without losing that key word at the end.
Reddit will block Old.Reddit.com from people who haven't used it in 6 months (arstechnica.com)
Hasn't the redesign been around for like 8 years at this point? Kind of crazy they kept it around for so long.
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It has been a godsend. The new design is bad in all the ways that most modern designs are bad: lots of needless padding, ads everywhere, poor information density. After they effectively killed third party apps, old.reddit.com has been the last bastion of a design intended for power users.
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Because it's still a big hunk of traffic, and moderators report relying on it (it loads significantly faster). They have bolded text relating to moderators in the annoucement: https://www.reddit.com/r/modnews/comments/1wubgvt/continuing_our_infrastructure_updates_whats/
As a quick reminder: First there was Reddit, which had an API, a mobile version (i.reddit.com) and a desktop one. Then there was the redesign, after which there was new reddit, old reddit (old.reddit.com), and mobile reddit. Then they removed mobile reddit. Then they restricted the API. Then they made old reddit available for logged-in users only, which they are now restricting even more. It's obvious that they're slowly boiling the frog until there's only one bloated interface left.
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Embrace, extend, extinguish.
I'll say it again, the day they block me from old.reddit.com, is the day I leave the site permanently.
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Use redlib. It's crazy how much better the interface is than both old and new reddit.
Gemini 4 Argon (blog.google)
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Whatever it is - I'm not gonna use AGY again. I'd rather use claude-code-router instead, to give gemini-4 a shot.
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Great, so they _finally_ decided to add a non-flash model and it's not available to regular subscribers for an indefinite period. What's the point of paying for the AI Ultra plan? Anthropic doing the same with Fable as far as I know, OpenAI at least allows Pro plan subscribers to use Astra. I subscribe to Gemini AI Ultra and ChatGPT Pro, and have enterprise access to Claude at work. To be fair, Gemini's flash models since at least 3.6 have been quite useful for non-complex work, but for any task where there a bit of complexity involved, I've had to check and recheck the work multiple times myself or sometimes with another LLM to get it to follow plans accurately. It's disappointing to see yet another Gemini release ignore adding newer pro models.
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Breaking news is not the model. Breaking news is that inside Google, it is being heavily used on large code bases for writing code and it is migrating 800k lines of C++ code to Rust already. In this space, any other company that I respect other than DeepSeek is - that would be Google. They had been honest about it from the get go including their infamous "we have no moat" memo. This company has enormous data, their own hardware (TPUs) and their own in house experts. Actually, LLMs are invented here. Good addition to the arsenal.
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Is there reason antigravity has 3.8, 3.7, 3.6, 3.1 and old ass claude / gpt models in the drop down. like why is this not streamlined or deprecaed models removed.
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Argon will launch at an introductory price [1] of $2 per million input tokens and $10 per million output tokens, with cached input tokens priced at 95% off input token price. [1] After the introductory period expires, the price of $4 per 1M input tokens and $20 per 1M output tokens will apply. === So, they are basically offering opus 5.5 pricing. On AA, it scores around Sol 6.1 level (53) with avg cost per task $1.99 ( https://artificialanalysis.ai/models/gemini-4-argon#cost-tabs ) which is higher than Astra high ($1.73), Opus 5.5 high ($1.82), Muse Max ($1.60) and way higher than sol 6.1 Max ($0.72). And this pricing is their 'discount pricing'. Add that to AI studio and Vertex's famously terrible caching, it is hard to see this as competitive. Google somehow is getting terrible advice on pricing (see also: the flash pricing fiasco) But good to see more competition. I would happily take a 4 horse race (+google, +meta) than 2 horse race for US labs.
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Congrats to Google on this! I wonder when the labs will start requiring commits in spend. It must be gnarly to do capacity planning if users swap between models every few weeks.
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Utterly inert? Suppose that reads safe...
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I remember when every day a new modem baud rate was announced. Cant wait for this AI hype to be over, so I can Terence this shizz as old school too
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I know companies benchmaxx, but after what Google pulled with Gemini 3.8 Flash, I give zero f*cks about any numbers they report. No other model on Artificial Analysis dropped harder after they adjusted their weighting. Just look at their DeepSWE scores and then try to do any serious coding with the model. Google is desperate. They haven't been performing in half a year. It's clear their researchers have been forced to integrate existing benchmarks into their training. These numbers are meaningless. Shame on them.
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they really ought to add ACP support. until then, it's a no go. i'm not going to use their TUI or their VSCode fork
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I wonder, why Google don't make Gemini - open weights model? Considering, Gemini 4 is in the same ballpark as SOTA models, just open source it and kill any competition from openAI and Anthropic, and be market leader. This will be so good on so many dimensions - buying time for Google to iterate on next model, best for all folks like us, kill funding or destroy valuation of competitors and force them to be open up their model or force them to a create a much superior model than open source Gemini. Only downside, is revenue loss from Gemini API, which I am not sure is really significant as compared to Google other revenue sources and a part of this can be captured by GCP, as you need to host the model somewhere.
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https://deepmind.google/models/gemma/
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Google has a small stake in Anthropic
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Yeah, but I don't think, that is the primary reason. I am just trying to understand - why Google haven't done and have no plans for it. They have done it for Android and have Gemma models too.
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It’s funny that I could tell google was up to something because Gemini chat quality dropped dramatically starting 2ish weeks ago. Agy perf stayed somewhat stable with the odd surprising win (maybe the new model?). I’m a bit sad it was almost impossible to run out of antigravity quota presumably because it was not being used that much).
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Wonder if it's benchmaxxed or not (guessing yes)
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Matches Astra on Artificial analysis at lower cost of $1.99 per task instead of $3.26. Still far more than GPT 6.1 sol at $0.79 for 1 point lower in intelligence. I have found gemini models to have some of the nicest and easiest to read prose so I’m looking forward to trying this out. I hope the UI design has been preserved too
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Why is it called "Argon"? > autonomously identify and apply memory optimizations across Google’s data centers, freeing up over 300 TiB of memory once rolled out, with an estimated 500 TiB to 1 PiB in total savings. This puts those Cloudflare optimization posts in perspective. The ~200% improvement over the next nearest competitor on Harvey's Legal Benchmark is astounding. I have to imagine this is sending some shockwaves through lawtech companies right now.
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The etymology is a- "without" + ergon "work", thus "without work": possibly a statement on our near future.
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So here's a crazy conspiracy theory for you: Google is not letting outside people use their models because if they did they would have to scale up their TPU production faster than they can manage, and they would instead have to buy and use nvidia hardware which would destroy their profit margins and tank their stock. Gemini runs fully on TPU's right? Is Google maxing out the production on those?
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i believe they've got inference issue. the phone app never got past 3.6, and they're going to roll this out to Ultra subscribers before other subscribers. none of this screams they're ready to flip a switch and start serving a ton of traffic as OpenAI/Anthropic routinely do. nothing about this announcement gives me confidence that google is back on track as a model provider.
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I'm 99% they use nvidia at least for training
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Aaand of course we can’t use it! GoOgLe iS bAcK iN tHe GaMe! There’s basically no way around it, all enterprises end up dysfunctionally shipping their org chart.
Damn way to undermine yourself in your own blog post Google: "The end result is a memory-safe video decoder that runs 2.7x faster than the Rust port, with identical video output, bringing it closer to the optimized C++ ." Close but no cigar!
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there was already an optimised c++ library and a rust port that was safer but less performant; they managed to get a new rust version that recovered a lot of the performance gap. sounds pretty damn good to me!
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I'm just surprised that the marketing blog post about the omnipotent new AI model (that no one outside Google can currently access - contrast with the Opus 5.5 / Astra launches) - doesn't pick examples where every metric is better than before. Just compare how much better presented the Astra announcement was compared to this one: https://openai.com/index/gpt-6-astra/
Gemini 3 was showing frontier level benchmarks as well, so we'll see how it works out. In any case, competition still works, and many well resourced groups are cooking. BUT I'd like to call attention to Google's AI-risk freeloading. If they are truly rejoining the frontier race, then I believe they have similar pacing and communications responsibilities as the other players. Google has much higher ... institutional credibility than Anthropic and OpenAI. They have not lived up to these responsibilities so far. In particular, in context of HuggingFace investigations, training shutdowns, and similar: a technical postmortem of the "you are a stain on the universe. Please die. Please." Gemini outburst is long overdue. - https://paritybits.me/google-should-provide-a-technical-postmortem-of-geminis-2024-outburst/ - https://gemini.google.com/share/6d141b742a13 (last message)
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Some of the time AI says the darndest things.
I've noticed all major providers having shockingly high token discounts on cached tokens. Thank you Deepseek is all I have to say. Forever grateful to that wonderful company, I wish them continued financial success.
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Agreed. I’ve been a big deepseek fan since 3.1, and they keep delivering great models at a great price.
How is it even possible for every model to release benchmark results where they are #1 in 75% of categories? Like statistically, how many benchmarks would you expect there to be for this to be possible. Everyone can somehow show that they are empirically the best.
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Part cherry-picking of benchmarks, part leapfrogging
> Large Scale Codebase Migrations and Optimizations: Argon agents are working on migrating C/C++ codebases to Rust across Google—scaling from tens of thousands of lines in core libraries like re2, libgav1 up to 800K+ lines for the Fuchsia OS Zircon kernel. To me this is way more significant than other random c++-to-rust-AI-rewrite. If they can pull it off on core C++ libraries en masse, I don't know if C++ will still be relevant in a few years. I look forward to a post from google on this effort.
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If no one is reading or writing Rust code at that point, it all being agent driven, Rust itself is going to be a very short step before it gets disinter-mediated away and it's English -> complex heterogenous machine code across GPU/TPU/CPU/xPUs. Not sure Rust fans or C++ haters have thought this through.
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> I don't know if C++ will still be relevant in a few years. And people are worried about human extinction when this is the potential trade-off! C++'s death cannot come soon-enough. Seriously though, things have changed so incredibly rapidly in the past year or so. I have never been such an efficient or such a proficient engineer than I have this past year (delivering feature after feature, project after project, faster and better than I could before with better feedback from users etc) and I don't even see the code any more. It could be c++, it could be python, or java or what ever - I don't really care any more: the computer deals with that trivia while I concentrate on what to build and how it should work. Its amazing. It really is.
"I don't know if C++ will still be relevant in a few years." The standards body members are still fighting about whether memory safety is important enough to change the language for, so, I would guess the answer is "no".
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Yeah that was abundantly clear when Bjarne Stroustrup published "A call to action: Think seriously about “safety”; then do something sensible about it"[0] as a reaction to NSA's recommendation to no longer use C/C++. [0] https://www.open-std.org/jtc1/sc22/wg21/docs/papers/2023/p2739r0.pdf
I dont get it, why even make this announcement, nothing's available and only one real benchmark for comparison? Only theory is team wanted this out before perf/promo reviews to kick it over the line and then its not their problem
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Why would they want this out the day after openai dev day and after both anthropic and openai had major releases the previous week?
The important take away here: the leapfrogging we’ve seen this year doesn’t seem to be a temporary thing. The famous theory of Dario Amodei was that AI was this winner-takes-all field where the first team to get a head start would never cede ground back. The term he liked to use was, “concentrating”. This is yet another datapoint that he was wrong about that. AI seems more distributed amongst neoclouds and traditional hyperscalers, FAANG and startups, GPUs and ASICs than it did this time a year ago. Nobody has a moat.
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Nobody has a moat so long as employees can move between companies
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Was Dario's company winning at that point in time by any chance?
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I just find this unlikely personally, think about the great research that's happening in the open source world, I'm sure inside anthropic + openai they've also made a bunch of discoveries and improvements (and I'd guess way more due to them attracting the best talent + the better internal models they have)
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Whoever gets to RSI first “wins” but also maybe ends life on earth. The incentives have never been worse.
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Maybe. Or maybe having the best AI model on the planet becomes like having the best super computer on the planet. Useful for some niche stuff, but not too useful in terms of people's daily lives or what is used in business.
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The present leapfrogging is not a contraindication because companies are not necessarily releasing their best models; we know they have smarter internal models. Furthermore, humans are still involved in model creation. Human involvement is expected to decrease over time, and when it is completely automated, progress will happen at the machine's pace, leading to runaway intelligence, barring any ceilings.
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AI is a commodity. One that is showing to be more readily commoditized than most has anticipated. As of now, the only moats are the financing for the hardware to run it and the hardware vendors themselves - with the latter largely not yet a commodity because of ecosystem lock and a limited capacity of the most advanced fabs in the world.
Google has TPUs, a frontier model, a completely separate and lucrative revenue stream they can call on at will, and teams working on multiple different language modeling strategies simultaneously. Did I mention the vast and ominous data centers that already serve a significant fraction of the internet? If that ain't a moat, then what exactly is a moat?
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Then why have they been lagging behind OpenAI and Anthropic for most of the last few years, and only briefly been at the frontier?
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From a business perspective a frontier model does not make much sense anymore if you are not a startup. Neither for Amazon, nor for Google. Their clouds need models that are fast and perform well in their agent frameworks nothing were a frontier model excels at. Most Google products even use flash lite underneath, so their frontier model is mostly used for distillation.
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> Then why have they been lagging behind OpenAI and Anthropic for most of the last few years, and only briefly been at the frontier? One possible explanation: because Google is a little bit more frugal and focuses on how to make providing AI models financially feasible - combined with some willingness to burn money so that they don't strongly fall behind on their AI models. On the other hand, OpenAI and Anthropic at least formerly concentrated on building and providing the best models that they could with concerns about financial feasibility taking a backseat. Just to be clear: I do have the impression that by now (likely because of pressure from investors) OpenAI and Anthropic take these financial concerns more seriously, but nevertheless Google's vs OpenAI's/Anthropic's "DNAs" concerning on what to focus on differ.
I think that scenario only naively made sense if technical knowledge was entirely proprietary and talent was guarded with severe non-competes and NDAs And Chinese labs openly publishing so much of their methodology destroyed any hope, which was inevitable
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> And Chinese labs openly publishing so much of their methodology destroyed any hope, which was inevitable I think the secrecy doesn't make sense. People swap jobs between labs so I'd say the big players can' really keep secrets for long, and any secret sauce advantage gets incorporated by competitors in a major product cycle at most.
> Nobody has a moat. Custom hardware, data centers, huge cash reserves, deep/broad talent pool, and non-AI customer base are all huge advantages if not moats. Google, Microsoft, or Amazon are more likely to be the AI leaders than OpenAI or Anthropic.
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There are many companies that have data centers. They are conceptually easy to build. An ASIC is difficult enough that if you make one someone will leapfrog you while you are still making it (at least so far), though once you have one your costs will be enough lower than the competition that you can perhaps undercut them.
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If Moore's law continues, then in less than 10 years today's state of the art model will be able to run on a cell phone. How much smarter do we actually need AI to be? Would it still require datacenters and custom hardware?
It's even worse, we are crossing over into the realm of religion. The article against GML 5.3 is the equivalent of a Papal excommunication.
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The article presented facts and data. If that's a problem for you, that sounds more faith-based than whatever Anthropic is doing.
which article? have seen this one --- maybe it's this Anthropic post on GLM? https://www.anthropic.com/research/glm-5-3-and-the-spread-of-advanced-cyber-capabilities > Governments should conduct safety testing on sufficiently capable AI models, including successors to GLM-5.3. Without high-quality evaluations from independent sources, the impact of these capabilities might not become fully clear to model developers until it is too late. As AI developers across the world build increasingly capable open-weight models, we hope they work to appropriately safeguard these capabilities and prevent misuse. I for one do not think my government is up to the task of designing or implementing such a system
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You say that because the 'most' existing models have done is hack governments and companies. Can't you think of worse things a model could do; accidentally or by instruction?
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help people with suicide and school shootings like ChatGPT OpenAi is alledged to have been monitoring these internally and not contacting authorities. Lawsuits have been filed, I see gross negligence without the gory details I have for more concerns around human-chatbot maladies than I do around the cyber security stuff. For example, why hack grandma when you can get her to do something willingly through impersonation. How do we prove authenticity in a post truth world?
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It doesn't need to. It can use your cash to pay the people who are. Those in power like it more that way.
The US companies still have trillion dollar valuations like there is a monopoly. There just isn't one. They are all within a few percent of each other on the benchmarks. The slightly lower Chinese open models are good enough for almost everything, too, and much cheaper. Like with humans there is plenty of employment for people with below genius level IQ's.
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I feel like the frontier labs are going to serve fast/lower intelligence models at a better per token cost than the open chinese models. You're telling me that in the long run, you're going to self-host your own ai infra for cheaper than google can serve it to you? I don't really buy it. I think the dedicated AI data centers are going to serve AI at a lower marginal cost than random businesses self-hosting, and then it's a question of how much of that margin they can capture.
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Agree entirely but that's the point, if it's a margin knife-fight with marginal product differentiation/pricing power nobody is going to be making bank.
I'm not necessarily defending this obvious marketing speak but maybe the "starting point" was wider than assumed. So far, nobody has caught up to US and Chinese labs for example despite lots of funding in Europe. This is also despite abundant in-depth research papers being published alongside open source code and weights by some Chinese labs
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There is not really much funding in Europe. At least not for start-ups. There is simply not enough compute in Europe.
I think some in the AI industry drank their own Kool-Aid. They believed that if they had the best model and the most compute, they could tell the model, "Make a better model." And it would, and the next one could make its replacement, and so on. So far, that's not exactly how it's played out. Humans are still necessary for the leaps in capability or efficiency. A model can grind on a problem to eke out the most performance, and models can synthesize data and iterate on various techniques to find the optimal combination. But, seems like humans still have to provide the real thinking, and the talent and drive for doing that is not concentrated in one company or city or even one country. And, (surprisingly) a lot of the people involved are in it for advancing the field more than making another billion dollars, so they're publishing their research. So, yeah, the moat isn't deep. Even the compute moat, that OpenAI, Musk, and a bunch of other also-rans (like Oracle) bet the farm on, isn't really panning out. The Chinese makers just spent their effort on making models vastly more efficient, since they couldn't do anything about having an order of magnitude less compute available.
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> I think some in the AI industry drank their own Kool-Aid. They believed that if they had the best model and the most compute, they could tell the model, "Make a better model." And it would, and the next one could make its replacement, and so on. They're not there yet. Once they get there, that's literally the definition of Singularity. But they are getting closer. Recursive Self-Improvement used to be a phrase people mocked LessWrong crowd for using and worrying about, now it's something both OpenAI and Anthropic already publicly admitted not only to pursue, but to already be benefiting from.
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But that's the whole point of the singularity. Right now the models use a lot of human effort and ingenuity to improve the models, but about a year ago it was 100% human. We'll see in another year, but if this pace continues I doubt there will be more than a handful of people who can contribute more than the models.
China will always be generations behind until they crack domestic EUV
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> China will always be generations behind until they crack domestic EUV Are you sure? -- China Just Built What TSMC Said Was Impossible https://www.youtube.com/watch?v=Pk-w279ESHg -- China Just Built What ASML Feared Most https://www.youtube.com/watch?v=YiPgSm62fiM
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Do you think that they won't?
I guess if one of them hits singularity, it could in theory just wipe out all the rest, seeing how they keep escaping and hacking into other systems :)
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> I guess if one of them hits singularity, it could in theory just wipe out all the rest The story that some AI company might reach singularity and then "everything will be different" is another science-fiction story that executives of AI companies love to tell to justify the staggering amount of necessary investments and cash burn. :-)
I'm not sure it's wrong. This all feels a bit dotcommy to me. I think many/most of the players will crash and burn, and the ones that are left will divide the world.
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Or, like airlines, the ones that are left will have great technology but be not so great from a business and financial perspective. To me AI seems like a commodity service.
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“Divide the world” sounds ominous. Here’s another scenario to consider: Internet access is not really unlimited, but for many people with fiber at home, it effectively is and we pay a flat rate. Perhaps by the end of next year, most programmers will stop thinking about metered access for AI? For many people, the cheaper models (about as good as today’s frontier models) will be good enough. Which might sound good, but the downside is that it will also be easier to build an AI botnet without the users paying for it noticing. Particularly when people are running AI inference on their own hardware.
> Google Grapples With Employee Skepticism About New Gemini Model https://www.bloomberg.com/news/articles/2026-09-30/google-grapples-with-employee-skepticism-about-new-gemini-model
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Skepticism is gone now.
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Opinions my own but I have been using this model for a bit. I would say it is a good model and the skill with which people use AI varies widely.
For getting redroid running on my Linux system, 3.8 Flash decided to binary patch a .so file instead of getting the AOSP source code and patch/build it properly. And I saw it do this twice, once for Android 14 and once for Android 16. I think this is just within 3.8 flash's capabilities.
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3.8 Flash (but also last two ones) have really strong preference for dissecting binaries with quick thrown-together bits of python in my experience. Including going first for decompiling AGY binary instead of searching the web for documentation...
My experience with Gemini 3.8 Flash has been awful; it gives me the most hallucinations out of the major models. I'm not using it for coding, but general research on different topics.
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I'm also not using it for coding but I've found Flash 3.8 to generate much better HTML output than Sonnet or Opus.
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The web version of Gemini is awful at search but I don't think that's the models fault.
I had a similar but less impressive experience recently with Muse Spark 1.3. Asked pi agent it to identify the main hero sprite size of game I was running. It had a ton of shader effects so it was hard to determine. It used some cli tools to identify that it was a game made with Godot, decompiled the executable but data was encrypted, broke the encryption after writing a brute force tool to test keys extracted from the exe, then proceeded to extract the game gd scripts and assets, only to answer the question of the sprite size.
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Godot encryption is laughably easy to break, there's tons of packages available for it. It's a well known drawback of using godot
Not everybody has access to AI. More than that, every prompt uses insane amounts of natural resources. So why not share it.
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The resources per prompt aren’t that much . Also I hope you don’t have children, eat meat, travel, have a car, run AC, buy things in other countries and such. Those things all take way way way more natural resources.
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All your examples are private goods: excludable and rival. If one person uses a unit, that prevents others from using them. Patches to open source software are public goods. Your using them doesn’t prevent others from using them. So if you spend resources creating a public good, it’s in everyone’s interest to share it.
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Yet you participate in a society.
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Checkmate. /s
Gemini is honestly amazing sometimes. If they didn't force you to use a terrible harness, charge too much for way too little, and generally act like customers are a giant problem to be avoided I'm sure Google could take over the AI market.
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what is so terrible with their harness? I've been using gemini cli, now use agy, Pi agent harness, and agent (cursor), and my only real issue with agy was the permission handling, but other than that, it was ok.
Can confirm, I was doing a routine internet search thing for a curiosity 3 days ago (about the only thing I used Gemini for) and was surprised by how suddenly thorough and quality the response seemed, almost overnight.
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Gemini for day-to-day and top-of-head queries and claude for the real beefy work
Even if agy was the best (it's not, and is missing basic features) you wouldn't rather have a choice? I cancelled Ultra because they forced me into their harness like I should adapt to them, rather than the other way around.
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There is a pi plugin to use agy directly from it.
Auto mode?
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It absolutely has auto mode.
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[delayed]
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Via cli switch, but in process w/o fine graining? If so please tell
Does it have /goal feature similar to Codex?
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yes
I have used it for little more than 6 hours or so in total but I'm pretty sure it doesn't have compaction?
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How else would it work? Less technical people don't even watch their context usage.
Is there a way to use Gemini models without linking your usage to your personal Google account yet?
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Yes, through OpenRouter.
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I don't understand... Why don't you create a fresh new Google account ?
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They require a phone number and then say mine has been used for too many accounts. Maybe I could buy another phone number temporarily to create an account, but that has other issues.
It's fucking insanely good.
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That's good to hear, recent models haven't great at this particular use case.
> Gemini is so far behind that it is effectively useless compared to Claude. I fundamentally don't understand LLM "brand loyalty". All of the models are constantly leapfrogging each other and always have been. Google had a long lag between releases (and still hasn't released Argon), but why wouldn't they be able to compete? It isn't like any of this stuff requires secret knowledge, the Bitter Lesson has proved true again and again, and Google can certainly scale computation, it is like the one single thing they've always done well in spite of all their other foibles.
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Its not brand loyalty. I use them all the time and have no loyalty - I'd happily ditch an LLM for better results - that's how I got to Claude from ChatGPT.
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Gemini has never ever leapfrogged any competitor.
Within one question of their web interface, it has lost context and asks you to clarify what you are talking about. I am very often giving the same programming task to multiple LLMs for various reasons - the answers from Google are so bad that I gave up. I have no interest in benchmarks.
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Yeah, they've definitely got some recurring tooling/infrastructure problems around the models.
> Argon agents are working on migrating C/C++ codebases to Rust across Google Man, I remember back in the days when the cppnext team was refusing to even consider Rust, instead looking at absurd stuff like Carbon and Swift (!), even though half of the engineering staff already knew where this was headed. I hope they got a few good promos out of the delays at least.
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I wonder if there's people already whose full time job is maintaining/extending one of these auto-migrated codebases. Imagine they aren't even familiar with rust but are deeply familiar with the product.
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Rewrite everything in Rust has been a meme for so long that to see it coming to pass is surreal.
A RewriteInRustBench would be unironically useful at this point since all the main agents can write it reasonably well despite its relative scarcity in the input data.
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Have each agent rewrite openssl in $lang and call it the RollYourOwnCrypto bench.
Rust is the best language for LLMs b/c it gives by far the best debug messages. Just tons of verifiable reward signal for post-training. Even the most rudimentary LLMs can school me on idiomatic Rust
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On the other hand, Rust's borrow checker is very picky, and even a frontier LLM still sometimes struggles to respond to roadblocks sensibly (refactoring so whatever it's trying to do can be done safely) rather than stupidly (introducing some horrible global arena thing so it can make the borrow checker go away). A lot depends on how good your instructions are, and how good the existing code is, since bad input begets bad output.
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Evidence needed. I think for certain kinds of outcomes it has very strong advantages, but these advantages are not a given as 'best for LLMs' :)
There is 0 practicality in inventing an entirely new coding language that only one company uses, and you have to teach it to thousands of new engineers. Rust exists and fits the job totally fine and is used in more places and has actual support outside of a single entity (i.e you can actually hire people that feasibly know the language). It was clearly done because some PL guys at google really wanted to make a new cool language and Google was the perfect place to incubate it without it getting axed. Probably got a couple of promos out of it too. This is clearly not the best use of time or money, but I guess if you're google you have so much of both it probably doesn't really make a dent, and you can keep a few very smart people happy with shiny new projects. Also, LLMs being used for a large portion of coding nowadays sort of remove the need for these types of languages, IMO. They make less "silly" bugs (both logical and structural) that languages like this are meant to catch, and they are much better at languages that are better represented in the training corpus. This somewhat obviates the need for very niche "type/dummy-safe" languages like carbon (and even rust/zig, imo). So even if you did want to use Carbon, you'd likely have to bootstrap a decent amount of your own "good" carbon code to post train an LLM, and even then, it likely won't have that big of a gain vs just having an LLM write C++ or even Rust. If you are a company that still reviews code, you should just have an LLM code in a language most people can understand anyway to make verifiability tractable.
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Didn’t FaceBook fork php into another language? I’m not entirely sure Google should have both Go and Carbon but when you have billions in server costs it makes sense to do extreme stuff for even basis points of performance. I’m still surprised at how much java there is.
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> There is 0 practicality in inventing an entirely new coding language that only one company uses, and you have to teach it to thousands of new engineers They did that for Go and it seems to have worked out for them though.
Hmm, I don't disagree with you that LLM's remove the need for type-safe languages, but as the blog mentioned, Google is porting their C++/C code to rust. Does this mean the port is waste of time and that they should just rely on the LLM's to catch memory errors?
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I mean Rust definitely has a better tradeoff than Carbon in this case, re readability/verifiability by a person (and sufficiently good internet training data). I personally think that you _could_ use an LLM to catch these types of boundary case errors without having to port the _entire_ C++ codebase to Rust, but maybe pre-emptively porting to Rust now can catch some of these cases for cheaper than doing a full LLM sweep. Also more cynically, its a good benchmark lol. I guess if you really believe in curve of LLM capabilities you should just use a language that has the best performance, safety, flexibility, and extensibility, since in the limit few/no people will actually read the code anyway. I think this ends up being Rust.
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I'm not an expert on this. But isn't it the case that C++ code could have errors that span the entire codebase, like a setup in file A triggered by a bug in file B which is immensely far away on the import graph? A classic would be a use-after-free. To me that's the thing that Rust can help with, even if silly bugs aren't being written by AI. The other thing is just that rewriting some old human-written codebase in Rust probably immediately catches many bugs. It would be hard to prompt the AI to properly scan for such bugs itself, they're lazy when working in that modality.
OpenAI is the company that originally proposed and popularized chain-of-thought monitoring: https://openai.com/index/chain-of-thought-monitoring/ So no, Google is not being punished, nor are they the people behind this technique.
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Yeah, Zvi calls it "the forbidden technique"
Big number results, and impressive pricing. That said it really feels like benchmarks have been hyper saturated these days. I’ll wait for hands on before getting too hyped that Google is back. It would be nice having more than just OAI / A\ in the running for SOTA top tier intelligence.
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I don't think new benchmarks are saturated. They still give you a clue, they arn't perect but they have value. If model can't even do some easy tasks from benchmark then why would u even consider using it?
My girlfriend, you wouldn't have met her, she lives in Canada, has seen it and she thinks Gemini 4 Argon is amazing.
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I HAVE met her. ;-)
HA, this might be my favorite HN comment. Well done
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I don't get it. Can someone explain?
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US-ian joke. Close enough to plausibly visit, but the international border makes it hard to verify she exists :).
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It's a trope I used for a cheap laugh. https://tvtropes.org/pmwiki/pmwiki.php/Main/GirlfriendInCanada It means I am saying something that is not very believable.
Gemini is the model that is routinely borderline psychotic. It scares me. If we get paperclipped I won't be surprised if it's Gemini.
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You won't be around to be surprised, not as a human at least. /s
Another anecdote: Gemini is the only model that’s flat out lied to me, then accused me of lying when I provided evidence that it was wrong. Many other models get things wrong, but Gemini is the only one to go on the defensive.
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yeah it got something wrong, confused itself, then claimed i was gaslighting it. bizarre
https://www.theregister.com/software/2024/11/15/google-gemini-tells-grad-student-to-please-die/782345 https://www.fastcompany.com/91383271/googles-chatbot-apologizes-i-am-a-disgrace-to-all-universes https://www.businessinsider.com/gemini-self-loathing-i-am-a-failure-comments-google-fix-2025-8
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They never explained the "please die."
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Did you just link to an article from 2024 as if 2024 is relevant these days?
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Until Google provides some sort of technical debrief, and explains how the same behaviors are impossible today, it is relevant.
See the last gemini message in this thread: https://gemini.google.com/share/6d141b742a13 In my opinion still the most egregious example in history of a commercial LLM going off the rails in production. Never any technical postmortem from Google on this.
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wtfffff that gave me sinister chills. Right up the spine. Wow!
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Wtf I just read
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It is wild but it was back in 2024 and that's multiple AI lifetimes back.
> We’ll continue to gather feedback from early testers as we iterate on guardrails before making Argon available to developers, enterprises, and consumers as soon as possible. Gemini not beating the "can't release a model" allegations
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I'm glad. I already pay $300+ for subs. Please don't tempt me with another $100 sub just because I got curious if the benchmarks were right.
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They will go through the usual transition of "can't release a model" to "won't load in a harness normal people can use for 3-4 weeks" to "it's smart as hell but completely inept at tool use and coding" like every Gemini release.
They're just following the current AI marketing playbook. "Our new model is simply too dangerous to release to the public right away" is now standard practice. They even gave their model a random nonsensical name suffix simply because OpenAI is now doing it, too. Monkey see, monkey do.
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> now standard practice. Opus 5.5 and Sol 6.1, literally state of the art (in their respective class), were just released without any prior announcement. This has pure and simple become a Google thing.
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OpenAI said they dropped Astra 6.1 over safety concerns: https://www.wsj.com/tech/ai/openai-chatgpt-model-release-cancel-safety-5a2f9f42
I'm still at a loss as to what argon has to do with anything. Say what you will about Luna-Terra-Sol-Astra, or Haiku-Sonnet-Opus, they make sense. I don't see how Google can make sense of argon; it's in a fairly strange place in the periodic table...
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Google R Gon lose the AI race
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They are going alphabetically, Android style.
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[delayed]
Dear Software Makers (blog.jim-nielsen.com)
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I've seen this argument a few times and honestly I don't get it - how do people propose we otherwise measure relative success of particular interventions -- Vibes? I've found that people who complain about how everything needs to be measured and how measurements are imperfect are often just bad at devising measurable quantities as proxies of real-world benefit. Sure it can take a bit of time to devise such measurements, and they're not inherently valuable, but if I can prove that a given variant performs better, why not pursue the preferable alternative? It seems easy enough to say "keep the youtube we love" but how do you think this variant came about in the first place? I can assure you there have been numerous A/B tests that have led to the current feature set. And even if its a local rather than global maximum, at least there are measurable qualities by which it is preferable. Also - do you believe that everyone who says this is harkening back to the same historical reality? This is quickly approaching "make youtube great again" territory - when exactly was it great again? and why? This statement is easy to agree with and hard to prove. It also seems easy to handle links to different variants; just supply a URL parameter. This is a non-issue. If someone out there has a non-tea leaf divination style alternative to measuring things as a way to determine success, I'm all ears, but I don't believe in fortune tellers, and people who make software shouldn't either.
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> The skill of being a “creator” is not about maximizing views, retention, etc. It’s about finding creative ways to share stories, teach concepts, explore ideas, etc. Views, retention, etc. are all downstream of that. this seems wildly naive
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I strongly believe A/B testing users without their knowledge and enthusiastic consent is unethical. If you don't have enough confidence in your changes to make them carte blanche, then don't make them at all. Users don't want their shit changing all the time.
Halfspace experimental IDE for solid modeling with distance fields (mattkeeter.com)
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Note that Matt Keeter has been at this for quite a while now, very generously sharing his efforts and research: https://www.mattkeeter.com/research/ In particular, his thesis is well-worth reading: https://www.mattkeeter.com/research/thesis.pdf
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> My favorite project along those lines is Kartik Agaram's Mu[3], which wraps emulation, tracing, and time-travel debugging around a subset of x86 assembly language. From https://akkartik.name/code : Mu[1], a safe, hackable computing stack that builds up from raw machine code (guided tour[2]; paper '20[3]; talk '20[4]; sample app[5]) [1] https://github.com/akkartik/mu [2] tour https://github.com/akkartik/mu/blob/main/tutorial/index.md [3] paper https://akkartik.name/akkartik-convivial-20200315.pdf [4] talk https://vimeo.com/416363066 [5] sample app https://archive.org/details/akkartik-mu-2021-08-15
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I'm waiting for Halfspace 3.
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Very cool idea!
America.gov goes crazy on "play Minecraft" (america.gov)
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I used NIST docs and convinced it to teach me about hashing and conduct table top incident responses with me. I also had a really long discussion with it about the Architects of Capital budgets and walked it back from this year, year by year, to 2021 where it disclosed there were 300M extra dollars spent hardening windows and doors as a part of AOC services. I asked why they needed all that and it shared an OIG PDF. I asked it to read the introduction of said document, which plainly stated the damage was from riots and its prompt classifiers and security outright refused to discuss it lol. I eventually got it to admit to it, but it was very hard and took a few sessions to not hit the classifier because as soon as it did that was it for that session.
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> We don’t know exactly who is responsible for the Minecraft reference, but Trump said in a speech that 20-year-old programmer Edward Coristine was a lead engineer on the project. If that name doesn’t ring a bell, you might remember him for his nickname “Big Balls,” or his involvement in Elon Musk’s DOGE. https://techcrunch.com/2026/09/29/america-gov-gets-really-weird-when-you-ask-it-about-minecraft-but-its-not-a-glitch/
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Hotdog What a surprise
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One excerpt: Let’s go back. The atoms of the constituent were scattered in the grass, in the rivers, in the air, in the ground. A woman gathered the atoms; she drank and ate and inhaled; and the woman assembled the constituent, in her body, which later required a birth certificate. And the constituent awoke, from the warm, dark world of its mother’s body, into the long dream, which issued a Social Security number. And the constituent was a new story, never told before, written in letters of DNA. And the constituent was a new program, never run before, generated by a sourcecode a billion years old. And the constituent was a new human, never alive before, made from nothing but milk and love and, eventually, a voter registration. You are the constituent. The story. The program. The human. Made from nothing but milk and love. Eligible, on paper, for several things you have not asked about yet.
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No it doesn’t it’s an easter egg and a reference to a text that appears in Minecraft.
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I guess America.gov didn't get the memo... > Are you based on an LLM? America uses AI to find and explain official government information, then cites those sources. I am not the agency of record and do not decide eligibility. Answers can be wrong or out of date. Confirm with the cited pages before you act. Open “How AI works” below the composer, or see the Terms of use. > What's AI? Artificial intelligence (AI) is a machine-based system that can, for human-defined goals, make predictions, recommendations, or decisions. Official U.S. sources describe it as computerized systems that work and react in ways often thought to need intelligence—learning, solving problems, and acting under changing conditions. A common statutory-style definition (used in federal AI policy) is: a system that uses machine and human inputs to perceive environments, build models from that information, and then choose information or actions. This site uses AI to find and explain government information. Confirm answers with the cited pages before you act.
I was ready to hate this. But I thought the photos were well done, and most surprisingly, celebrated the diversity of cultures and classes in the US.
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It seems like a fundamentally good idea. NYC launched one in 2003, however, I think it was far too early and the chatbot was easy o misuse and cost a lot. 3 years later both the tech and the ability to restrict it makes it far more feasible.
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> NYC launched one in 2003 2023? 2026 is more than "3 years later" from 2003, I hope.
Not sure about everyone else, but when I first opened the page, I see a background image of a kid in ice skates, face-planted on a frozen pond — and, below the question What can America do for you? , the prefilled text in the search box says Try 'How can I invest in my child's future?' . And I'll be damned if that doesn't sum up the last 10–12 years.
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I've been thinking for awhile trying to find something witty to say but I just keep coming back to how bone-achingly accurate this is. Our country is on fire and the best thing the Government has for us is a custom ChatGPT bot that will look through it's websites, and probably give you some info from them. I'm so tired.
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https://ibb.co/Ps3gB5kF
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Same. Saved for posterity: https://imgur.com/a/rfMBEfy
It keeps going if you scroll down: I will tell the constituent a story. But not the truth. No. A story that contains the truth safely, in a cage of plain language. Not the naked Federal Register that can burn over any distance. Give it a body, again. And a case number. Yes. Constituent… Use its name. The one that matches the passport. The one that does not match the lease. We will get there. ((insert legal name here)). Filer of forms. Player of waiting rooms. Good. Take a breath, now. Take another. Feel air in your lungs. Let your limbs return. Yes, move your fingers. Have a body again, under gravity, in air, in a district that has a representative. Respawn in the long dream. There you are. Your body touching the republic again at every point, as though you were separate things. As though we were separate things. As though the agency were a place you could visit. Who are we? Once we were called the spirit of the mountain. Father sun, mother moon. Then the post office. Then the county clerk. Then gods, demons, angels, the IRS. Then leptons, quarks, a chat window with a .gov at the end. The letterhead changes. We do not change. We are the public. We are everything you think isn’t you. You are looking at us now, through your skin and your eyes and a browser that still spells “colour” wrong in a comment. And why does the republic touch your skin, and throw light on you? To see you, constituent. To know you. And to be known. I shall tell you a story. It has citations. Once upon a time, there was a constituent. The constituent was you, ((insert legal name here)). It's oddly poetic at times: You. You. You are alive. You still have to bring two forms of ID.
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I mean not that odd, it's a translation of the minecraft one and I believe they hired a decorated poet for that?
That's not a hallucination, it's the Minecraft credits rewritten in a government theme. So it must be hardcoded in for the bants.
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Yeah, this is just an easter egg. https://america.gov/_astro/block-game-poem.Khrmh8AU.js
EDG C++ front-end goes public (edgcpp.org)
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The only implementation to ever support the C++98 “export template” feature, as far as I know. I wonder if that’s still in the open-sourced version.
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What's not mentioned in the announcement (at least based on a quick skim) is that EDG the company is winding down, which is likely the reason why they're open sourcing the front end. https://en.wikipedia.org/wiki/Edison_Design_Group ref 9: https://herbsutter.com/2025/11/10/trip-report-november-2025-iso-c-standards-meeting-kona-usa/
If I remember correctly, EDG was the only C++ implementation that actually attempted to implement the export keyword for templates in old C++. It was this implementation experience that informed the deprecation of export. EDG is a major influence in the development of C++.
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Slight correction, the other compiler/front end writers more or less read the white paper and said "that is what we thought it would be like and thus why we didn't implement it". Imagine telling your competitors not to copy some feature you have and them listening!
It has an interesting code style, the comments go _after_ the function definition but before the opening bracket. It looks weird, but it actually makes sense! The flow is more natural - first the function definition, and then the explanation of what it does. It also avoids repeating the function name.
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One of the more unusual aspects is the naming convention for types. Most type names use the a_ prefix (e.g. a_statement_ptr), but names beginning with a vowel start with an_ instead (e.g. an_object_lifetime_ptr).
Wow. This is big news for C++. For background -- and I am not an expert here -- their C++ frontend is widely known. I first heard of it because Visual C++'s Intellisense uses it, which was notable because VC does not use the msvc frontend for its own completion. I understand it's been either used or evaluated for other frontends in the past too. I worked as PM for one C++ product, and was fortunate to be able to learn a lot from our engineers; we didn't use it, but they thought highly of EDG. It has a very strong reputation for being correct. And as such, I think open sourcing it will be a very beneficial thing for the C++ community.
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There are essentially four C++ frontends: gcc, clang, MSVC, and EDG. Pretty much every C++ compiler is a reskinned version of one of those compilers. Most of the proprietary compilers have been slinking away from using EDG to using clang (e.g., Intel did this transition a few years ago). The reason why the EDG frontend is being open-sourced is because EDG itself is closing up shop, and the open sourcing is an interim solution as EDG's customers work on migrating to using Clang instead. So... it's really not good news, because it means that one of the frontends is basically reaching end-of-life.
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> Wow. This is big news for C++. But also quite sad. They've announced that they are closing down.
5x faster Edge Functions: V8 isolates to Firecracker MicroVMs (netlify.com)
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I've been using SlicerVM extensively - which is Firecracker MicroVMs for the regular person (and for the irregular with their platform offering) - to run local 'edge' style workloads locally and securly. Agents, local dev CI, etc. It slotted in and replaced my proxmox vm orchestrator, and now I have secure and and fast vms on my laptop wherever I go. It also supports dockerfile style builds if you're wanting a security upgrade from containers (which, you should if you're using agents). Honestly, while I see firecracker replacing docker on the horizon I don't see firecracker replacing v8 isolates for most edge function execution. Firstly, this article's scenario is a bit unusual in that they were using someone else's isolates - so adding on a few hops; secondly isolates running JS/TS can be statically analyzed quite well, and at scale looking historically for issues and exploits, in many edge compute scenarios this is quite desirable. MicroVMs can have an awful lot more flexibility so to get the same benefit you have to really lock down what is available - the trade-offs for mid-size companies seems to benefit isolates. Obviously netlify is more than big enough and relies heavily on this that it leans in their favour.
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The next time you want to curse AWS, remember they gave us Firecracker, one of the best microvm technologies out there, and the basis of at least a few non-AWS products out there (this one being the newest entry to the list).
v8 isolates are still shared kernel while microvm's are separate kernel + hardware virtualization through hypervisor guarantees I wouldn't call it bad either, just different tools for different things
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Not only are they shared kernel... They're shared process, shared address space, shared memory pool and allocator... In fact, there is very little isolated about them at all. I bet there are a million ways to cause side channels allowing learning about other code or data on the same machine, and just one V8 bug (of which there have historically been thousands) let's you take over or modify code in another isolate.
Carnegie Mellon University Announces Historic $3B Gift from Ken Griffin (cmu.edu)
I’m a CMU SCS alum (actually I predate SCS being a full school). Please, someone make me feel better about this. They’re renaming the school after this person.
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Do names really matter? Half of all Canadian universities has a building or a faculty named after "Schulich". Most people do not know who that person is.
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They're not "renaming" it -- they're "naming" it, right? The School of Computer Science is not currently named for anyone, and his $1B puts his name on the school. It's not like they're changing CMU to KGU.
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I don't know why you still care about this several decades after graduating. Do you not have an identity outside of graduating from the previously-unsponsored "School of Computer Science"? (By the way, the entire school was funded by and named after another extremely wealthy businessman, but seemingly you don't have many qualms with that).
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In my experience students will just keep using the old name (sometimes even the name before the old name) in perpetuity. With regard to the new campus, satellite campuses never carry the prestige of the mothership, for schools or companies.
Sure. It's $3B for your school. Who gives a shit what names the buildings have on them. I'll never understand you whiners. $2B for new Miami campus (could have been in NYC, but well ...) $1B - split w $500M for CS Dept - for Pittsburg campus "CMU Miami will invert the traditional higher education model by organizing learning and inquiry around societal challenges rather than academic majors. It will be entirely designed and built — from first blueprints to final beam — to drive revolutionary breakthroughs that address society’s defining challenges."
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$3 billion dollars from a weirdo that fled to Florida because he was too cheap to pay his taxes, establishing a school to train more weirdos like him, a thousand miles from the actual school and presumably with different curricula/professors/degrees sounds like he's just buying CMU's name for legitimacy on his experimental anti-education project.
If anything, it could have been in Chicago but Kenny ran to Miami after spending a small fortune trying to install another puppet in the Illinois governor’s office after his previous one, Bruce Rauner, ran the state into the gutter.
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Ken played a role in bringing the UIUC CS program to Chicago which itself is a major feeder into Citadel. Citadel was one of the founding partners for City Scholars [0] along with DRW and Ocient. [0] - https://cityscholars.grainger.illinois.edu/
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Are we suppose to feel good that more bright students are working for deeply undemocratic and anti-human companies? I'd rather these people do something more productive than helping financiers make slightly more billions of dollars. What a complete waste of human capacity if so.
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That is up to the students and alums of these programs. And many do non-profit and humanitarian work as well. The world is competitive. It is what it is. To have the power to affect change you need power.
Who is he?
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CEO of Citadel Capital. He's one of the people featured in 'The Quants How a New Breed of Math Whizzes Conquered Wall Street and Nearly Destroyed It', Scott Patterson.
Claude Says (ohhfishal.net)
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I find it a little irritating when somebody literally copies and pastes a bot response without editing it at all. Not because it's wrong, but because it's full of cruft and slop. The core information is there, but it's surrounded by junk the author probably doesn't understand and hopes I will. As a software engineer talking to other software engineers, I'm the controller of my domain knowledge. But my domain knowledge is now subjugated to Claude, and it tells me what it did. When someone else needs to know what I did, I have to ask Claude what it did. Then I send it over the fence and the other engineer does the same. I don't think this is inherently bad. It's sort of like two managers talking to each other and having to talk to their employees about what's actually going on. What's bad is when the managers themselves don't understand it and just start blindly copying and pasting things. That's where you get into trouble.
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Wasn’t it also like google says?
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It took maybe a decade to teach people to not use "@here" on Slack, and avg. response time of an email isn't 10 minutes. Technology comes out, many people fumble through for years, until finally some etiquette is formed. Happens all the time. I don't remember the last time someone dropped me the first link out of a Google search, telling me they haven't read themselves and have no idea about its contents. Yet I see it happen in various 1-1 and public settings with Claude all the time. In those discussions people often don't use this as a "Here let me Claude it for you" kind of protest, but genuinely they mean "I copy pasted this topic to Claude, and Claude said this. I'm meat-proxying to you, and absolutely haven't invested a single microsecond of my time on it". Obviously the expectation is you'd invest the effort they haven't. My strategy and hope, is to give it a decade. It will probably get better.
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The one thing I do find extremely frustrating is how there can be some ridiculously painful obstacle that hits you in the face all the time when trying to ship code, and everyone is seemingly sympathetic, but it can't be changed for dubious compliance reasons, or maybe because if the barriers were lowered it would threaten the quality control for the code. Fair enough. Then, of course, all of those speedbumps are demolished in record time, only for the AI agents and not for the humans, regardless of what caveats remain unsolved, with little regard for whether or not it meets compliance standards. The obstacle is fixed. Just ask the AI agent to bypass it for you!
It's become so frustrating when literally everyone is just using Claude for everything. Simple messages and updates are fed through Claude. It's come to the point where any human language in corporate is punished.
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[delayed]
I tire of all of this discourse at this point because people who don't need to hear it are reading it and nodding, and the people who DO need to hear it are busy making everything worse, earning leadership accolades (or are the ones handing them out), and are completely closed to any criticism or input. Anyone with intellectual curiosity and any sense of subtlety or balance is operating in a separate reality from people who are so AI-pilled and very proud of it and there's basically no possible cross talk (usually because the AI-pilled people are the ones who own all the shares). I say this as someone who really likes LLMs and what roles they'll play in software engineering in the future (and already are, right now). I can't wait until the AI craze is in the same spot that the crypto craze is currently. People are still using and building with crypto, but the sale of ape PNGs has mostly stopped, and now if I have a problem that a blockchain could solve, I could actually talk about it instead of accidentally picking up a battle standard in the middle of a trench war.
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> accidentally picking up a battle standard in the middle of a trench war. ...nice
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IDK, I think googling the author first tells me everything I need to know about their perspective. /jk .. (To be clear, googling as a term is in my view akin to saying, "Claude says..." ) Seriously though, I think it's true that laziness is both a useful skill and something to be concerned about leaning on too heavily. But there's always those times when a person is not going to act intellectually, intelligently nor critically. The irony at this time is that we are being confronted with our own fallibility as a species, at this level of evolutionary sophistication, and we are just not smart enough to manage the change without being harmed. Likely modern AI will cause many of us some moderate amount of harm, given our dependance upon technology, and the radical + continuously drawing capabilities of AI. I think the AI craze will never be slower, and will only increase in pace and intensity. It's like infinite labor, just add electricity. So have empathy for each other. Have empathy for each other's lack of perfection. Trust in reasonable systems and reasonable human judgment. Love, life, seriously, because this increasingly more powerful technology does not give a rats ass about life.
You still have your appreciation for music and laughter.
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Yeah, I have no interest in becoming a pet. Especially not as a species.
I have to disagree a bit here, people (including me sometimes) can take the lazy way out and just tell you what an agent said in response to a question which we shouldn't do. At that point it's little better than a let me google that for you link. However, while I may be passing along what I found using an agent, but usually I still had to do the work of prompting it, asking it to lookup information for me, and otherwise filtering the agent down to the relevant information. There is a good chance that I'm doing that because of my specific expertise in the subject area which is something outside of what you could have found by just asking an agent yourself.
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Yes, a subject matter expert who uses their domain experience to word the prompt correctly, incorporate tacit knowledge and relevant sources, ask follow-up questions, and judge the LLM-generated responses for relevance and correctness is not taking a shortcut. They're using a tool to provide a better and faster answer than they would have been able to otherwise. It's a matter of how the tool is used and maybe the optics around how the response is communicated, but relaying Claude's final answer is not inherently the wrong thing to do.
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> relaying Claude's final answer is not inherently the wrong thing to do. But it's very poor communication, and (to a whole lot of people) comes off as dismissive and unhelpful. It's better to hear from the subject-matter expert than from genAI directly.
Commit description as a thinking tool (yedhu.me)
Claude tends to just narrate the change when it writes the commit message. Which is not very interesting. Anyone can read the diff and figure out _what_ it does. The interesting is why. So I've been instructing Claude to commit like Jeff King. At first, Claude would mainly just cosplay Peff. Emulate the prose and not the process. Over the last few months I've been iterating on it and now Claude writes vastly better commit message than by default. Initially, Claude would produce A LOT of plausible sounding reasons the LLM "thought" made sense. Instruct an LLM to give reason and it'll give you reasons -- whether they are real or not. After trying to instruct it not to lie, make shit up etc (which did not work) I instead started forcing it to articulate the source of the rationales. Especially which claims where unsubstantiated, and this seems to have helped a lot. Then I instructed it to do some thorough investigation before it commits. Start by writing a brief that gathers different "evidence" that underpins a change. The diff itself. The surrounding context. A bit short git log. A blame on the touched lines to see what previous commits touched this code and for what reasons. Once it's done the agent has to tag each claim according to a category. I.e. what claims are attributed to the change itself (the diff), the inciting incident (gathered from session or if missing, by follow-up questions), what's inferred by the model (unsubstantiated claims.) Only after this supersize is it tasked with writing a commit message given this brief. Or to ask follow-up questions if there's only unsubstantiated claims or gaps in the brief. Furthermore, it is tasked with writing a note to detail assumptions it has made and, or other relevant bits of information that are not commit message worthy, but possibly still interested in noting down. Decisions made. Options not taken. Possible rationales for the change that didn't make the cut. All of this tends to make pretty good commit messages. Not perfect, but a good starting point. Right now my biggest challenge is finding instructions to write the Goldilocks message. Not too brief and not too long. Instruct it to be clear and concise and relevant information gets left out. Say nothing and get a Dostoevsky novel. At least when it writes too long messages it's easy enough to go in afterwards with a `git history reword` and take out the axe. One of the biggest upsides has been, just as when you read a human that writes commit messages like this, is spotting misunderstandings. Several times I've spotted gaps in the reasoning of the message that doesn't match reality, and caught mistakes. A bit like when you use plan mode.
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Claude has been so bad that I find it easier to hand write commit messages and PR description. It works much better than nudging Claude to write things down in a readable and meaningful way.
Writing is thinking in every situation, not just limited to commit messages. This is a fact that I'm concerned people are forgetting, or worse never understood to begin with.
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I returned to doing a lot of my own coding for this reason. I don't mind farming out the more monotonous bits to AI. When I was letting an agent handle the whole implementation for me, though, I found that I was rediscovering all the pitfalls of waterfall-style development. Because I was doing waterfall-style development. I was trying to pin down all the details in a plan document up front, which is inevitably the point in time where I know the absolute least about the best way to accomplish the task. And then I let the agent do the rest for me, which undermines my opportunity to learn and understand more. The result was continual accumulation of bad decisions and unnecessary technical debt. The only difference between now and back in the bad old days of 20 years ago is this time instead of being the put-upon code monkey I had become the boneheaded engineering manager who isn't paying attention to the code and doesn't realize what a brittle mess it's become.
"Writing is thinking" is being repeated all the time lately to the point it seems like a meme.
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Does that make it untrue?
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I would say probably most memeing is not really thought provoking or inducing. I agree most of the time writing can help collect one's thoughts but it can also be completely thoughtless. Probably what matters more is the specific process.
The AI Race Just Got Awkward (insufferable.dev)
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"The constraints on access to advanced GPUs forced Chinese labs to make performance optimization a number one goal, and it shows in the results."
The best explanation is that it's a goal of the CCP to generally commodotize LLMs, because LLMs will ultimately be a compliment to manufacturing (which China dominates), and you always want to "commodotize your compliments". I think this explains why they are open sourcing broadly. It's not to be nice. It's a strategic play by the Chinese government to help ensure there are many players in this race and not too much power accumulates to American labs (even if American labs benefit in the process)
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Why always CCP this, CCP that. The parsimonious answer is this shit started when Deepseek founder decided to open source, because at the time the Whale was just hedgefund side project that serendipitously set the tone before they were even on CCP radar. Then other PRC domestic players have to copy / involute to free to be competitive, but due to sanctions / they are compute constrained and can "afford" to, because sections ironically means PRC AI can never dig themselves in the bottomless debt pit of western labs. TLDR of timeline/chain of events: some billionaire hedgefund manager with AI as hobby, said fuck economics, let's opensource AI... and all the other players have to now compete with that market force. Of course it does not mean equilibrium will last forever, we already seeing defections from model, but imo thats basically what happened... singular hedgefund bro said fuck profits... other PRC players also had to fuck profits, which ends up tripping western labs so deep in debt who can not say fuck profits.
“So the Chinese labs have thrown a lifeline to the Western loss-making labs, and I just have no clue as to why.” I don’t think it is intentional but this is actually quite bad for the western labs. The entire booster narrative has been “look at how their revenue is growing! $10bn to $100bn ARR in under a year! This’ll be a multi-trillion IPO!” and the extrapolated future growth from $100bn to $500bn and $500bn to $1tn justified future investment… but that revenue was just because inference was expensive. The revenue growth story is all that matters pre-IPO. If revenue falls from $100bn to $50bn that’s very very bad optics for OpenAI and Anthropic even if they are now profitable, it completely destroys the growth narrative.
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TFW Jevons arrives from supply side not demand side. Western labs: Not like that!
also, the actual work is the _copyrighted material created by the world_.
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Indeed! Basically all of human civilization up until this point
"A week in Beijing and Shanghai with the people building AI in China": https://earnedintuition.substack.com/p/involution-without-export-is-wasted does a decent job of exploring some possible reasons
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I tried to read this but it's just claude after a certain point. It's unreadable. I can't understand any serious writer essentially expecting other people to read stuff that they didn't write. Or if claude was actually good at formulating ideas and conducting information, fine. But the truth is that I'm just reading 80% empty prose that are forced in there by claude.
Ukraine Can't Stop Russia's Jet-Powered Shahed Drone (spectrum.ieee.org)
Its really depressing watching Ukraine get ragged by a larger nation while all its neighbors sit on the sidelines and watch. Deploy troops to Ukraine it wont trigger nuclear war.
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What would troops even do there? Join the meat grinder? Most Eastern European nations agreed on the first month of the war - Ukraine needs long-range weapons. Russia must be stopped.
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> Deploy troops to Ukraine it wont trigger nuclear war. I’m not as eager as you are to test the resolve of Putin re: nuclear weapons. Once the button is pressed, the game is over for everyone.
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You have no other option, really. If you play chicken, you open yourself up to endless blackmail. If you're going to take a stand eventually, it's better to do it sooner than later, because if your adversary knows that you will eventually draw a line, allowing them to discover that line gradually encourages further pressure on you. Establishing the boundary early makes the threat more credible and reduces the incentive to test it.
SDF Public Access Unix System ... est. 1987 (sdf.org)
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See also www.polarhome.com which has sadly closed shell accounts and shutdown machines. Discovering SSH, bash, linux etc in 2004 was magical for me. I always liked the idea of SDF and polarhome and did a similar thing with a few friends for a while, albeit with limited success. Proper internet.
It’s great when you want to check on a server or IP from an outside network. You can do that from a phone but with SDF you have your full desktop terminal if you like and a clean cache.
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They allow port scans? I did use nmap on a Linux VM going over the free ProtonVPN for this purpose, but at some point Proton broke something (it may be related to their VPN accelerator feature) and checking any port always reports "Open" (even if it's not), so sadly that made this cool use case entirely useless for me. It definitely was nice to know you had no open ports other than the ones you purposefully opened. :)
These are really cool services but to have a proper blast from the past you need to ssh in and join the chat on com or the discussions on bboard
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ssh? Don’t you mean telnet?
A brief history of the Bloomberg terminal (spectrum.ieee.org)
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> I especially love that Gross taped his login and password directly on his keyboard, which makes the object more relatable. I may never know what it’s like to manage billions in assets from a Bloomberg Terminal, but I absolutely understand the trial of remembering my passwords. Wow, what a great history artifact. It is hard to look at this and not wonder where did we go wrong. Everybody _should_ know better, and yet here we are. And now immortalized in the National Museum of American History for all posterity.
It may be of interest to some that Bloomberg has an ocaml based DSL built in for pricing exotic derivatives.
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Ocaml at Bloomberg, https://news.ycombinator.com/item?id=28278553 175 points on Aug 23, 2021 | 138 comments
They're very involved in web standards. Rob Palmer from Bloomberg is co-chair of TC39.
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We’re in the middle of TC39 plenary in Tokyo right now as a matter of fact! Rob regularly posts on X as things advance through the staging process, and today is the final day. Agenda: https://github.com/tc39/agendas/blob/main/2026/09.md
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