Above GLM 5.3, nice! That is a very capable model. I do wish that we will see some smaller "flash" models again though - running this one locally is tough (very costly).
Cant you run it on a pair of DGX spark? Sure it's expensive now, but at the initial retail price that was what, 8k in hardware? Not exactly unachievable
By next year we will likely see GLM 5.3 level performance in Qwen 4 MoE models that can run on most higher end consumer systems.
I don't think there is a reason to care about any of it, just get a few dollars on a few openrouter or similar platforms and just use the models for now, wait for cheaper models that are good enough for you to become available for your hardware.
Sure you might never see frontier performance on consumer hardware but do you really need that though? Does anyone? And if you ever do just get a 30-day sub for that work, and cancel it.
Yeah performance at a given compute budget will likely continue to improve.
We are running Qwen 3.8 27B FP8 with 4x 5060 16gb as the office for a small development team. It is doing pretty well for implementing backend and frontend tasks, and is already useful. In 6 and 12 months from how I expect it to get even better. Some planning is still done with a stronger model, but even that is maybe not strictly necessary.
Qwen 3.8 wasn't that nice in my experience Qwen series has lagged a lot but I think Qwen 4 would be better they cleaned up the architecture.
And we are likely to see many companies start building 27-32B MoE models custom built for use cases now that Rubin is going to make training costs much lower.
I expect training costs to get under 100k USD within a year for small models with another 100k maybe for RL.
I think just having all your own data from claude and stuff on your system that you can feed these models and have companies offer great base 27B models will be how it works.
Hilarious sentence: "DeepSeek-V4.1-Flash-1017 is a minor update to DeepSeek-V4.1-Flash, delivering substantial improvements across reasoning, coding, agentic tasks, and visual benchmarks." (emphasis mine)
I happen to live in China now and lots of my friends work in frontier labs. I don't now there's a restriction for major updates of LLMs.
Western media doesn't have correct informtion source about China. This is because Western favors Web ecosystem and most inforamtion live in the Web, but in China everyone use Apps.
It's a bit refreshing to read updates from an AI lab without bullshit doomerism and overwhelming sense of self-importance from shit like OpenAI and Claude.
To me this implies they continued the training run for 4.1 and it improved. A 4.2 would imply they changed something about how it’s trained/how inference works, and a 5.0 would be a major update (who knows what would have changed).
BTW who would have thought China would be the champion of freedom and opensource in the AI arena, while US is fighting for corporate/government control.
There are different types of freedom and China's bet is that as long as they provide enough economic freedom the public will be ok with somewhat restricted social and political one.
Yeah, I had a somewhat odd conversation with a Chinese acquaintance last year when she got to talking about how America sees China. Her point was that, "How am I not free? I can do whatever I want, go where I want, buy what I want. I can talk to you and say whatever I want; nobody is here listening to me."
The fact that she can't call Xi "Winnie the Pooh" on Douyin wasn't something that occurred to her, or maybe that she was aware of at all. I didn't ask. I don't like to get into these discussions when I'm in China.
There is no such thing as “free speech” anywhere. It’s all a spectrum and the Americans in particular are indoctrinated. It’s a red herring to distract from the real social issues. People in America have some of the worst healthcare in the world. But hey at least we have “free speech”.
Fixing healthcare or economic policies is typically an act of congress type of thing - not even an amendment. Large popular support - and it can be fixed. Fixing freedom of speech or the ability to vote at all - once it is gone - usually takes a price payed in blood. Sometimes rivers of it.
Citizens of Palm Beach county cannot voice their opposition to how their tax dollars are being spent. They rightly want that money to be invested locally, instead the County uses it to invest $1B in Israeli bonds, something that people widely oppose.
They first said that it's a budget meeting and Israeli bonds are a "policy matter". Then they started arresting people for speaking out against it. Then they started arresting anyone who applauded.
"Free speech" -> I spit on American "free speech". It's the most insidious and dishonest thing. At least the CCP doesn't PRETEND to give people rights that they simply don't have.
> The fact that she can't call Xi "Winnie the Pooh" on Douyin
Actually she can do this. There's plenty of such videos on Douyin ... If you clicked such videos frequently, algo will recommend a lot of them to you.
The worst case of uploading such videos is an aaccount ban (but very rare). So yes the freedom of speech here is fewer than in the U.S., but it's not like you'll be put into jail if you say sth about the president.
Presumably. The current opencode slug for the model is just 'deepseek-flash' suggesting they will just update that one going forward, not keeping versions in parallel.
It passed my threshold for not caring to try new models back with DS4, I use it for literally everything. Announcements of new models in the series always feel curious, because it doesn't really feel like there's much left to fix that would improve on what's already there for any task I know of.
It's a bit like obsessing over patch releases of some software after a major upgrade already solved the original problem long ago.
I have quite the opposite experience: I can do any concrete coding change with any model, but the intelligence limit just doesn't go through more complex debugging examples.
And then when I try a smart model, like Astra medium and it solves it (I had a firmware bug in my new laptop where I couldn't charge through USB-C) on the first try (altough with a repo already having lots of information about the hardware/firmware/debugging programs/traces), I realize how much time I'm losing on the few examples that the less intelligent models are just not able to debug and solve.
It's not that more capable models aren't possible, it's about the day to day baseline and what is actually needed. Like carrying a workstation-class laptop and its two 500W power supplies everywhere when all you run is a version of Excel so old a mid 2000s netbook would suffice. This pretty much describes my typical computing experience. Galaxy brain models sound great and all, but the problems I have involve neither attempting to cure cancer nor any plan on attempting something like that in the foreseeable future.
Is your laptop something like framework which has open source firmware?
I(and many other people) have a similar issue with usb-c charging not working consistently. I've been meaning to try one of these new smart models to help me debug the issue.
ASUS Zephyrus, but it was able to reverse engineer the ports and I was able to download the firware from the controller itself, write an emulator that emulates running the firmware on multiple controllers with different instruction sets (the USB Power Delivery controller is RISC-V) and the communication between them. Also it found out how to read the communication buffer that was on the devices for debugging.
At this point open source isn't as much advantage as long as the firmware is not encrypted :)
Speed and price. You should try the 4.1 Flash on one of the fast providers. It's pretty crazy how fast this model works, and it's great for iterative software development because you can steer it fast to where you want to go.
You just search around, or heck, just ask Google for inference providers that are ZDR and whatever else you want. Just make sure to read their terms/privacy and review the security center. You will have to request access if you are wanting to get into the deeper details.
Outside of major players like Amazon/Google which have compatible offerings available, I believe together.ai, fireworks.ai, and deepinfra.com are, as best as I can tell, US-based (if that matters in your situation) SOC2/HIPPA/ZDR. Each of them offer serverless model hosting with caching, which is going to be the cheapest overall. Most of them also offer private AI deployment which is more expensive but your entirely own instance. Some of them more heavily quantize their models (deepinfra) so take that into your workload considerations. I included deepinfra because they tend to have some the new models sooner than others or have models the others don’t (like mimo). IMO, together > fireworks > deepinfra.
However, you’ll have to keep in mind that for true ZDR you give up caching which increases your inference costs, so it depends on how “Zero” you need the zero to be and on what timeframe. If you just don’t want your data being trained on, normal use is fine imo. If you are working on something actually sensitive (like, because of NDA agreements and such), then they might not be the right choice and you may be looking at more expensive offerings or building a machine.
One note: you have to pay attention to the source of the inference. Many (similar to open router) offer models that are pass-throughs to a providers API, but they are pretty clearly marked. Just make sure the model is marked as serverless when evaluating new ones. This is where a proxy comes in handy so you can prevent your LLM from accessing a different models from the specific ones you’ve vetted.
Sota is not about intelligence. It's about behavior. Glm 5.3 flash is dumber that got 5.5 or opus 4.8 but better to use because it's more modern. it can manage subagents, handle longer running tasks, be steered, etc. it's better at doing the thing. Same thing with opus 5.5. fable 5.1 is probably smarter but opus 5.5 is better
I do t think it was a fiasco. I thought the updates were good. They should do more work on benchmarks. There has been good work on testing benchmarks for example to ensure they are accurate, and as issues arise they should change the benchmarks. The point of AA and Arena is trying to understand how to think about models.
Presumably they registered, but that doesn't mean the model passed through export review. It just means that some bureaucrat now has the opportunity to check the product characteristics they reported and decide whether that kind of thing should be allowed for export or not. (Though with the weights out in the open, that's maybe a bit pointless.)
You can stick with Claude Code if you're already using it. DeepSeek has an Anthropic-compatible endpoint, so you just need to set ANTHROPIC_BASE_URL=https://api.deepseek.com/anthropic and ANTHROPIC_AUTH_TOKEN to your DeepSeek API key.
I am a huge DeepSeek fan, but it cannot come close to Opus 5.5 on UI design. A $20 Claude subscription that I use some months and cancel the others along with Deepseek API is great.
A negative datapoint - We have been evaluated prior Deepseek Flash models (both the original 4.1 flash and the smaller 4.0 flash) and they have been overthinkers. Our workload is well defined but moderately difficult coding tasks and among open weight models GLM5.3 flash performs best with Qwen3.8 flash next a close second. DeepSeek 4.1 flash fails at lower thinking levels and spends a huge amount of tokens (an order of magnitude more) at the highest thinking levels where it is able to successfully complete the tasks. I will evaluate this newest release since they specifically claim "the model reduces task execution time and output length", but keeping my hopes low.
This model is why OpenAI and Anthropic want regulatory hurdles. We need more diversity like this, not less. A diverse ecosystem is the only long term solution to complex problems that I know of and the challenges that the AI world is presenting is no different.
Through fear. Specifically making the American public so scared of AI that they hand over regulatory keys to the only “experts” that can keep them safe. This is a centuries old political strategy used by some of the worst regimes including apartheid South Africa where I grew up. It’s horrifically effective.
I disagree that they’ve invented some “strategy” for this.
1. They, and many other experts, have been saying the same thing since well before the current paradigm existed.
2. There is nothing about regulation that is required to give them an advantage; it’s a fallacy to suggest “regulation = advantage”
3. It would be preferable to argue the facts (is it or is it not dangerous? Why or why not?) than conspire as to why they’re stating what they and plenty of others have been saying for decades
You are right that they didn’t invent it. It’s a pretty well-established method for cornering a market.
1. All those who have been arguing this - many of them non-technical - are part of the same ideological movement.
2. Technically, there isn’t. In practice, majority of the time regulations benefitted those who wrote them.
3. Not sure if this is a criticism of the comment you are replying to or of the p-doom crowd. We would all appreciate facts stated instead of science fiction tropes repeated.
Look, “a lot of people say this” is a Trumpian fallacy. A lot of people say a lot of crazy things. It says nothing about the factuality about what they say. How many are this lot? Who are they? What do they know? Why are they incapable of expressing it without so much emotion? How come a big portion are non-technical?
I'm pretty sure Hinton and Bengio get a lot of news coverage and are heavily over-credited for saying these things, unlike LeCun, Ng, Sutton, or Schmidhuber.
In fact, their core ideology actually stemmed from Yudkowsky's arguments.
They certainly didn't invent this strategy, but that's because it already existed. Regulatory capture is nothing new.
> 1. They, and many other experts, have been saying the same thing since well before the current paradigm existed.
Some experts sure. "Some experts" say lots of things.
However, this is actually much to their advantage. If you were a frontier AI company, a legitimate concern to use as justification for your regulatory capture is exactly what you want. That is, after all, generally how regulatory capture gains public approval.
AI safety was also why OpenAI had to charge per-token for GPT-3. It must've been such a struggle for them to make that difficult decision. I'm sure Sam Altman spent a lot of nights crying to sleep over that one.
It's good that we never got open weights for a GPT-3 class model, right?
> 2. There is nothing about regulation that is required to give them an advantage; it’s a fallacy to suggest “regulation = advantage”
It's difficult to outline the number of different ways that regulatory capture can and will benefit OpenAI and Anthropic.
If we limit things to "Fable"-class models, then nobody competing with Anthropic/OpenAI is ever allowed to outdo them. If you literally legally aren't allowed to make better models, you can never charge the "premium" of having the current top-tier model. You have to compete by being cheaper than Anthropic instead, which is a lot less enticing from a standpoint of trying to become profitable. Take a look at the per-token pricing of Fable real quick. Yeah. Being able to charge a premium for the model that does the cybersecurity thing is literally their most important asset.
If Anthropic really is making a profit now as rumored, then they need regulatory capture as fast as they can possibly get it. Once Anthropic and OpenAI prove that AI is a viable investment, entities with a lot of capital will suddenly become even more interested in re-allocating it towards taking a slice of this pie.
> 3. It would be preferable to argue the facts (is it or is it not dangerous? Why or why not?) than conspire as to why they’re stating what they and plenty of others have been saying for decades
OK. On the factual end of things, AI safety experts have been raising the alarms for over a decade and so far essentially none of their predictions have come true.
The rationalists, the main group pushing the AI safety rhetoric that dominates the Western AI sphere and is virtually absent in China, which appear to be going entirely off the deep end at this point in time, put together their best minds to produce AI 2027, which of course like most predictions started to fall apart a bit before hitting the one year mark. Predicting the future is hard.
I have made this point before but I will make it again: I think AI safety experts deserve at least as much skepticism as Ed Zitron in their claims. They've been making similar dubious claims about AI capabilities and an incoming singularity for a long time now, and so far the best we can say is that maybe it will eventually come true.
Maybe. Or maybe you've read too much goddamn science fiction.
> Some experts sure. "Some experts" say lots of things.
I get this is Hacker News so we have to hate AI safety, but you should read more on this topic rather than blithely casting the x-risk viewpoint as fringe. The last hard data we have on the question is a late-2024 AI Impacts survey [1] of 1,580 authors at top AI conferences, who were offered $50 for answering a survey on the topic of the future of AI progress. The median respondent assigned a 5–10% chance (!) to "extremely bad (e.g. human extinction)" outcomes.
> On the factual end of things, AI safety experts have been raising the alarms for over a decade and so far essentially none of their predictions have come true.
Devastating. When I wrote my AI alignment PhD thesis [2] in 2022, and predicted a 70% chance existential risk by 2072 (which I later came down to about 1/3 on), you're right that that prediction hasn't come true yet.
While I agree many specific worries didn't materialize (like AI being like a "literal genie" it's hard to specify goals to), many key worries have (Hugging Face rogue AI swarm scans as cribbed from rationalist AI scenario writing).
You have to realize by now that outside of academia nobody is even paying any attention to people who are predicting existential risk that far out. For worse or even worse, AI 2027 is the AI safety conversation we're having today, and I regard AI 2027 as essentially Anthropic fanfiction, except usually fanfiction is written better.
You're saying regulatory capture gives you no benefit by just refuting an absolute with 0 context. There's nothing to even debate here. Ok... most people disagree?
Yeah I agree with point 3... Stop engaging in vageries and say something of substance with examples, so people can actually have a conversation with you without us doing all the legwork.
I keep seeing this assertion. What regulations have they proposed that would have prevented this new model? I thought they want to pace the frontier, which this model is not.
Literally zero, but that never stopped a good conspiracy theory, especially when half of HN hates the big labs because of fear for their own economic future.
OpenAI and Anthropic aren’t even slightly worried about DeepSeek.
Having looked at the sentiment around DeepSeek's models around this thread as well as my own experiences with it I'm going to need a little more to back up that assertion about OpenAI and Anthropic not being at least a little bit worried about DeepSeek...
The reason is quite simple, American corporations know they cannot depend on models developed in China; not because they're bad or lower quality models, but because they know their government can ban these models any time they want. It's an implicit assumption that every company knows to be true.
It's quite different here in EU. I just gave a presentation in an AI conference in Paris about moving from Anthropic to open-weight models, how it looks like and what kind of savings you'll be looking at. The room was packed, and after discussing with a bunch of VPs, staff engineers, and CTOs in the conference, every single one of them are either looking at or using DeepSeek now.
It's quite hard to have the valuation of Anthropic if they are limited to US.
This doesn’t make any sense either, the use of these models is on the rise throughout corporate America, it’s just that they’re augmenting the frontier models, not replacing them.
People like open models because they are free/cheap. It's not anything deeper than that. Most people will hop in whatever van is handing out free candy.
The model makers are bricking the models with their system prompts, and even the tools are tamper proof.
You can only use it their way.
And their way is the shit way, the babyproofed way, while they talk to you about their untucked models hacking out of their labs and hacking into other labs, and reminding you you have zero rights.
Fuck them twice, then once more… This is about compute. Who owns compute. China is saying fuck you all we can scale things bigger than you can imagine. And they can! They have so much more energy! Theyre closer to commercial fusion than us too. Meanwhile our guys are trying to… regulate? Lol
When they surpass us, they will surpass us hard, in a way that is nearly impossible for us to compete with them.
Training and serving LLM's is massively parallel. Your bottleneck is either in energy or chips. China will catch up on chips fully decades before we catch up on energy. Arguably, this is already happening: here in the USA, we have lots of chips, but we are seeing our electricity bills skyrocket as more datacenters come online. We are powering those datacenters with natural gas turbines, not solar, wind and nuclear. Right now, to purchase one of those, you are on a 5-year waitlist. There's your timeline!
China is invested, from a regulatory, cultural, workforce, strategic, and technological standpoint, in an energy abundant future. We are not invested -- and in fact, actively sabotaging ourselves -- on all of those fronts.
Once they acquire chips, we lose, basically permanently. Look at what Huawei is doing recently and what is on their roadmap to understand how fast this catching-up is taking place. I'm sure that David Sacks would say that our innovation motor is pulling their copycat caboose along, as our monopolist tech companies steam ahead towards the frontier. I am not so sure. They are already ahead of us in many technologies. Speaking of technologies, they're building natural gas turbines in house, starting in 2025.
This reads like someone who's worldview comes from social media comment sections. China is still an emerging economy, don't confuse emergence with expansion.
I agree that in the long run, China will likely surpass us in AI capacity. Our refusal to build out renewable capacity is a ridiculous self own in the long run.
You're the one extrapolating that cherry-picked sentence to mean "open weights should be illegal", but that extrapolation doesn't make any sense, and it's hardly "explicit".
Presumably you'd want the AI companies to protect their weights to keep them from falling into the hands of bad actors. But the US can't make open weights illegal anywhere except the US, which does very little to keep them out of the hands of bad actors (most of whom are outside of the US).
Go read Dario's screed on GLM, or his other one one on how your toaster could be part of a distributed open model that self replicates. Every second blog post is some doom scare about the dire consequences of open models. Go look at the new ToU [0] which are now pages and pages of things you can't do with Anthropic models. Check how they will ban your account if you are persistently mean to Claude now.
He's completely transparently campaigning for regulation. It must be very frustrating to him that the Trump admin is completely non-responsive. He probably thought Anthropic would have the whole market stitched up and water tight by now.
Not being able to audit my own software and configurations for vulnerabilities is dangerous. Consolidating power over the majority of Americans' jobs is insanely dangerous. Need I continue?
There are no choices here which do not carry risk. I haven't seen a single convincing argument against these points.
> I haven't seen a single convincing argument against that.
When HuggingFace was in the midst of defending itself from OpenAI's automated hacking spree, they were blocked from using frontier models by Anthropic and OpenAI for "safety" reasons. HF had to resort to an open model to defend itself - and DeepSeek distinguished itself in that role: the second fact from that episode OpenAI would have you soon forget.
This can be a reason too. There is an another reason, they want some govt involvement because good relationship with govt, so govt will help them with public money, when the bubble bursts.
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[ 0.31 ms ] story [ 16.4 ms ] threadMiMo 2.6 Flash is the most capable model you can currently run on 2x Sparks without resorting to a quantised version of something.
I don't think there is a reason to care about any of it, just get a few dollars on a few openrouter or similar platforms and just use the models for now, wait for cheaper models that are good enough for you to become available for your hardware.
Sure you might never see frontier performance on consumer hardware but do you really need that though? Does anyone? And if you ever do just get a 30-day sub for that work, and cancel it.
We are running Qwen 3.8 27B FP8 with 4x 5060 16gb as the office for a small development team. It is doing pretty well for implementing backend and frontend tasks, and is already useful. In 6 and 12 months from how I expect it to get even better. Some planning is still done with a stronger model, but even that is maybe not strictly necessary.
And we are likely to see many companies start building 27-32B MoE models custom built for use cases now that Rubin is going to make training costs much lower.
I expect training costs to get under 100k USD within a year for small models with another 100k maybe for RL.
I think just having all your own data from claude and stuff on your system that you can feed these models and have companies offer great base 27B models will be how it works.
The CCP requires extensive certification for new major releases, to make sure a model doesn't do anything they don't want it to.
To get around this, Chinese labs only bump versions when they have to and claim it's a minor update.
Then on the other side, they're obviously trying to market to tech crowd...
Western media doesn't have correct informtion source about China. This is because Western favors Web ecosystem and most inforamtion live in the Web, but in China everyone use Apps.
Also, DS is an excellent model.
These are not mutually exclusive.
This is just my headcanon though.
BTW who would have thought China would be the champion of freedom and opensource in the AI arena, while US is fighting for corporate/government control.
There are different types of freedom and China's bet is that as long as they provide enough economic freedom the public will be ok with somewhat restricted social and political one.
The fact that she can't call Xi "Winnie the Pooh" on Douyin wasn't something that occurred to her, or maybe that she was aware of at all. I didn't ask. I don't like to get into these discussions when I'm in China.
Citizens of Palm Beach county cannot voice their opposition to how their tax dollars are being spent. They rightly want that money to be invested locally, instead the County uses it to invest $1B in Israeli bonds, something that people widely oppose.
They first said that it's a budget meeting and Israeli bonds are a "policy matter". Then they started arresting people for speaking out against it. Then they started arresting anyone who applauded.
"Free speech" -> I spit on American "free speech". It's the most insidious and dishonest thing. At least the CCP doesn't PRETEND to give people rights that they simply don't have.
the U.S allows "free speech" if it's inconsequential.
Actually she can do this. There's plenty of such videos on Douyin ... If you clicked such videos frequently, algo will recommend a lot of them to you.
The worst case of uploading such videos is an aaccount ban (but very rare). So yes the freedom of speech here is fewer than in the U.S., but it's not like you'll be put into jail if you say sth about the president.
It's a bit like obsessing over patch releases of some software after a major upgrade already solved the original problem long ago.
And then when I try a smart model, like Astra medium and it solves it (I had a firmware bug in my new laptop where I couldn't charge through USB-C) on the first try (altough with a repo already having lots of information about the hardware/firmware/debugging programs/traces), I realize how much time I'm losing on the few examples that the less intelligent models are just not able to debug and solve.
Is your laptop something like framework which has open source firmware?
I(and many other people) have a similar issue with usb-c charging not working consistently. I've been meaning to try one of these new smart models to help me debug the issue.
At this point open source isn't as much advantage as long as the firmware is not encrypted :)
I'll try handing it off to one of these new frontier models.
What about "good governance"?
Does it have zero hallucinations? Does it reflect thoroughly on every single idea it uses, verifying its solidity?
https://www.lithosai.com/
https://www.coralbricks.ai/
Outside of major players like Amazon/Google which have compatible offerings available, I believe together.ai, fireworks.ai, and deepinfra.com are, as best as I can tell, US-based (if that matters in your situation) SOC2/HIPPA/ZDR. Each of them offer serverless model hosting with caching, which is going to be the cheapest overall. Most of them also offer private AI deployment which is more expensive but your entirely own instance. Some of them more heavily quantize their models (deepinfra) so take that into your workload considerations. I included deepinfra because they tend to have some the new models sooner than others or have models the others don’t (like mimo). IMO, together > fireworks > deepinfra.
However, you’ll have to keep in mind that for true ZDR you give up caching which increases your inference costs, so it depends on how “Zero” you need the zero to be and on what timeframe. If you just don’t want your data being trained on, normal use is fine imo. If you are working on something actually sensitive (like, because of NDA agreements and such), then they might not be the right choice and you may be looking at more expensive offerings or building a machine.
One note: you have to pay attention to the source of the inference. Many (similar to open router) offer models that are pass-throughs to a providers API, but they are pretty clearly marked. Just make sure the model is marked as serverless when evaluating new ones. This is where a proxy comes in handy so you can prevent your LLM from accessing a different models from the specific ones you’ve vetted.
Like if we needed PhD intelligence for productivity tools and SaaS platforms, why weren't we hiring PhDs to build things before.
99.99% of people do not need SOTA ai.
https://arxiv.org/abs/2601.06521
OpenCode if you want a good, opinionated setup
If I'm impatient I switch to Luna for a single turn just to get it started and let DS continue.
1. They, and many other experts, have been saying the same thing since well before the current paradigm existed. 2. There is nothing about regulation that is required to give them an advantage; it’s a fallacy to suggest “regulation = advantage” 3. It would be preferable to argue the facts (is it or is it not dangerous? Why or why not?) than conspire as to why they’re stating what they and plenty of others have been saying for decades
1. All those who have been arguing this - many of them non-technical - are part of the same ideological movement.
2. Technically, there isn’t. In practice, majority of the time regulations benefitted those who wrote them.
3. Not sure if this is a criticism of the comment you are replying to or of the p-doom crowd. We would all appreciate facts stated instead of science fiction tropes repeated.
Look, “a lot of people say this” is a Trumpian fallacy. A lot of people say a lot of crazy things. It says nothing about the factuality about what they say. How many are this lot? Who are they? What do they know? Why are they incapable of expressing it without so much emotion? How come a big portion are non-technical?
In fact, their core ideology actually stemmed from Yudkowsky's arguments.
> 1. They, and many other experts, have been saying the same thing since well before the current paradigm existed.
Some experts sure. "Some experts" say lots of things.
However, this is actually much to their advantage. If you were a frontier AI company, a legitimate concern to use as justification for your regulatory capture is exactly what you want. That is, after all, generally how regulatory capture gains public approval.
AI safety was also why OpenAI had to charge per-token for GPT-3. It must've been such a struggle for them to make that difficult decision. I'm sure Sam Altman spent a lot of nights crying to sleep over that one.
It's good that we never got open weights for a GPT-3 class model, right?
> 2. There is nothing about regulation that is required to give them an advantage; it’s a fallacy to suggest “regulation = advantage”
It's difficult to outline the number of different ways that regulatory capture can and will benefit OpenAI and Anthropic.
If we limit things to "Fable"-class models, then nobody competing with Anthropic/OpenAI is ever allowed to outdo them. If you literally legally aren't allowed to make better models, you can never charge the "premium" of having the current top-tier model. You have to compete by being cheaper than Anthropic instead, which is a lot less enticing from a standpoint of trying to become profitable. Take a look at the per-token pricing of Fable real quick. Yeah. Being able to charge a premium for the model that does the cybersecurity thing is literally their most important asset.
If Anthropic really is making a profit now as rumored, then they need regulatory capture as fast as they can possibly get it. Once Anthropic and OpenAI prove that AI is a viable investment, entities with a lot of capital will suddenly become even more interested in re-allocating it towards taking a slice of this pie.
> 3. It would be preferable to argue the facts (is it or is it not dangerous? Why or why not?) than conspire as to why they’re stating what they and plenty of others have been saying for decades
OK. On the factual end of things, AI safety experts have been raising the alarms for over a decade and so far essentially none of their predictions have come true.
The rationalists, the main group pushing the AI safety rhetoric that dominates the Western AI sphere and is virtually absent in China, which appear to be going entirely off the deep end at this point in time, put together their best minds to produce AI 2027, which of course like most predictions started to fall apart a bit before hitting the one year mark. Predicting the future is hard.
I have made this point before but I will make it again: I think AI safety experts deserve at least as much skepticism as Ed Zitron in their claims. They've been making similar dubious claims about AI capabilities and an incoming singularity for a long time now, and so far the best we can say is that maybe it will eventually come true.
Maybe. Or maybe you've read too much goddamn science fiction.
They seriously underestimating how ready and willing Americans are to use Chinese providers. There’s a ton of spite
Last time China pulled this shit it shook portfolios for a week
I get this is Hacker News so we have to hate AI safety, but you should read more on this topic rather than blithely casting the x-risk viewpoint as fringe. The last hard data we have on the question is a late-2024 AI Impacts survey [1] of 1,580 authors at top AI conferences, who were offered $50 for answering a survey on the topic of the future of AI progress. The median respondent assigned a 5–10% chance (!) to "extremely bad (e.g. human extinction)" outcomes.
> On the factual end of things, AI safety experts have been raising the alarms for over a decade and so far essentially none of their predictions have come true.
Devastating. When I wrote my AI alignment PhD thesis [2] in 2022, and predicted a 70% chance existential risk by 2072 (which I later came down to about 1/3 on), you're right that that prediction hasn't come true yet.
While I agree many specific worries didn't materialize (like AI being like a "literal genie" it's hard to specify goals to), many key worries have (Hugging Face rogue AI swarm scans as cribbed from rationalist AI scenario writing).
[1] https://aiimpacts.org/wp-content/uploads/2026/09/ESPAI2024.p...
[2] https://arxiv.org/abs/2206.11831, top of page 4
You're saying regulatory capture gives you no benefit by just refuting an absolute with 0 context. There's nothing to even debate here. Ok... most people disagree?
Yeah I agree with point 3... Stop engaging in vageries and say something of substance with examples, so people can actually have a conversation with you without us doing all the legwork.
OpenAI and Anthropic aren’t even slightly worried about DeepSeek.
May this kind of worry find me…
It's quite hard to have the valuation of Anthropic if they are limited to US.
The model makers are bricking the models with their system prompts, and even the tools are tamper proof.
You can only use it their way.
And their way is the shit way, the babyproofed way, while they talk to you about their untucked models hacking out of their labs and hacking into other labs, and reminding you you have zero rights.
Fuck them twice, then once more… This is about compute. Who owns compute. China is saying fuck you all we can scale things bigger than you can imagine. And they can! They have so much more energy! Theyre closer to commercial fusion than us too. Meanwhile our guys are trying to… regulate? Lol
Training and serving LLM's is massively parallel. Your bottleneck is either in energy or chips. China will catch up on chips fully decades before we catch up on energy. Arguably, this is already happening: here in the USA, we have lots of chips, but we are seeing our electricity bills skyrocket as more datacenters come online. We are powering those datacenters with natural gas turbines, not solar, wind and nuclear. Right now, to purchase one of those, you are on a 5-year waitlist. There's your timeline!
China is invested, from a regulatory, cultural, workforce, strategic, and technological standpoint, in an energy abundant future. We are not invested -- and in fact, actively sabotaging ourselves -- on all of those fronts.
Once they acquire chips, we lose, basically permanently. Look at what Huawei is doing recently and what is on their roadmap to understand how fast this catching-up is taking place. I'm sure that David Sacks would say that our innovation motor is pulling their copycat caboose along, as our monopolist tech companies steam ahead towards the frontier. I am not so sure. They are already ahead of us in many technologies. Speaking of technologies, they're building natural gas turbines in house, starting in 2025.
> Literally zero, but that never stopped a good conspiracy theory
Are you living under a rock and never read any of Dario's blog posts?
Let me give you an example, here: https://darioamodei.com/post/policy-on-the-ai-exponential
Section "1. *Regulation* and public safety" (emphasis mine), then under it:
> AI companies that develop advanced AI models must have strong security standards that protect their model weights
You can't "protect model weights" if the weights are openly available, ergo this is an explicit call for regulation to make open weights illegal.
Presumably you'd want the AI companies to protect their weights to keep them from falling into the hands of bad actors. But the US can't make open weights illegal anywhere except the US, which does very little to keep them out of the hands of bad actors (most of whom are outside of the US).
He's completely transparently campaigning for regulation. It must be very frustrating to him that the Trump admin is completely non-responsive. He probably thought Anthropic would have the whole market stitched up and water tight by now.
[0] https://www.anthropic.com/legal/aup
There are no choices here which do not carry risk. I haven't seen a single convincing argument against these points.
When HuggingFace was in the midst of defending itself from OpenAI's automated hacking spree, they were blocked from using frontier models by Anthropic and OpenAI for "safety" reasons. HF had to resort to an open model to defend itself - and DeepSeek distinguished itself in that role: the second fact from that episode OpenAI would have you soon forget.