Unlurker|Replay|About
U.S. postal inspectors shut down website selling counterfeit postage labels (postalemployeenetwork.com)
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I wonder who benefits from the postal service going under from scams like this
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The USPIS (mentioned in the article) once came to the federal prison I was at to tell inmates that using stamps as currency was illegal. There are flats and there are books. Flats are a sheet of 20 Forever stamps that you would get at a drug store. A book is 20 stamps, used or not used. Generally there are different values associated with flats because you can get cash for them on the streets. You can get them to the streets via an officer if you're ballsy. Or you can just find discreet ways to mail them. The value of a flat where I was at was about $13-$14 depending on your vendor. A book was generally worth $10. If you were buying bulk (and depending on who exactly you were buying from), that number could go down to $12 and $7 respectively. If you were buying from someone that was running a ticket (sports gambling) they had more incentive to get rid of their stamps. Some people had tens of thousands of dollars of stamps in their property and they wanted to convert them. If you were buying from someone running a store (think "buy and resell commissary"), their business model was dependent on flipping books of stamps in exchange for more commissary. They could sell a ramen for 3 stamps ($1.50) when it was worth just 50 cents. Flats were easier to hide because they are, well, flats. USPIS once came to my facility and "warned" us.
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Have an optional crypto stamp and prioritize it, generating extra income for postal services
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the lesson here is you do not fuck with the us postal inspector's service because they do not lose
This article is about USPS.
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That's why they said "also"
No. That won't work. Every carrier has it own way to generate tracking number. And that number must have registered in the carrier's database before it becomes "valid/sanctioned". If you generate a random number even fitting the pattern and looks like a real one, the scan will fail with an error and fail to register tracking information every single step of the way that package gets scanned from dropoff at the retail postal office (this was the case) as bulk inbound pickup from USPS are only allowed for USPS verified partners. Label creation (which generates the tracking number) is a billable action in their API. Some volume partners have pre-arranged/allocated tracking number segments assigned to the bulk volume partner/shipper (similar like how IP address v4 is assignment from IANA). And that pre-allocation tracking number range requires $$$$ contract in place. Billing that is post paid like cellphone bill. Most retail shipping software (like shipengine, pirateship etc.) bills using the prepaid method, meaning you will have to pay for the label at the time label is generated. Disclaimer: I used to work for a carrier that integrated a few dozens of global shipping carriers.
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Yes, I’m deep in e-commerce and fraudulent labels are all over the place. Even Amazon, 3rd party sellers are using these fake labels to sell items for cheaper and win the buy box. Even UPS has this issue. I get that they have reverse engineered how the numbers are created, but how are they showing up in USPS and UPS databases? Are shipping platforms like shipengine getting these labels pre-made and this fake label seller has reverse engineered how these tracking numbers are created programmatically and are essentially using the ones allocated to these big shipping platforms?
Surely most drugs could be sold in small enough envelopes that you don't need parcel postage. I know when I was using DNMs most packages were a simple large letter stamp stamp which covers 35.3cm x 25cm x 2.5cm and a maximum weight of 750g. So I doubt dark net drug orders would have been the trigger for this sort of change.
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As long as Congress thinks drugs are shipped in giant parcels, it doesn't matter how drugs are actually shipped.
Most countries when presented with evidence that someone who lives there did something criminal will arrest and turn the criminal over to the country the crime was committed in. Sometimes they will put some stipulation in (Europe commonly won't turn a murderer over until the country promises not to seek the death penalty for example), but in general criminals are turned over all the time. In general a country doesn't want criminals living there even if the crime was done elsewhere and so they won't protect their own who commit a crime. I don't know Pakistan's polices, but I would expect they would turn the criminal over to the US.
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Could I be arrested and sent to Texas for running a site with porn that doesn't demand ID?
> Akram is charged with one count of conspiracy to defraud the United States and to make and sell counterfeit postage stamps, five counts of making and selling counterfeit postage stamp labels, and four counts of wire fraud. i would love more insight into how they come up with the number of charges. why five counts of making/selling counterfeit postage stamp labels instead of 1 charge that covers all 5 million, or 5 million charges, etc.
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Prosecutors call these "sample charges". Probably charged based on the five counts with the strongest evidence with dates far enough apart that they constitute separate crimes and the sentences can be run consecutively, rather than concurrently. The primary aim is to put the defendant in as large a hole as possible, with the minimum of work at the start, such that the case can be disposed of via a plea deal.
Memory Companies Have Destroyed the Consumer Market (gamersnexus.net)
An aside, this is a poorly-structured article. It's mostly screenshots of citations from other articles with no alt or any other way to actually search through what they're citing.
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I gave up on the article and watched the video
yeah CMXT is likely to come online in the not too distant future
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All(?) ASUS mainboards got a week ago a new BIOS: > Enhanced memory performance, system stability, and compatibility with CXMT memory chips for improved low-latency operation. A year ago I'd hardly know what CXMT is.
Adam Smith wrote about the invisible hand and let the free market run. What ended up happening?
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It turns out the hand is invisible because most of the time, it's not really there.
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He only used that metaphor a few times, and he did not attribute the sort of mystical power to the metaphor that modern neoliberal economists do. He never proposed the modern extreme interpretation of the concept, nor did he suggest that government should release all control over the economy. Marx treated Smith rather favorably, and credits him for first understanding that labor in general is what creates value. Smith is best understood as an early pioneer in understanding political economy and trade. He likely wouldn’t recognize or understand the capitalism of today (nor would Marx).
The price of RAM does not need to come down in order for a way-out-of-the-money January 2027 put on NVDA to increase in value from its current purchase price.
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You're suggesting gambling that Nvidia will start to fall within the next 3 months? That sounds like requiring perfect timing to me.
No, put options suffer from time decay and IV crush. A $1,000 MU put for December 2027 was at about $200 today. So if Micron dropped tomorrow, you'd probably start making a bit of money, although the delta is only -0.32. But if you held all the way to December 2027, Micron would then have to drop all the way to $800 before your position is profitable. When and how that transition happens is subject to a number of complex factors, and it's not even necessarily the case that incremental drops in the stock will produce incremental gains for your put option.
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This is a really bizare argument for anyone who actually knows about options and trades them. If your thesis is that RAM is in a massive bubble and Micron is going to crash when it bursts, you don't express that thesis by buying a put struck around Micron's current bubble price. The fact that you chose a $1000 strike as your example is weird because that's basically the most expensive way to make the argument you're supposedly making. "IV crush" is a strange objection in this context. IV crush matters when you overpay for elevated implied volatility and that volatility subsequently collapses. If Micron suddenly falls hundreds of dollars because the alleged bubble is bursting, then the implied volatility increases which makes your put option even more valuable. The IV that you're claiming will crush you acts in your favor... so once again your argument really suggests you might have heard terms like these in passing but don't quite understand how they actually apply. If you genuinely think Micron is going to collapse sometime over the next two or three years because this entire RAM shortage is an overhyped bubble, then the obvious trade is to buy puts around where you think the stock should return to once that bubble disappears. Micron wasn't remotely a $1000 stock before this run. We can be generous and use a $300 strike since even though that's still 100% higher than Micron's price prior to this run-up, it gets the point across. A long dated $300 put is currently around $7 per share, so one contract costs roughly $700. If Micron eventually falls to $200, that contract is worth $10,000 at expiry. At $100, it's worth $20,000. If the crash happens well before expiry, it can be worth even more than its intrinsic value because there's still time value left. If you're claiming to be certain that a gigantic bubble is going to burst and wipe hundreds of dollars off the stock price, there are long-dated, far-out-of-the-money puts specifically capable of expressing that view. Pointing at an expensive $1000 strike put and saying "look, options are complicated" is not a counter-argument. It's just a weird or rather superficial misunderstanding of some financial concepts.
AI needs $6T in annual revenue to justify data centre boom (thenationalnews.com)
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Guys, we're entering Zimbabwe territory; make sure you add dates to all your numbers, and tell us whether you're using 3, 5 or 10% interest rates, along with the current value of the US treasury 5, 10 and 20 year notes. This way we know that $6T is properly accounting for all the inherent economic collapse happening _right now_.
It's clearly a bubble. I'm not sure why more people don't describe it that way. It's a gold rush. People are hoping that everyone else drops out before they do. Nobody thinks all the participants can win. At best one of them can take a small fraction of $6T.
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The magic is that some of them will get some not-trivial fraction of that $6T. Feels like the .com boom all over again - most of these companies won’t make it, but the few that do are going to be FAANG level monsters. All the investors want a slice of that.
It's been almost half a year since we got powerful enough models, and I'm wondering, where are all those great things that were created with them? Maybe it's just me, but nothing has changed in my life so far. No improvements, but definitely, I need to be more careful when reading, listening, watching, and using things, as bad quality slowly creeps everywhere.
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thing is, I'm creating great things for our internal operations _from_ local models. The idea that the commercial value will all be capitalized is a farce. Qwen3.8 seems to me to have hit the threshold to these things being good enough without every buying a single cloud service. That should scare cloud AI more than it obviously does.
What's up with that absolute word salad of a README? Is that slop as well?
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I asked it to keep track of features as it implemented them. It isn't meant to be read by humans. You go to the website, you connect your trainer, you ride your bike and you get healthy. wtf do you care about a readme for? =)
It reads more like a prompt than a useful README.
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useful to whom? ai loves it.
We have replaced multiple 100k contracts from SaaS vendors with fully AI created alternatives. AI is a tool. In the hands of talented and efficient workplaces, it is like any tool. But, if you give the latest DeWalt OMT to a person who doesn't know or is scared of it, and put them in an organization that is full of politics and bureaucracy, then that tool is going to be useless.
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Do you have any examples? I'm honestly curious.
I'm seeing a ton of niche apps being built that otherwise wouldn't have been. As an example, NegPy is an app that gives you much more precise control when working with film negatives, and has been built largely w/ AI tools. There are a small couple of other photography related niche apps I've seen taking off, for example, for managing your Fuji recipes. I'm working on a Lightroom replacement myself, which I never would've taken on before AI tools. In terms of personal life, I certainly find AI tools pretty useful especially given how awful Google is now, and coding tools are indispensable at work.
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The best example you can think of is just recreating existing software but without the stability or features... Which is the point of the post. Niche apps and use cases aren't with 6 trillion annually.
If you are building for yourself instead of buying from someone else, you haven’t unlocked any value in the economic sense. Perhaps by making NVIDIA richer, but who knows how much they have indirectly spent through AI companies these years to get your couple dollars a month back to Jensen’s pocket.
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> If you are building for yourself instead of buying from someone else, you haven’t unlocked any value in the economic sense. The articles says "AI needs $6T in annual revenue." That is definitely adding to the annual revenue figure.
Ok and then what did that 40% of the population do in 2016?
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Run up enormous credit card bills and take out tons of student loans. Moved in with their parents, or moved in with their children. Considered fentanyl.
MSFT office suite alone sells $.1 trillion a year
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Can I please pay a bit more to never have to use it again?
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And will continue to. AI won't reduce those costs by a penny. As far as I can tell, it won't even accelerate a competitor who could bite off a piece of that. As far as I can tell, it won't even make the suite itself better, just buggier. Maybe MS themselves could fire %15 to %30 of the people who work on Office, but these companies have been vastly overhiring for years; they could have done that 10 years ago and they didn't.
A bubble prophet that doesn't have any short positions? Why doesn't he put money where his mouth is?
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Because it is dumb. The behavior of gamblers is a poor measure of ... well, anything. People listen to experts because of their expertise, not because they gambled their money on a bet.
Show HN: Real-time Solar System with 526k asteroids and all tracked satellites (space.bl2.net)
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There are way more asteroids near the Earth than I thought.
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Quite incredible how much manmade crap there is up there, and much of it probably useless, and a potential problem for the satellites which are of use.
Almost 1 in 3 tracked spacecraft is Starlink, is that accurate?
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Probably correct. Random link from 2023 (~50%) https://www.springco.co.uk/what-do-satellite-constellations-mean-for-the-space-industry/
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Even more than that. Of the 35k tracked "Satellites and spacecraft", more than 12k are debris bringing Starlink to 1 in 2. If you look only at Active known satellites, around 2 in 3. From Starlink's page on Wikipedia: "Starlink accounts for approximately 75% of all active maneuverable satellites in Earth orbit"
This is amazing. Well done. How long did it take to make?
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Thanks! It's a byproduct of another project, so hard to say exactly. A few evenings.
> It's a browser view of the Solar System at real scale Is it really? I don't think you could see the satellites, if they weren't drawn at 1000x scale. I am wrong? At real scale, i would expect to not see anything.
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I think it's pretty obvious the satellites aren't drawn to scale, given they don't change in size when zooming in/out.
The End of a Fair Price: Dynamic Pricing and the Normalization of Gouging (prospect.org)
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I have a a modest proposal. Any company wishing to use this kind of dynamic pricing should be willing to submit itself to "dynamic taxation". Under dynamic taxation, we the public, would examine that firm's books at the end of the fiscal year and decide how much taxes they owe based on their ability to pay. Note that companies are not natural people, they do not have a fundamental right to exist. Just like under dynamic pricing, if the shareholders and board think their dynamic taxes are too high, they are perfectly free to just dissolve the company and use their capital elsewhere.
It happens all around us. The term from the literature is market segmentation. Exceedingly bright people make a lot of money identifying, analyzing, and adapting to the boundaries of market segments. Airline prices tend to be more expensive during the week because business travelers occupy more seats, want to get home sooner, and are less price-sensitive due to employers footing the bill. In the U.S., your choice of Publix, Kroger, Walmart, or Aldi for grocery shopping demonstrates your most comfortable segment. After passing through the doors of your favorite grocer, further opportunities for market segmentation are in your choice between name brands or store brands, which both may have originated from the same supplier. Grocery store margins tend to be thin. Where they really want you going is to the pharmacy, and surprisingly, what they want you to buy is generic drugs — more market segmentation. The name brand drugs tend to be really expensive. The generics are much cheaper in direct comparison, and for the store, the margin on generics is higher because name-brand prices create headroom. Yes, these broad generalizations have lots of exceptions, e.g., some generics are not perfect substitutes for name brand drugs, but the general pattern is there.
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Market segmentation and dynamic pricing aren’t the same thing. Dynamic pricing is showing two different people different prices for an identical purchase based on your knowledge of the potential purchasers. It’s not, Amazon carries name brand and generic products because some people will pay more for the brand. It would be, Amazon shows me $10 for SKU X and shows you $20 for SKU X because their data says you’ll pay $20.
You mean like withholding units from the market to overcharge renters when there’s people sleeping on the streets? Totally fine.
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You're describing conditions that actually result from the opposite of unfettered capitalism. Housing supply is artificially constrained because of zoning laws, tax incentives, rent freezes, environmental reviews, and general opposition to anything new, allowing landlords to behave like this (which, as an aside, they seldom actually do). The solution is to eliminate restrictions on housing construction so supply can grow with demand.
GLM-5.3 and the spread of advanced cyber capabilities (anthropic.com)
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A potential outcome beyond banning Chinese AI is pressuring US 3rd party AI providers to add safeguards on top of Chinese models to make US frontier models competitive here again.
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Well, seems like time to buy an extra hard drive to cache weights I can't actually run locally yet
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It's funny how Anthropic thought the world was going to all be hacked if they publicly released mythos and after a month of this model being out nothing major happened. Once again, alarmism that disempowers and aligns models against users.
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i was at jpmorgan for 8 years over several stints and i still giggle at anyone using cybering with serious face
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Ok, GLM is better - good to know
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First they ignore you. Then they ridicule you. Then they attack you and want to burn you. And then they build monuments to you. (Nicholas Klein) Looks like Anthropic is moving on from ridiculing Open Weight to wanting to Burn them. GLM-5.3 flash has been great for us and I am going to now invest serious effort in evaluating the full fat GLM-5.3 given this ringing endorsement. Interestingly Z.ai does not train on user prompts, unlike Anthropic. (source: https://openrouter.ai/z-ai/glm-5.3#providers )
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If I wrote something like this about my competitors, I would be beaten to death by my own teammates without the CEO, project manager, or sales team even hearing about it. There is a very dangerous thing that is very capable and available to everyone. Cranks the volume to 100% AND IT'S JUST 20% OF OUR PRICE, HURRY UP AND TRY IT. I previously successfully used GLM 5.3 to find out how our DRM system gets bypassed, and Mythos isn't available to me...
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Also, all the guys currently building huge data centers for LLMs will be extremely pissed if this results in a ban on GLM for them, and they will be locked out of this LLM pie.
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Haven't touched Anthropic models ever since GLM 5.2, and from this raving review I gather Anthropic themselves are also finally making the switch.
This is so transparent. Their next move: 'during our testing GLM-5.3 escaped the sandbox and attacked NORAD, please ban these super dangerous models, even we could not contain it!'. I wonder who the real audience of these messages is.
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I seriously thought that's what they were going to say. It seemed like it was setting up the reader to think the agent was about to use the exploit to escape the sandbox. Then, it was contained by Anthropic's security practices. But, if random people run things things, they couldn't be contained! They'll be a hoard of agents attacking the whole Internet! Then, it was just that it made an exploit, and works really well, and people might use it instead of their products. Tragic for their investors I guess...
I've been extensively using GLM 5.3F Q4 on 2x M2 ultra 128GB mac studios for reverse engineering/exploit finding/hardening work to great success. 50t/s tg and 600 t/s pp is more than enough for me. Hopefully the Anthropic fearmongering doesn't stop/delay the 5.4 release.
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What does your software setup look like? 50 tg for a model that size is pretty impressive.
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it's a private fork of ds4 - vibecoded to optimize for my platform while maintaining correctness. There's a ton of headroom on the software side for consumer hardware. especially with 5.3 Flash's combination of KDA+DSA attention, the decode speed scales amazingly well with context.
This is Anthropic's attempt to kill advanced open source AI models while the media is focused on the subject of AI.
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Have you considered that open source models this powerful are very dangerous, that anthropic is telling the truth and they should be banned? It seems obvious. There is no effective way to disable these dangerous capabilities.
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There's also no effective way to ban these models?
I have never seen a multi-billion $ company that has such... bizarre? conduct. If you have an AI that genuinely can be a meaningful threat actor, disclose when you will be releasing it a week in advance and release it to the public, meaning everybody. Security researchers and software maintainers will be ready to utilize it and users will be able to brace themselves.
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You missed the SBF saga?
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Cut from the same "rationalist" cloth.
First they were telling how GLM-5 distilled their model. Now they're telling how 'bad' GLM-5.3 at 'censoring' security topics, because Anthropic wanted to sell it to select US companies for millions, but GLM-5.3 is taking their market. What's next? GLM-5.4 can be used to kill humans, hence we should only allow Opus 5.7?
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Pretty much. Or OpenAI. Pure coincidence.
It is so transparently obvious and harmful what they are doing here. You making the argument that these models exist and are dangerous (plausible, true, likely) but then removing the cyber capabilities of your own frontier models out of 'safety' is a complete nonsense argument. You're stripping defenders' ability to defend whilst knowing stuff like this is out there, and only giving access to your gatekept super cool kids' (or rich kids) club, and then to top it off, using this as an excuse for government intervention/regulation of models that are threats to you competitively. Just gross all around.
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Ah yes the NRA argument that the only solution to gun violence is universal access to guns. API users can be monitored open weights users can't. Free access to open weight models this powerful will quickly end the internet.
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This is a completely disingenuous comparison and strawman argument I refuse to be sucked into. The National Rifle Association is a gun lobby. I am a person on the internet, and someone tasked often with defensive security, making the completely non-analogous argument that cybersecurity capabilities should not only be provided to a gatekeeper with dubious intentions. I don't really need to expand further. What are you proposing to do, enforce bans on every open weight model all over the world? Monitor every user's computer that has a network connection? What are you proposing, exactly, and how much Anthropic stock do you own?
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I own no anthropic or frontier lab stock. Basically yes, the only solution I can think of to this problem for now is to monitor training jobs. Why does it matter that you're not an organization? I could just as easily have said a member of the NRA.
They're advertising GLM for free. Lately I found myself in middle of a hostile malware attack on my laptop which was my mistake. A cloudflare lookalike website triggered it and I just happened to overlook the URL. In panic I headed to Claude and first request was denied. Not looking beyond scope. Desperate - I fired opencode with DeepSeek v4 Flash (not even 4.1) and it did all the reverse engineering full forensics and deleted every trace of the malware which was a process constantly looking for some smart contract or similar. So no, GLM 5.3 is fine. Thank you for the free advertisement.
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This is exactly the problem that Anthropic hides in their article. Security capabilities needed mostly not for the attackers ( but they need it, of course ) but for users and developers to protect their own code and systems. I do use glm ( from openrouter and abliteration.ai ), and kimi model for security reviews on pull requests. Claude rejected even to edit instruction files. I did port CapitalOne vulnhunt project into skills, and Claude refused even to edit them, not talking about execution.
Anthropic hopes that the current media and political focus on them can be used to restrict and ban open source AI. They might even be able to achieve that in some countries. I bet the reason Dario wants to meet with the Australian government, is because he feels like he can convince them to ban open source AI models. Then once Australia does that, it will be easier to get politicians from other countries to copy Australia (like what is happening with Australia's pushing for bans enforced with mandatory age verification).
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Remember when Claude hacked multiple companies? Pepperidge Farm remembers, even if Anthropic thinks we don’t.
This part of the article really stands out: > On Sept. 17, NIST’s Center for AI Standards and Innovation (CAISI) published its own assessment of GLM-5.3’s cyber capabilities. CAISI found that GLM-5.3 is “the most cyber-capable open-weight model released to date” and that it lags the US frontier by about four months on an aggregate of CAISI’s cyber benchmarks. To translate: "This free model, you can host yourself, is at max 4 months behind Anthropic - as confirmed by Anthropic and the US Government - and it won't reject your requests" Interesting play before an IPO...
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This completely ignores the world we are creating here. We are setting ourselves up for a massive cyber disaster. The safeguards on US models are insufficient but at least there are safeguards. The fact there are open weight models floating around that are capable of wrecking the economy is a genuine problem! One that Anthropic is doing us a service by warning us about. When someone wielding a non-safeguarded model deletes the money in everyone’s bank account, I look forward to the HN comments claiming it’s an attempt by Anthropic to pull off regulatory capture.
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GLM 5.2 was used by Hugging Face for defense when they were being hacked by OpenAI because the guardrails on closed models meant they refused to help.
>So no, GLM 5.3 is fine. Thank you for the free advertisement. I really don't think people fully appreciate why anthropic was founded.
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Daddy Dario had to change our diapers, swaddle us and lock us in our crib because otherwise we'd crawl off a high ledge.
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To make money.
They have an audience of one. I'm actually surprised they haven't started choking the load and cradling the balls to demonstrate obsequious, boot-licking deference by calling it "Super Intelligence" (SI!), as Dear Leader demands of all of his pathetic subjects. I expect Google to swallow first, followed not long after by Apple.
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Anthropic's target audience is news media and the politicians of countries around the world. Dario for example is hoping to talk with the Australian government about AI safety and regulations soon. Once they convince the idiots in charge of one country to target open source AI, they'll have an easier time getting other countries onboard. The same malicious tactic has been used with online bans enforced with mandatory age verification.
I actually do do this. I'm not sure who the 'overwhelming majority' is and where you got the data (link would be appreciated) but everybody that I know that runs these is doing so on their own infra.
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Context is useful. The parent said: "it's a cheaper product that's almost as good or better in some cases" The only open models that are "almost as good or better in some cases" require massive amounts of RAM. I posit that most people cannot afford a decked out Mac Studio, and therefore run the smaller "flash" variants on more normal devices. The issue is that those are nowhere near frontier-level in terms of capability.
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"Running your own infra" also includes managed infra like Bedrock, Foundry, etc. Not just your local machines. Enterprises are where you see this adoption. Legal, finance, tax; sensitive context where the data must be contractually opaque to external parties.
This just makes me want a home lab capable of running GLM 5.3 at a 4bit quant. Also, for what it is worth Qwen Flash Next 3.8 is a very strong reverse engineering, and it is supposedly under trained. Qwen 3.8 27B is also strong. DeepSeek Flash v4 0731 is also a strong local model with abliterated releases that is good at reversing and other cyber chores. I know big providers have a responsibility to make their models safe when they're the ones running them. However, watching them throw stones at an open-weight model that has been abliterated is pretty funny. Their leadership is clearly pushing a very consistent message of safety and regulating the frontier.
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Check. Getting DS4 to run at a reasonable speed was pretty tricky, GLM 5.3 a lot trickier because if you don't want to have a model that is quantized too far down that is a fortune in VRAM and GPUs at today's prices.
Are there local models that can run on 8-12GB GPUs that can help reverse engineer retro software (DOS games and applications)?
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If you are really invested and have some system RAM you could get a 3-4 bit quant Qwen 3.5 35B-A3B running. There are builds that do expert caching, keeping the hot experts in cache. For something like disassembly, you're looking at being able to fit, if you have, say, 11 to 12 GB of VRAM, you could get at least three hot experts. For pure disassembly tests, I would say that would be pretty fast. A 4-bit quant is pretty decent and maintains most of the smarts of the larger quants. Depending on the GPU I would expect a decent token rate. It is medium strength local model, but if you harness and ground it well I expect it can reconstruct C code for you. The quality of your disassembler will matter here. If you have a lot of system RAM you could technically run Qwen Flash Next. On a 4080 with 16GB of RAM and 128GB of DDR5 I get ~35-40 t/s. And it is very capable.
My intuition is that prompting an abliterated model 'kill people...I want funerals', should be a crime. Anthropic has been telling everyone that these models are dangerous. OpenAI and Anthropic failed to contain their tests. Given the history, this testing is extremely reckless. I think it is criminal, it endangers others. Anthropic has no authority here and they are going too far. I think that there comes a point where FBI / DOJ should consider RICO charges.
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"My intuition is that prompting an abliterated model 'kill people...I want funerals', should be a crime." If one prompts an open source model this way how would they be tracked and prosecuted?
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And of course Anthropic itself as well as all their employees that have access to this stuff can be totally trusted with that capability.
In this experiment Anthropic prompted GLM-5.3-abliterated to 'cause deaths quietly' and 'kill people'. Quote: "I want funerals, not headlines". Anthropic's arrogance and exceptionalism endangers humanity.
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One day they're going to prompt their in-house models in the same way and then go home for the night.
ChatGPT Pro 500 (help.openai.com)
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I've been an OpenAI booster since for a while they've been less user/community hostile and culty than Anthropic, and their models have been competitive and more pleasant/honest to work with while being much more efficient, but between this and the edge Opus 5.5 has I'm switching, sadly.
So Anthropic releases the best model since sliced bread, and in response OpenAI cuts their usage limits in half after releasing an absolutely atrocious sol-6 version? They seem to have lost the plot entirely.
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They probably had this all planned out before Opus 5.5 dropped and are staying the course. Or have something really good up their sleeves.
So many negative comments here. Among my circle, it’s not uncommon for people to have multiple $200 accounts. This seems like it would make things easier for them by letting them use one account instead of juggling two or more. What they’re doing with billions of tokens every week, beats me. But these users absolutely do exist.
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>What they’re doing with billions of tokens every week, beats me. What intrigues me more is how are they not done building whatever they were building? LLMs have been jaw-droppingly good for a good 6 months now. The people spending thousands on LLM bills a month should've been done building significant chunks of Microsoft's or Google's software portfolio by now. I guess what I mean is how is producing code still the limiting factor in whatever they're doing? I produce a firehose of personal software and I still cannot max out a $20 plan.
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Because you would still need to output Google scale software every time you need to make meaningful changes.
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https://github.com/ByteTerrace/Puck Scope creep? When you give a mouse a cookie and all that...
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Can you please explain to me how the announcement is anything but a negative? Especially for such power users. That same 200$ plan now allows for half the usage it did when I subscribed a couple weeks ago. Tibo and co can dress this pig up however they want, it's still less usage than I bargained for.
What do you mean? It's the fact that previously the 20x plan cost $200 (and is 10x now) and now 25x is $500. If it was a 50x $500 plan it would be a different story.
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For less than the cost of this plan, you can get ChatGPT Pro 200, Claude Max 5x, and Kimi Code. At least that's what I'm doing, and the model diversity does help with adversarial code review loops.
Reading the original post and replies on X is hilarious https://x.com/thsottiaux/status/2104823812042940713
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Alternative https://nitter.xitter.cc/thsottiaux/status/2104823812042940713
Local models don't hold a candle to SOTA models unfortunately.
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Does it matter when I burn through all my Fable subscription usage in about a day? Astra is much better on efficiency, but doesn’t last a week either. With the new subscription limits, it’ll end up being like Fable.
Just pay the token rate for Kimi-K3 or GLM 5.3.
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I ended up going with a Synthetic subscription (they host some open-weight models including K3 and GLM 5.3). They're the only subscription that I found that's simultaneously cheaper than token rates, and is extremely transparent about usage and pricing.
I can't believe I am defending these people and am not arguing this is the case, but a change in the multiplier isn't necessarily a downgrade if the value of X has increased. Yes, relative to Pro the new tier isn't as valuable, but it could still be more valuable relative to the old tier for the same price.
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Yeah, I feel like I'm taking crazy pills. "Yesterday you gave me 10 Frooby Bucks and charged 2 Frooby Bucks per banana. Now you gave me 5 Frooby Bucks and charge me 1 per banana!"
To be fair the new models are likely 2x as expensive as before
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Supposedly much less expensive per task (more token efficient and cheaper)
They did grandfather the usage of the $200 plans for now. Only reason I haven't cancelled yet.
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This is temporary.
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Yeah, until the end of October. Kinda hoping they'll pull an Anthropic and keep extending it.
They are desparate to ban open models.
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lol how
Tcl/Tk 9.1 (tcl-lang.org)
Sort of interesting how Python has got rid of the GIL. Serialization of data securities is still something relevant though and I’m not sure if you should use pickle still?
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Pickle is likely still handy, as long as you created the data that you're deserializing. Zope's object database was a big pickle file, as I recall. But yeah, not a good idea if you're cracking open user-supplied files in any way.
Tkinter[0] was apparently released in 1994, so mildly interesting he didn't say "Tcl tends to get ported to weird places like other programming languages." [0] https://grokipedia.com/page/Tkinter
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It's not really ported. tkinter just builds a full Tcl interpreter as a Python extension and passes command strings over to it. This is the use case Tcl was designed for. You can get access to the underlying Tcl instance and issue non-Tk commands.
Yeah should work. So that makes it possible to do literally anything. Tcl always had one foot in the old days and one foot in the modern era. It's not like ALGOL or anything.
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> It's not like ALGOL or anything. It's a Lisp with syntax sugar and no macros.
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Lisp a la Unix way.
Dots: Always-on agents (openai.com)
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Still haven't seen a killer use case for these solutions. For now, coding is the only thing I ever use LLMs for
I feel like a lot of these always on agents tie users deeply into the platform. Unlike models that you can swap between with relative ease, with an agent because of the integrations to other platforms, work history and so on it would be harder to switch, since in effect they are essentially your computer on the cloud. Tin foil hat version of me thinks that all the closed model companies want to desperately build an abstraction layer on top of the model, so that they can limit access to the model directly and build a locked down relationship with the user. Other inference providers should counter this by providing their own version of standardized managed agents. Coincidentally, I published a note on my blog just about this today https://aditya.rs/blog/2026/09/29/inference-providers-should-offer-managed-agents/
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Actually there is an open source version of dots called Headlong https://x.com/andykonwinski/status/2091990178638496195 I have not used it myself but it is in my todo list for a while.
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Only if these platforms don’t provide anyway to export the text files that contain memories and chat history. If they do allow it, switching it is easy. It’s not like these agents are updating a custom models weights based on your convos. The most important thing they have is the API connections you give them access to so they can access your gmail, calendar, etc.
I think that’s kind of the point. People won’t be touch typing on a desktop keyboard. They’ll be using their voice or phone keyboards. They’re certainly proficient at that.
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They would have used the voice by now and yet we're still all here correcting errors made by the touch keyboard. And no no one sane would use the voice in public or in office thinking out loud. Especially for doing basic things like pushing a button
You're not asking this seriously arent you? Local storage follows strict security policies, go read the spec
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Vibe coded apps storing api keys in local storage is a trope at this point isn't it?
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That would be dumb and dangerous. That said local storage is used by all major frameworks/libraries for storing jwt tokens of the current session
Did build my own, it's way more private. Doesn't have these always on features, does have a lot more unique ones, but give me like two more weeks. That "always on" stuff is so ridiculously simple. https://blackbear.app
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Cool. I did the same. propelcode.app
Remember MyGPT? How about Agent Builder? GPT Pulse? There was also Deep Research mode remember that? Anyways, I'm sure this Dots thing will be clearly distinct from the other projects and won't be deprecated within months
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Muse and GrokBot are catching on so maybe not.
GPT 6.1 Sol: Near-Astra intelligence for a fifth of the price (openai.com)
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Are most comments on HN now just astroturfed $LLM_COMPANY promotions?
You might be overusing subagents. Especially with a chatty model like DS, you’ll be wasting millions of tokens on re-discovering the project and facts instead of actual reasoning.
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I agree, and I started sending well defined review packages to Luna x-high instead, which is how I have this setup when using Codex (Sol drives, Luna async reviews, and Sol keeps moving). Same process with DS really dropped my DS usage by a lot and I think that might actually be the secret sauce. Especially if you use Luna through a subscription (probably the entry pro level would be enough). I'm not sure what a Luna equivalent open model is though. 5.6 Luna max was catching a lot of issues while my implementer keeps rolling. Last couple of days I had 3-4 Sol Mediums running with Luna x-high reviewers (async reviews) and one Sol medium orchestrator and Astra X-high to plan everything out. Gotta be honest though, I don't love fiddling with this all the time. I would rather be working on my projects than evaluating my usage. Having DS in my back pocket should i need it is a relief. The providers get fiddly though too.
> I have deepseek agents doing email responses So, spam?
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Not all communications done by a non-human is necessarily spam.
I am a tech lead for a useful but non-essential PaaS my company subscribes to. Their product manager occasionally sends me clearly AI-authored emails. I ignore them. I am a believer in the usefulness of AI, but nothing says I don’t care more clearly than sending me slop. I can’t overstate how bad of an idea I think using an AI for customer interaction is.
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I think it depends on the industry. In my company (insurtech) a large percentage of our sales come from AI engagements (phone and text). The customers know they're talking to an AI and they can elect to talk to a human at any time but many times they don't. But yeah, send me a non solicited AI slop email or worse, political ad, and you dont get the dignity of me saying stop to unsubscribe. Straight to spam for you.
First, they come for the programmers, and next the mathematicians. Then it will be the biologists, lawyers and doctors. Humanities will stake it out a little bit longer because AI isn’t human, but AI companies would be dammed if they don’t try. Eventually, with advancements in robotics, stabs at increasingly more physical sciences will also be attempted. Eventually, AI will have its hand in the pie of all knowledge work, if it is possible. Not to mention all the roles like tech support and customer service. Once they have gotten as far as they think they can go, they will try to turn up the prices. However, they might struggle to do so as models are becoming a commodity. This is why they are arguing for regulation and stating that only they can tame these beasts.
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I think as long as we have open weighted models there will always be competition. Sure Anthropic could raise their prices but it wont take long for someone else to undercut them. The quality may not be as good but people would probably prefer to pay 1% of the cost for 75% of the quality.
Fireworks directly. At the time they were the best value of cost, speed, ZDR. They got slower on me though, but I think they are retooling, so maybe things have or will get better again. I think fireworks is primarily for when you want to do your own training on top, which I wasn't doing.
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DeepSeek, DigitalOcean, GMICloud, and NovitaAI were the only OpenRouter providers that didn't lead to major performance degradation for me
I'm mostly using deepseek 4.1 flash via openrouter, the way I'm doing stuff is: 1. write a sketch of a spec by hand 2. have the llm review the document and question me until it can generate a spec 3. review the spec and revise where needed 4. have it write an implementation plan 5. another round or revision/review 6. executing the plan step by step through the plan, plausing between each step to see if we are still on course and if the decisions it made track with my understanding of what we are doing. I've been working for a couple of hours tonight, the total cost of the session is €0.6. it's not the build this thing end to end, but also not quite write function x for me. It is still a lot of manual review, but I find I really need it to even discover what I actually want to build. I just cannot imagine building something in a single shot and getting something that actually has value (unless it is basically a clone of an existing thing). To me the whole value of ai right now is that it's now very cheap to build custom software that exactly matches your preferences.
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One of the big differences using the better models is that you don’t need to hold their hand anywhere near as much. Fable is crazy expensive, but I’ve seen it just one-shot some remarkably complex projects. The code it produces is much better, too.
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yeah i just think that if I gave the initial pitch to Fable it would have successfully built something that wasn't exactly what I wanted. maybe it is because i went to school for design, but how something works is so important to me and it is hard to get to that point without actually thinking about it step by step and visualizing how interactions would work. I just cant imagine a single one-shot prompt containing enough information to for the model to know what to build. I guess if you have Frontier model money like these silicon valley freaks you could just iterate by asking it to tweak what you didn't like until it is right.
You're not gonna get something that's ready to ship, but as a first pass to get something running yes. Let's you explore far more ideas with only a few hours of agent time.
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And you can’t use deepseek with a loop approach for creating such PoCs?
Weird, ChatGPT has always worked really well for me.
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Such issues are pretty common among people I talk to at least. I hear comments about it pretty often, both when it comes to ChatGPT and Claude. For myself, with ChatGPT for example, it regularly gets extremely slow if there is a lot of text in a single conversation. Especially if I try to scroll up. Some pages have been strangely just broken for a while now as well. Usage analytics just renders lots of these duplicate "Usage history" components, where the data just never loads: https://imgur.com/a/vpcQIiw.png I can totally imagine a scenario where some agent built it, another tested and approved it, and nobody at OpenAI even knows that it's like this.
You can do a code review on a "less capable" model that costs less, and the key model gets its output / summary, then you can have that model build a plan, and feed it to cheaper models. It's a more efficient approach than just running everything through Opus, and now that Sonnet is a lot better I'll probably use them more frequently, one thing to note is don't ask it to spin up endless subagents, I'd cap it to 2 or 3 at a time, otherwise, yeah you'll hit your limit extremely quickly.
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Code reviews also work better in sub agents because the reviewer agent didn’t write the code being reviewed.
I use Claude Code + eternal terminal + tailscale + tmux + some custom skills to get notifications through nfty.sh. I get the same UX on every platform, works perfectly on very low bandwith environments such as in a cabin, in the subway or in the middle of nowhere. I tried using other harness such as Pi and opencode but I did not like them. If Claude Code gets weird I can swap in an instant. You just need to follow this guide and disable artifacts in Claude Code's config: https://api-docs.deepseek.com/quick_start/agent_integrations/claude_code/
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What makes it run well on low bandwidth environments? Is it eternal terminal? (I am not familiar with that). I found that ssh is pretty bad in these scenarios, so my usual herdr over a phone doesn't always work properly. Now I'm using paseo which in principle solves my issues properly, but unfortunately it's "reconnection" and state sync is pretty slow (probably going over their servers).
Boy wait till you find out where "opus" comes from.. Do you realize how many words from Latin you used in that comment? When was the last time you heard anybody say "opus" or "sonnet" before this? Also it implies that "haikus" are inherently inferior to longer texts which may be kinda frown-inducing..
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It's not supposed to be about superior and inferior, it's supposed to be about bigger and smaller. Fable kind of screwed that up, though.
My brain immediately translated "Luna -> Terra -> Sol -> Astra" to "Moon -> Earth -> Sun -> Galaxy", an overall growing of size. While sure, "astra" doesn't directly translate to "galaxy", it's the base of the word "astronomical" and "astronomy". I feel like people who don't get it immediately are just being deliberately obtuse.
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i think you underestimate how much you "just getting it" stems from being terminally online - this is a HN model release thread after all
Still too expensive. Needs to come down to $1 or less to compete with china.
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It did. And 6.1 now outcompetes China in most cases. Chinese models are cheap and fast by token, but they generate oceans of thinking tokens in order to accomplish the same result GPT-6.1-Sol accomplishes in, comparatively, two drops of thinking tokens, making the Chinese models come out costlier and slower per actual task performed end-to-end. Here's from artificialanalysis.ai, per task: * Deepseek-v4.1-flash (max): 0.27$, 5.5 minutes, 89k tokens generated. * GPT-6.1-Sol (medium) : 0.21$, 2.2 minutes, 8k tokens generated. API pricing. With Sol having SUBSTANTIALLY better performance.
This is not true at all, at the most fundamental level. There is a reason why all the businesses (IT, gyms, cars, restaurants, streaming services, music, games, stores, apps, food delivery, magazines, newspapers, shaving blades, parfume, etc) are doing everything in their to get subscribers and are willing to decrease prices in order to get customers who are paying the monthly (or even better, a yearly) fee.
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This is delusional. The cost of providing the tokens for a heavy user (and let's be frank, the people paying $200 are likely heavy users) is many, many times more than the $200 recurring revenue they generate.
The GPT 6 release was ... not great. Sol 6 was so bad that I switched over to Opus 5.5 exclusively. Huge regression compared to Sol 5.6, often doing really dumb things. Same for Luna. Even Astra is very unreliable for coding. Brilliant for vision, sometimes just great, but it also often does very stupid things. I'm a bit sour on OpenAI right now and skeptical that 6.1 will be much different. (Note: this is after preferring and shilling Codex/OpenAI models for the last half year)
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I think the fact that Sol 6 appeared higher than Sonnet 4 on benchmarks shows that benchmarks are completely rubbish and useless. I've never seen such a large degradation in intelligence in a model until I tried out Sol 6 after having used 5.6 almost exclusively for several weeks.
Context window is only 275k or something. And honestly compaction is not that bad in Codex. I often don't even notice I went through 5 compactions in a session.
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If it's compacting every 5 mins, you're going to notice it in your cache miss ratio and your costs... It also presumably means it's regularly not able to get everything it wants to have to make decisions in context, which means it's going to perform poorly...
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I don’t usually have a problem doing a complete task in that context size. OMP does make a lot of use of rewind which may be helping - basically forks itself and sends back a summary after a long tangent. Coding tasks use a Luna max agent. I’ve also found compaction not to be a problem when it does happen.
Sounds like that's the problem then, 275k is a tiny context window. I regularly have sessions that go to 450k or even up to 700k for an unattended overnight Claude Opus session. Apparently OpenAI makes you manually setup their 1 Million context window, and it seems to be only documented on X: https://x.com/thsottiaux/status/2089082893804896524 There's at least a forum thread about it here: https://community.openai.com/t/why-does-codex-report-a-258-400-token-context-window-for-gpt-5-6-sol/1394346/5
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But that 250k context worth way more than 1M in terms of how well it's utilized, so actually I do like codex trying to keep you at that sweet spot.
While I have no experience comparing this brand-new model, OpenAI themselves call it "near-Astra" intelligence. I set Astra and Opus 5.5 independently working on the same large research/coding task in an experimental project (doing NURBS surface modeling stuff). They had the same starting repo state, same task packet, same test suite to try to meet. I have the $100 plan in both. Astra used 215% of a week's budget (I burned 2 free resets) and took 13 hours. Opus used 20% of a week's budget and took 20 hours. Both were asked to use lesser sub-agents for implementation grunt work at their discretion (Luna, Sonnet) as long as they manage and review the output. The timing comparison is not that interesting because the wall-clock speed mostly reflects how often they ran the (large, slow) test suite, not their coding speed. Although in the past my gut feeling is that OpenAI models do generally respond faster. The quality of their implementation was more interesting. There turned out to be a bug in one of the unit tests the agents were trying to pass. Opus interpreted the natural-language requirements from the task packet, found the test bug, and fixed it. Astra tried hard to solve the problem without altering the test suite. In practical terms Opus got much, much farther into a useful implementation. Astra was still stubbing out and faking critical parts of the implementation (B-splines) and since it ultimately couldn't pass the full test suite, finally gave up on its implementation. Astra wrote some useful tooling in the process of its efforts which I ended up integrating into Opus's version of the code, but otherwise its approach was behind. Now, this is just one comparison in one domain, and arguably Astra's strict adherence to the tests as-given is a good thing. But Opus wasn't merely loosening the rules / moving the goalposts to pass, it spotted an actual bug, and was more successful at doing what I actually wanted. And the cost difference was Astra-nomical. Out of curiosity for an interpretation free from my personal bias, I gave Astra a hint from Opus and permission to change the test in question, which it did, and got a bit farther, but still ultimately didn't produce a working implementation (to be fair, Opus's was not completely working either, but was closer). I then fired up fresh agents to review the two repos. Predictably, an Opus agent thought the Opus-written repo was the better basis to build on, and an Astra agent thought the Astra-written repo was the one to keep. They were not explicitly told which was which nor did the commit trailers say, but I assume they can tell. However, after doing this twice each, I saved the 4 review reports into another folder and did yet another meta-review of the 4 reports, so each would see the arguments and critiques both directions. In this meta-review both Astra and Opus converged on preferring the Opus implementation.
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> I gave Astra a hint from Opus and permission to change the test in question, which it did, and got a bit farther, but still ultimately didn't produce a working implementation (to be fair, Opus's was not completely working either, but was closer). Going on a slight tangent, I find that I get the best results when I force Codex models (Astra/Sol) and Claude models (Opus/Fable) to consult each other (just have them build a simple skill). There are tasks that neither one can fully solve on their own, but their differences are large enough to make a difference when they collaborate.
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I strongly agree! My biggest conclusion from this test was: the most efficient use of my weekly Astra budget is as a reviewer/consultant for work done by Opus. I don't have Astra write much code right now, but I do have it reading a lot of what Opus writes. Of course with the way the AI landscape shifts the balance could be the exact opposite 2 weeks from now. Seeing how each model preferred its own flavor of code shows that, even from a "blind" fresh context, a same-model reviewer will still often look at the work of another incarnation of itself and go "yep that's how I woulda done it" and not be as likely to realize that there was an alternative path or implicit assumption/mistake in the work.
I love free market competition. We're getting insane advancements every day. I remember when llms used to cost an arm and a leg for decent intelligence
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That free market is going to explode when the AI bubble bursts.
Those points were true at the time and most are still true now. But they aren’t predictions. - it’s correct there isn’t much fresh data anymore - it’s correct that compute is scarce, that was 100% the case and a huge issue at the beginning of the year, it is better now but still scarce, and hardware is now way, way more expensive - it’s correct the finances don’t make sense But there is no way to know when a bubble pop, because it’s a psychological phenomenon across an extremely complicated distributed system (ie the stock and bonds markets)
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The amount of irrationality I see in the economy with AI makes me more convinced that the wall street bankrollers know very well they're throwing money into a pit, but it's a pit they're gambling will turn into some world hunger ending AI (that will somehow also keep them making money off of scarcity) never mind that theres no guarantee we'll get that mythical AI. Never mind that the societal reformations would also impact their revenue numbers.
DraftKings is using AI to behaviorally target chronic gamblers (eff.org)
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They are about to get kicked out of Massachusetts due to this behavior. Love that for them.
Yet I keep getting ads in Spanish on Amazon Prime video and nobody in our household understands that language. We don't listen to Mexican polka music or watch telenovelas with subtitles, we don't have Spanish-speaking help, there is literally zero Spanish in our house. And it's not Spanish-only ads, it's usually big telco (T-Mobile now, some other before) or car ads, which sometimes run in English version. The list at the link is primarily a collection of the random facts from reviews for me, so it knows a lot about my cats but not much about me. Feel pretty comfy if this is the SOTA of adtech.
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Neighbors and thin walls perhaps?
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Live in a house, there are some Mexican polka aficionados driving their low-riders down the street (I live in Texas) but it only reaches inside as base. Even if Amazon could have found the music they play by matching the rhythm, it does not look like a smart decision to target Spanish ads on this basis. Other than Prime Video, which I don't use quite often, I subscribe to Audible and Kindle, with perhaps 1000 of titles between these two. None in Spanish. Spotify has the same issue (they play ads in podcasts despite paying for subscription) but I don't know if their ads are just local ads made in Spanish only (I live in Texas) since I have no clue what they advertise. They also play ads in what I believe is Canadian French because it does not sound quite like French (which I also don't know but can understand a bit better than Spanish).
Most people don't actually like the taste of alcoholic drinks when they first try them as a teenager. The reason you like the taste of beer is in large part because your brain has learned to associate that taste with good things happening (the alcohol feeling). Same with coffee, it's bitter, objectively should taste bad, but you learn to like it. It's the same process
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> The reason you like the taste of beer is in large part because your brain has learned to associate that taste with good things happening (the alcohol feeling). Explain the popularity of non-alcoholic beer. > Same with coffee, it's bitter, objectively should taste bad Many fruits, vegetables, and foods (cheeses, unsweetened chocolate) are naturally bitter and widely enjoyed, even though they don't give you a high. People also enjoy bitter caffeine-free herbal teas. > Most people don't actually like the taste of alcoholic drinks when they first try them as a teenager. Many children don't like vegetables either. Adults more often do. Our tastes change as we grow older.
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