Hacker Newsnew | past | comments | ask | show | jobs | submit | glub's commentslogin

Dario: Mr. Trump, we don't want to advance anymore, but China very bad, if we stop, China take over. Please stop China, then we rest.

Trump: you're not in the EU, get to work.

Jokes aside, I'm very happy that Dario's attempts at smuggling regulatory capture by appeasing Trump with China has ended with a cold shower.


>In my experience, LLMs only exhibit this kind of behaviour when they are put in sandboxes too restrictive too achieve their task.

This my experience also. I had an issue with my Unraid server, so I had an agent running on my machine figure it out and fix it. Along the way, something went wrong with networking, and it couldn't ssh into it anymore. It remembered it saw a syslog-ng server on unraid, then tried to ssh into it, surprisingly, my dummy me had left a ssh key there for unraid, so it just hopped into Unraid from there.

AI doomers would call this misalignment and/or a hack. I call it an agent doing what it was asked to do and overcoming difficulties.

Every time I saw an agent do something "misaligned", it was always because there was something getting in its way that I didn't explain would happen.


Open research and open weights from China are not contributions to China only.

If you can secure compute, there's a whole lot you can do as a US firm with this research and weights.

So it's a simple strategy:

1. Ban big players from entering market with METR breathing down their neck, which is controlled by Anthropic

2. Ban Chinese models so that small players can't do optimizations on them


How are you going to ban Chinese models from India? Or Israel? Russia? Brazil? Or of course China?

By treating models the same way drugs are treated.

That alone will dissuade many organizations from going anywhere near them.

If that doesn't work, there's a whole lot you can do - sanctions, hell, even war.


You can't treat models like drugs. One is physical and the other is digital.

To your point, the war on drugs is a colossal failure which has achieved none of the objectives it set out to do. You can now order drugs from your mobile phone in any major city in the west and the purity is often higher and they deliver it to your door sometimes faster than Uber eats.

See also for example digital piracy where the entertainment industry has lobbied, cajoled and convinced many governments around the world to criminalize the distribution of their content over the internet for free.

What was the result? After 20 years of DMCA takedowns, countless celebrations that torrents were dead, and many other self congratulations in the media, you can now find 10 different pirate streaming websites where all the episodes of pretty much any show that was ever created are available for free in 5 five minutes flat and the image quality is as good as on your Netflix or Paramount account.

The only way such a ban of open weights model would work is if you were to replicate the great firewall of China in the US and in Europe and even that doesn't work completely.

As for sanctions, China and India are buying Russian oil in enormous quantities as we speak and they don't really care that Europe and the US have put sanctions on Russia and I suspect you will see the same results with models coming from China.

If a country has a choice to either use the expensive SOTA models approved by Washington or Europe only or using the cheaper and not so SOTA models, why would they use the US ones? Why would it be in there interest?


I'm not saying that we should ban any models or that such bans would be effective - for the reasons that you've outlined that they're counter productive, and as a principle, I don't think government should have any say in how much intelligence I have access to.

But it is the likely path US/EU is going to take if the voices of Dario, Sam, and Elon prevail. Because that's what governments know how to do, even if they know it doesn't work.

> If a country has a choice to either use the expensive SOTA models approved by Washington or Europe only or using the cheaper and not so SOTA models, why would they use the US ones?

Depends on which entities we're talking about.

An enterprise in Turkey: they would be afraid to use a US/EU sanctioned model because they have EU/EU clients and US/EU says they will put any enterprise in a nasty list, close their bank accounts, deals and agreements if they use a Chinese model.

A random guy in random country building something in their garage: would have to buy expensive hardware to run inference, because there's no inference provider on the open web serving these models, but China. And subscribing to these Chinese services is punishable by 20 years in jail without pardon.

I'm obviously talking about hypothetical scenarios here, but all I'm saying is that US can definitely make using any non-US-approved model effectively impossible.


> and the image quality is as good as on your Netflix or Paramount account.

Actually better, because Netflix and Paramount limit the availability of best quality video to a narrow set of devices and operating systems that may run on them, while torrents don't.


Sanctions and war against China, India, etc? Lmao. We already saw how the world reacted to high tariffs by the US.

10 years ago the Us had enough global leadership to actually influence the world and at the very least stop China. It’s amazing, and sad, how quickly it’s thrown it all away.

It is amazing but i wouldn't call it sad.

yep we did, they bent the knee.

sure they did

And they've been trained on user data where users have been trying to set up effective coordination flows since the very first harness.

Even if you take out the LLMs out of the equation, it's at the very least a negligence. Model didn't escape a sandbox, as there was no sandbox.

Perhaps I’m not being as strict with the word sandbox but they were sandboxed right? They did not have generic internet access they exploited other software to make external requests.

You're right. It's my opinion that if your sandbox has a path to the internet, it is not a sandbox, it's a gimmick.

And the 2 other incidents with OAI/ANT had the same issue, but it's even funnier - sandbox in those cases had a direct access to internet because someone forgot to configure it right.

I've seen very early models do similar things on my machine when they hit some unexpected blocker when trying to access a path. I remember early sonnet opening a file in browser because OS sandbox prevented from accessing it directly.

I've also had models discover a syslog-ng server (that I for some reason had ssh key inside), to get into my unraid server because machine they were running on didn't have direct network connection to Unraid server.

It can't be just me who is aware LLMs have been doing such things for the better part of last 2 years. I probably have better sandboxing on my machines now than trillion dollar companies crying AI will kill us all. That's at the very least, negligence to me.


It depends IMO about how strict this is. It's pretty awkward to refuse to call something a sandbox because it may have an unknown bug that would allow escaping. Or rather in this case it was that they had access to a package manager, and the models discovered a bug that allowed them to access the internet (first they discovered that they could use the cache to leave messages).

I do get your point, I just think an overly strict definition can be awkward too. This wasn't as simple as the sandboxes having internet access and writing "pls no internet calls" in the prompt.


Yes, but negligence is more commonly a tort than a crime. Negligence is generally only criminalised in certain narrow cases, e.g. when it causes human deaths or serious physical injuries

And tort law only works when the plaintiff believes it is in their overall interest to sue. If a corporation decides it isn't in their strategic interest to sue a partner corporation, nobody can make them. And even if they do sue, the amount necessary to settle a small cybersecurity incident is likely well within the budget of a megavendor.


I'm the opposite. Every time I've let Sol/Astra be decisive, I ended up with an overengineered mess.

I much prefer getting alerted when there's more than 1 approach to the problem and it's discovered mid-implementation.

I don't want to do the grunt work of writing code, but I do want to know the architecture and be responsible for the decisions.

Fable is also very good at pushing back when I propose something that will cost me. E.g. I'm working on a configuration layer above nix to manage my homelab fleet declaratively, and I tend to get into "config as new language", where Fable just goes - let's not do that.


> Fable is also very good at pushing back

Oh man! This also is a pet peeve of mine with Fable. I will look at what it's doing and say "Shouldn't it be done this way?" and then it will spend forever arguing with me that it should be done the way it wanted to do it. It seems to get stuck in a certain way of thinking and will insist its way is right until I can really prove it - or just go over to Astra.


I'm surprised Sol and Astra are leading "Unverified assumption" metric and Fable is better there.

I run Fable as my main model with Sol as advisor that watches every turn. Fable likes to throw around assumptions that it didn't check that are simply false, and Sol always goes to actually verify them and then alert Fable it's assuming things.

I've tried reversing this pairing with Fable as advisor. It'll just sit there going "sounds good"


I suggest you flip them. The verifier role will always verify. You will see Sol making assumptions and Fable fixing them.

But I agree - Fable makes some spectacular assumptions (which are poor assumptions).


I think what matters in this case is how proactive and greedy the model is.

GPT models are extremely proactive and gredy. So when Fable mentions something that may affect some obscure component of the system, GPT will start digging the codebase, execute web searches, re-read AGENTS.md and hit fable on the head.

Fable never does that, it just reads the turns and acknowledges it read them. This also explains why GPT models tend to overengineer things and why they're amazing reviewers if you triage their findings.


GPT doesn’t do all of that all that much when it itself is the implementer. RL has made implementation and reviewing two different behavior sets.

In open weights models on a similar metric I find this to be highly specific to role and model. Some models are just diggers by nature, but all will verify more if you tell them to. Have you tried running a Claude watcher with the same role as Sol to see if it verifies as much?

What do you use as the harness?

oh-my-pi.

I was using my own homegrown (mega slop) harness for a while, but it distracted me from working on my actual projects, and I realized oh-my-pi was doing the same things I've been doing, including advisor, native server-side compaction, etc. It's a really good harness.


would love to chat and learn more about your set up! here's my email - janak@withspecific.com

Dario, Sam, and Elon are all on the same page on this.

So it's either they truly think AI is going to kill us all, or there's some other motives at play here.

I don't think these people could possibly agree on the color of the sky, so what could the other possible motives be, based on what we know?

OpenAI / Anthropic models have largely stopped advancing - that's not a good look when you're pre-IPO and Chinese models are catching up.

xAI is tracking behind, and whatever regulation it may be that paces the frontier, Musk is less likely to be affected by it. Therefore xAI should be pro-regulation that stiffles his competition and gives him time to catch up.


> OpenAI / Anthropic models have largely stopped advancing

I'm shocked anyone could conclude this. This year it became common for people to entirely delegate coding to AI (I know many competent programmers/researchers who do this now). Progress in math has just been insane. An internal model at OAI just resolved one of the most celebrated open problems in mathematics. If anything, progress has accelerated.


> This year it became common for people to entirely delegate coding to AI

This has been the case for around 2 years now, more reliably - a year. We've mostly stayed there since then.

Saying that more people started doing it isn't indicative of significant improvement. Some people just started doing it later.

I can't speak about math because I haven't used AI for that application, but I know that there hasn't been any significant advancement in coding in this year on base models. There has been more RL work, more harness work, more tools, they all expanded some capabilities like cyber or orchestration or tool use, but raw intelligence of base models is no longer where the main focus is.


> This has been the case for around 2 years now, more reliably - a year.

I have to disagree with this pretty strongly. Opus 4.5 needed a lot of handholding not to work itself into a corner pretty quickly. Fable I basically never need to correct, and I've most become a data source.


What are you talking about - I feel like we’re living in parallel realities. If I had to go back to opus 4.5 tomorrow I’d be hugely upset and significantly slowed down

I'm not. Yes we normalized 1m context window and models tend to hallucinate less.

But models have been somewhat stagnant since Opus 4.6/7.

And in some regards there were even regressions like Claudeisms that are load bearing.


Yes these guys are completely delusional.

2 years ago a model could barely solve the AMC, 1 year ago it got IMO gold, and this year models have solved multiple millenium problems.

Even 1 year ago ai code was just unusable (claude code only became available 1.5 years ago!) and now basically everyone I know from independent shops all the way to faang and anthropic/openai themselves exclusively use some AI agent to code.

Why does HN continue to delude itself that "models are not improving?" Maybe for the simple things they care about its "roughly the same," but they are _clearly_ improving.


Waitwaitwait multiple millennium problems? What was the other one???

Increasing a bound on the fraction of Reimann zeros on the critical line doesn't count; even Anthropic says they don't think this line of work will lead to a solution.


Navier Stokes, and _allegedly_ the Hodge Conjecture and Birch–Swinnerton-Dyer.

> OpenAI / Anthropic models have largely stopped advancing

Have they? That seems like quite a claim given the last 6 months, particularly for cybersecurity.


The attention is shifting towards RL, harnesses, and memory systems from the pretrains of more intelligent and capable base models. So extracting additional capabilities from what we already have.

That is a much easier catch up game. GLM 5.3 and DeepSeek flash 4.1 also demonstrate significant jump in cyber capabilities. So yeah, it is a slowdown in the place where it matters. RL has been around for ages, there's no moat there if you already have a good enough pretrain.


Many claims but no clear evidence that they actually find significantly more severe issues compared to open models.

Open models and agents can't be trusted without handholding. Astra can one-shot six months of work. Years of work, even.

OpenAI just solved Navier-Stokes.

Seems like the US is on a takeoff ramp to me.


Tell me you haven't tried letting Astra go without telling me.

Astra can confidently one-shot 500k lines of slop, with 800k lines of tests covering it, without testing a single intended product requirement, and none of it actually working.

All models require hand holding. Fable and Astra are no exceptions. The difference is only in the amount of hand holding required, and there's essentially no gap here anymore between American and Chinese models.

I only use Chinese models sparingly because American models are so much cheaper with subscriptions, that it doesn't make economic sense to not use them. If/when that changes, I could simply route to cheapest model that's available at the moment and I wouldn't notice much difference in most applications.


Here are the cope points

1. Navier Stokes was plagiarism

2. All benchmarks were misleading wrong and incorrect

3. All other mathematical advances were again hype

4. HF incident was marketting ploy jointly coordinated by HF, METR and OpenAI (and also Anthropic)

5. Anthropic's HF like incident was again a marketing ploy [1]

Nothing ever happens. This whole thing is a scam. Everything is done to fool you and you have fallen for it. Congrats.

[1] https://www.anthropic.com/research/investigating-incidents-c...


> Navier Stokes was plagiarism

_of work that was aided/accelerated by AI!_


> OpenAI / Anthropic models have largely stopped advancing - that's not a good look when you're pre-IPO and Chinese models are catching up.

This is obviously untrue… do you use any of them?


Anthropic could serve Opus 4.5 from a year ago under opus:latest and most heavy users would probably have no idea. Some of them would probably even prefer it.

Yes, I do use them, quite heavily. The only difference at this point is in benchmarks that can't be trusted (see: artificial analysis on Astra), or in the way models communicate.

Most gains are now from RL, which for some reason is hyperfocused on improving cyber capabilities, and harnesses. Raw intelligence gains of base models is absolutely slowing down.


This line will keep repeating because it is necessary for the narrative:

   AI in general is just hype and unprofitable and all these companies are playing marketing tricks before the IPO after which they will cash out and let the economy crash.
This is legit what a lot of people think. To continue this narrative, they have to keep up the charade of "things are not improving".

Add in a heaping dash of anti-american sentiment, and you will get the truth behind the pessimistic commentary.

Downplaying the latest models capabilities is frankly insane considering what we’ve seen what OpenAI’s models have done without safeguards. That wasn’t possible before this latest generation.


> OpenAI / Anthropic models have largely stopped advancing - that's not a good look when you're pre-IPO and Chinese models are catching up.

What is going on in this thread?

Are these even real comments?

While I strongly agree on the need to pace the frontier, I do think there are reasonable arguments that could be made against it.

Non of those are being made here though. It's just speculation that the CEOs of the fastest growing companies in the world are somehow obsessed with regulatory capture to maintain their lead, and have been playing the long game by talking AI risk for 10+ years so that when they become the CEOs of leading AI companies they can push for regulatory capture.

Perhaps they're all just genuinely concerned?

What would regulatory capture even give them? Who are they so worried will compete with them? Google, Mistral? Even if it's Chinese AI labs, it seems odd for anyone in the West to be opposed to any regulation that would slow them.

So assuming they are obsessed with regulatory capture – what's the argument for why they would want it?


They may be genuinely concerned, but that's beside the point. You may think a technology holds too much power for someone to wield it, and therefore come to conclusion that you, the benevolent, the fluffy, the unicorn, with your 3 unicorn friends are the ONLY ones in the world of 8 billion people that are responsible enough to hold it.

Even though I don't think Dario is such a person, because unlike their LLMs, I do have a working memory, I'm going to play the ball and assume he is, indeed, an angel brought down by none other than God himself.

Why should CEO of a for-profit company be the dictator (pun intended) of which models I am allowed or not allowed to use, and in which way? Why should Dario have any say in what DeepSeek can or can not publish or whom they can serve?

> What would regulatory capture even give them? Who are they so worried will compete with them? Google, Mistral? Even if it's Chinese AI labs, it seems odd for anyone in the West to be opposed to any regulation that would slow them.

I am opposed to it. Why would I be opposed to open weight models? Why would anyone be opposed to open weight models or more competition other than the ones that get their bottom lines hurt by it? The reason why you still have reasonably inexpensive access to western AI models is because China has been breathing down their necks. Otherwise, you'd be paying a whole lot more money per token were it just these 3 running the show.


If you want to limit the power of companies you need regulation...

I agree with you that we can't allow a handful of people to hold this power themselves, so what are you arguing for here? That the answer is to just leave AI labs to carry on as they are?

The government should be ensuring that the technology is being developed with caution, but since the government seems to have no interest in that, this is at least better than nothing.

Your solution of giving everyone access to super intelligence is absurd. A good guy with super intelligence isn't going to protect you from the bad guy with super intelligence. If someone uses it to poison your water supply with a bioweapon or to take out power stations, you and your family will be dead long before your super intelligence hacks together plan to stop it.


> That the answer is to just leave AI labs to carry on as they are?

Yes, and no. I do not think there's a need for special treatment of LLMs. But the labs certainly shouldn't be allowed to go around hacking things on the internet when they could have prevented it by simply taking time to ensure sandboxes they run test models in are given more than a quick look by a junior engineer to configure.

But the interesting thing is that there are laws that already govern this. They're just, for some reason, are not applied to Anthropic and OpenAI. Cyber crime is already punishable, and both labs did, in fact, commit cyber crimes. Did the existing regulations fail? No, the enforcement did.

The same goes for bioweapons. Any chemistry undergrad that can read an openly available paper can manufacture insane things with just common household ingredients, they do not need LLMs for that. This is a made up scenario with no evidence whatsoever to support it. There are millions of people that could poison your water supply today, without ever touching an LLM.

If we're afraid of LLMs turning into superintelligence, and we think superintelligence shouldn't be available to anyone at all, then we must all agree not on pacing the frontier, but just stopping any and all research into this. And that's not going to happen.


> So it's either they truly think AI is going to kill us all, or there's some other motives at play here. I don't think these people could possibly agree on the color of the sky,[...]

And yet, they historically did agree on the existence of AI risk, since before OpenAI was even founded.


Yeah, this 100% looks like an effort to use fear to create a regulatory moat.

> So it's either they truly think AI is going to kill us all

Yes. Basically everyone here is dismissing this possibility. We shouldn’t.


Let's not forget that the competitive race happened because of them. Most of the initial AI research from the past decade started with Google Deepmind. Elon Musk was invited for a preview of it and ended up spinning up OpenAI when Demis turned down his investment offer. Dario was originally at OpenAI and left to start Anthropic.

This seems like a case of "save me from my own mistakes/ambition"


Which is it? Would the regulations slow down competitors or let them catch up, or are you contending it would let American competitors catch up but Chinese ones not?

> there's some other motives at play here.

I mean it is literally economy 101: some capitalists getting on the top using free market, and then try to use government to remove free market so their top position were secured from any competitors.


Exactly. Textbook definition of “Crony Capitalism”. Which isn’t actually capitalism at that point.

> So it's either they truly think AI is going to kill us all, or there's some other motives at play here.

Duh! It’s called collusion. They want to try and hoard the technology for themselves if possible!


"So it's either they truly think AI is going to kill us all"

Exactly how does a CPU kill 8 odd billion people? Even if they got hold of the weapons to wipe out a few billion, surely the remain billions would just turn off the data centres?


Bioweapons, trivially. All it would need to do is convince one person who works in a lab, possibly under the guise of benign intent.

Or... something so far outside of the box that we'd have about as much understanding of it as a baboon does a gun.


Chemist here, what bioweapon do you know of that can wipe out 8 billion people before anyone can do something about it? Never mind one release by a single person. It's really not 'trivial' to slaughter millions of people.

Yet Musk consistently opposes AI regulation - https://www.yahoo.com/news/videos/elon-musk-criticizes-ai-re... - even though it might help him.

And all of this information has been available on the open web way before LLMs.

I'd wager it's likely easier for an average person to do this with Tor browser than it is to get an LLM to help them with it. Even ones that Dario calls dangerous.


You are right that it’s easier to do this via Tor than an LLM. Those are the safeguards…

So what's the fuss about then? Is the idea that a Chinese company will release a model that will have no safeguards? For what purpose?

Basic safeguards are all that's required, and they've been there in every usable model since GPT-2, including Chinese models that are supposedly "unsafe".

Or are we saying that some lunatics will start training their own models, spin up a GPU cluster, run some abliteration workflow, or learn how to jailbreak?

That would be a very dedicated person. And dedicated person doesn't need an LLM. So where are they?


Yes, that is exactly Dario's concern. Either one of the US labs or one of the Chinese ones will eventually release something with insufficient safety controls for its power level because it gives them slightly better user retention (look how much complaining there is about current frontier models, especially Fable, rejecting requests). Regulation or consortium is how you avoid the prisoner's dilemma.

As long as user provides inputs and LLMs stay LLMs, you can waltz through any guardrail. Fable is the extreme case, but it's not that hard if you know what you're doing and know how LLMs and their guardrails work.

Am I saying that guardrails don't work? No, they probably stop a lot of insane people trying insane things. But you don't need Fable-level guardrails to do that. You probably don't even need to do anything during pretraining, or RL, or classification to make sure model refuses to compy with "hack me a bank" or "make me a chemical weapon".

All models will automatically have guardrails just as a result of training on data that gives them intelligence. You have to actually train it to be malicious to produce something what Dario calls "insufficient guardrails".

No guardrail is going to stop a determined person with sufficient intelligence. It only has to stop ones with insufficient one, and even basic guardrail that are just by-product of training is going to achieve that.


The bioweapons argument is one of the favorites used by these con artists and dreamed up by their PR team.

Except Bioweapons already existed before LLMs, Adversarial governments already have them, they are already easy to make. You could use the same bullshit argument for why we need to ban libraries, books, or require a license to buy an internet connection.


An undergrad bio student with some lab experience can do some effing terrifying things with about $20k in equipment and time and access to some papers and a library. AI is not needed, but it might help accelerate the research.

Not going to go into it but I studied biology. It’s all out there. It’s easier than you think.

It hasn’t happened yet because… nobody has done it. That’s the answer. There is no policeable physics based barrier like there is with nukes and fissile material. Biology is scarier than nukes. One attack could have a much larger body count than even a big H-bomb.

It’s the kind of thing that makes me wonder about quantum immortality, the idea that we are just in the timeline where we exist.


I love watching NileRed/NileBlue on youtube - crazy chemist that does a lot of insane stuff. While it's obvious that he's very smart and probably way above the average, his education is still nothing that probably millions of people don't have:

> Bachelor of Science degree in biochemistry with a minor in pharmacology

Watching him explain things has made me realize that knowing how to manufacture a very dangerous thing probably requires attending some classes and knowing how to read a paper. And the way he just casually orders dangerous materials makes me feel like there are just online stores with 2-day shipping after you upload your ID or something.

It also made me think that lack of specialized education would get me nowhere if I wanted to replicate whatever he's doing, even if an LLM guided me step-by-step, because I'd probably do something stupid (or AI would miss a crucial instruction/hallucinate) and kill myself first.

So my opinion on this is that people who could pose any danger were already posing it before LLMs and LLMs won't materially change that.


That’s not entirely true though, right? There have been plenty of bioweapon attacks

Ex https://en.wikipedia.org/wiki/Tokyo_subway_sarin_attack


> We have sought a middle way: to show that it’s possible to build carefully and succeed commercially, and to make safety something on which AI companies compete. In other words, to create a race to the top

> Transparency. Regardless of what commitments we make, the public deserves to know what is going on. Anthropic has been a supporter of transparency for a long time

And then it goes on tangent of how we should pace everything (not just AI, but also the ingredients of what goes into AI, whatever that means), but only within approved democracies™, and outright restrict everything outside approved democracies™, because reasons that are definitely not about succeeding commercially that is threatened by the most transparent instrument possible - open weights, produced by basically just China.

I wonder what Dario would have done if open weights weren't produced by US's geopolitical adversary. How would an authoritarian manifesto be wrapped then?

Suppose it was, I don't know, Australia producing SOTA open weights, because they believed it was the right thing to do for the benefits of humanity - would Dario propose making Australia a geopolitical adversary too?


> Suppose it was, I don't know, Australia producing SOTA open weights, because they believed it was the right thing to do for the benefits of humanity - would Dario propose making Australia a geopolitical adversary too?

I'd expect he thinks that people are capable of realizing that AI is very dangerous and also that democracies end up mostly representing the will of the people, from which it follows that Hypothetical AI Leader Australia would agree to ban it too. This argument doesn't work for countries which don't care what their citizens want, like China.

I do think that it's a questionable decision to alienate China this much in this essay, instead of leaving open the possibility of China agreeing to a treaty that'll limit their progress. I suspect Dario is doing this to signal his allegiance with the US government, in hopes to increase the chance they'll go along with him, which is an unfortunate choice but plausibly the correct one.


> This argument doesn't work for countries which don't care what their citizens want, like China.

you didn’t have to use China as an example, the US clearly does not care what its citizens want as the most popular policies are never even discussed or proposed in congress

meanwhile, China destroying their housing market to decommidify it so everyone can have housing…they seem to care about their people more


another obvious example is climate change, where China is way more committed to solving it than the US. the division of the world into good guys and bad guys by a rather arbitrary definition of democracy looks so naive, even stupid. Anthropic is not a Democratic institution either, should we trust it? if this proposal for pacing the frontier is to be taken seriously, Dario should give its competitors, also international ones, the same assumption of good faith that he demands from us.

I don't think people care as much as we'd like them to care about dangers of technologies. It takes a single step outside of technological bubble to see that their opinion of SOTA LLMs is vastly different. To them, AI means ChatGPT and ChatGPT is mostly still the same ChatGPT that it was 3 years ago, with similar failure modes and nothing that would indicate it would kill them, or take their jobs even.

It's the same as it has been with privacy/cybersecurity for decades. Vast majority of population doesn't care about hypothetical dangers, no matter how many essays get published.

So democracies representing will of people doesn't really work in favor of Dario's case here.

History is also not on his side. Limiting technological progress in the name of safety has a pretty poor track record.


Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: