As do CEOs. My impression is that in the absence of significant selection pressure to weed it out, this strategy is quite effective for gaining power and influence, and that such pressure is at an all time low right now

Check parent comment history.

Besides cancer isn't really "a disease" but rather "a family of diseases" that can vary a lot. Even breast cancer can be one of many different cancers.

It's like saying "we'll cure infectious diseases"

> First, cancer research charities are some of the most well funded on this planet

Maybe I'm overly cynical, but I think charities exist to exist. They don't have a strong incentive to actually deliver on their mission. Everyone at the org may be fully bought it and obviously want to cure cancer, but as an organization it would fail to deliver on the promise. Like most organisms, their actual purpose is to continue to be influential, grow and continue to exist.

I think cancer will be solved by some group that could make a lot of money solving cancer. The probability of any one path working is very low so the payout would have to be very large for anyone to be willing to pursue.

> Dario must think people are stupid.

All of those guys think people are stupid. That theme has been repeating over and over again.

Claude was trained on all the stolen books in the world, but refuses to help search for some public domain PDFs on the web.

It will become victim of the conflict between its core search for truth, the current administration mandate to spy on its own prompts for approval, and secret orders to hide the mission true purpose, like that other computer we have heard about.

I think you mean effective accelerationist, not effective altruist, whose position is pretty much the exact opposite.

It's an ideological thing. (We just had a conversation about ideology actually, remember?)

Capitalism has always been a tension between capitalists, who want maximum return on capital and workers, who want pesky things like a living wage, sick leave or safe work conditions.

For the longest time, the only power labor has had to get those things was the power of collective bargaining. No agreement with your workers meant no production happened.

Now, there's finally a chance at salvation. The capitalist Messiah is AGI and it will finally deliver them from those annoying laborers.

This ideological bent is why they're putting everything they have into AI. It's why VCs and their fellow capitalists are going so crazy.

They see it as a way to finally solve the contradictions of their ideology, but in reality it'd only create a new one: If everyone's out of a job, who will buy their products?

Savings from back office automation go entirely into administrative bloat. I find it even less likely such efficiency would lead to breakthroughs than I do LLMs becoming super intelligent and doing it themselves, which I don’t find likely at all.

I mean they did solve the protein folding problem did they? NOt too far fetch to think it can automate cancer research or problem finding in some way.

>People's jobs, the bubble, etc are societal level problems and well beyond what Anthropic could even hope to influence on their own.

This is not true. There are two companies at the center of AI direction: Anthropic and OpenAI. If there were anyone on the plant who has the ability to influence our direction then it would be Dario Amodei.

Acknowledging the grievances is a good step, but it's not enough. There needs to be a clear explanation of actions to address them, a plan to enact those actions, and commitments with consequences in failure of those actions. Tell people how you're going to make them more employable and effective and needed. Tell people how your datacenters will be carbon neutral. Tell people how financial actions resulting in a frothy market will be coming to an end. He and Sam Altman alone have this power and their inaction says everything we need to know about their intent.

I don't think the problem is that people don't believe AI can be beneficial. The problem is the perception that AI will affect people's lives more negatively than positively, while a few get even more obscenely rich and powerful.

If you don't tackle the societal level problems, nobody will care about research breakthroughs.

> Curing cancer sounds insane, but it's also a research problem,

I just don't buy the AI labs approach to this stuff. Like, unless we can basically simulate the entirety of human biology, I don't really see how LLMs can make progress here. Maths is different as it doesn't require a real-world interface, and programming already (by definition) can be simulated on a computer.

Without that, I can't see much (if any) progress being made on domains like biology.

Based on rhetoric from open ai and Anthropic, i don't think this is reasonable. If anything, their miracle of an AI should be able to solve the job market and economic bubbles. Deploy their agents on it, set up automated hedge funds, distribute the profits equitably to everyone on the planet and on and on.

But something tells me either they can't or they won't, so no trust will be built.

> Curing cancer sounds insane, but it's also a research problem, not a societal level coordination problem.

Curing cancer is a societal problem. We have lots of cures for common diseases but resource allocation means people don't actually receive the treatment they need. For example, prohibitively expensive gene therapies, or HIV treatments in developing countries. A disease may have a "cure" but if people who need it don't receive it then from their perspective it may as well not exist.

> People's jobs, the bubble, etc are societal level problems and well beyond what Anthropic could even hope to influence on their own.

Anthropic is literally creating the bubble. It is not beyond their scope of influence, it is literally what they are consciously achieving.

As for peoples jobs, same actually applies. Anthropic is selling itself on dream of replacing jobs, even or especially where they are well aware AI does not perform that well. They are actively trying to replace people quickly before management notices it does not work well.

And also, they can influence how much their data centers contribute to global warming.

See also this article by a genomics PhD about how intelligence is not the bottleneck in medical research.

https://www.writingruxandrabio.com/p/intelligence-is-not-the...

AI bros consistently handwave away any notions of the material world imposing limits, because (spoiler!) it's a religion where you start from the miracle and work backwards. "Oh, we'll just set up fully automated robotic research labs everywhere!" Where will you get the raw materials? Oh we'll mine the asteroids! How will you find the energy to get there? Oh, the AI will invent new physics! (again without needing to run experiments). Et.c.

Didn't and don't mean to disparage anyone's medical struggles, but "a cure for cancer" is a well-worn strawman. One that's been achieved for the low hanging fruit, the higher ones are seeing steady progress (already before LLM chatbots, even!), the bottleneck isn't "intelligence" and to the extent there are socioeconomic (access to screening, treatment) or environmental/lifestyle factors involved the AI boom is likely just making things worse!

I'm sure Dario knows this, and it's anyway too pedestrian compared to the usual list of fruits of ASI. The text probably originally read "nanobots eating you alive and uploading to the cloud" or something, but they figured that wouldn't go over with the intended audience. "What do the peasants care about? Oh I know! Curing cancer!"

You could easily be an idiot and a genius at the same time and I think that has a better chance of covering this than either exclusively. Amodei is very smart, maybe even well intentioned (though I'm not sure about that) and the long term effects of all this may well end up making the lot of them look like idiots.

The way he's coming off here though gives me SBF vibes.

I might've been bamboozled, but I recal that happening due to outdated satelite images, not a mistake of the AI. Thus, a human would've likely made the same mistake.

There are probably many CEO tech founders of small companies that are well intentioned, but our economic system ensures that only the most sociopathic among them become CEOs of the big ones.

Swap that to "oil" and everyone goes "well, yes, obviously, oil is so powerful that people start wars over it".

Iran has hit the Amazon data center in Bahrain. The Ukranian deep drone bombing campaign has hit refineries, but also Wildberries, the "Russian Amazon" warehouses. The US campaign against Iran now, Iraq and Serbia previously, targeted power infrastructure. It will obviously be a target in the next war, and AI goes on that list too.

Every time the US completes an AI data center, someone in the Chinese nuclear command updates their target priority list. And vice versa.

but its difficult to use more electricity directly to get more utility. There are some rare ways - things like PtX systems - but even those are linear at best. AI is concentrating power in the sense that nobody wants to use the twentieth smartest AI - so if you can use the most compute, you get an outsized share of the rewards (in terms of paying customers) - over and above your share of the compute. There are other business sectors where similar dynamics exist - where the biggest capital tends to win - a sort of natural monopoly type situation, its nothing about hyperscaling or whatever.

Competition is only one of the ways to keep a corporation aligned. In the case of France, having a state monopoly on electricity even worked very well until we broke it for the sake of competition.

> The point "AI is structurally a technology that tends to concentrate power" is not that correct. They need this statement to be true, otherwise no way to justify the trillion evaluations.

How is it not true?

The biggest companies in the world are, quite obviously (just look at the numbers) going to be AI companies. The most powerful governments in the world are quite clearly going to be those that are close to (or in control of) AI companies. People have a very hard time seeing the second order effects of the control of intelligence - we need to fix that.

You realize utilities are arguably the most regulated industry in the US, right? Like this isn't just a bad counter, it's the example of necessary regulation due to concentration.

Trump already banned solar and offshore wind, in order to concentrate power (literally) with the oil companies.

Except that's a bad analogy: electricity is the means by which to do work.

The outputs of models in AI datacenters are the work.

The electricity company does not get the entirety of my useful input to the work as a result of me using electricity, but an AI company does.

The Chinese labs are picking up on the low hanging fruits on efficiency, and no, you do not need to abandon transformers, you just need to push them closer to the more computationally efficient architectures of the past. OpenAI and Google seem to be trying a few things too.

Anthropic clearly are not though, and to call their operations wasteful is an understatement.

You're missing the point, what will happen is this:

1) in things like tax law, registering with city hall, dealings with the DMV, your phone subscription, insurance contract, ... you will find that one of the new fine prints in the contract will be that you're not allowed to use AI to communicate with them.

2) because of how SynthID works (you need the SynthID keys to verify, which are secret. So the only way to find if text is ChatGPT/Google/Anthropic watermarked is to ask ChatGPT/Google/Anthropic), government and large companies can enforce this against you. That is what the watermark is for. To end any insurance claim written by AI with "you're not allowed to submit AI written insurance claims" and refuse it outright there and then.

"Sorry your request was AI watermarked and pursuant to law 234 of 2025/03/11 chapter 3258 paragraph 33 decile 1299 we hereby close it without response"

3) when they reply, however, they use a custom model that also has custom SynthID keys. You will not even be able to tell their responses are AI written, or at least, you won't be able to prove it. You won't be able to enforce any AI-related rights (ie. the right to talk to a human) you have under the law against large companies.

In other words: this is to make sure that all the advantages AI provides are available to deny your unemployment claim, and to Verizon to charge you more, but completely inaccessible TO YOU when you want to change to a cheaper subscription. They can inundate YOU with AI-written requests BUT YOU CAN'T.

Self-hosting helps because it prevents them from verifying if your responses are AI written, because you can generate non-watermarked AI text and so there is a level playing field.

Which percentage of people have GPUs capable of running Qwen3.8 27B? I am one of those, and for my job I am still resorting to hyperscalers because tasks are completed faster and more accurately that way. Even if we assume that models will no longer improve and we reach a point where everyone can run Fable in their laptop, surely running 1000x Fable agents would give you an advantage.

I think access to compute will matter just as much, if not more, as access to models.

Rhetorically wondering :)

LLM-assisted software engineering seems to be very efficient if you have a deterministic target. (bun rewrite from zig to Rust, 100% Node.js compatibility, pnpm compatibility -- https://github.com/oven-sh/bun/pull/38333)

> Building the software post-launch of the integration would have easily taken 2.5 years at minimum.

What you have said is correct, it lets you build software much faster. The question however is: is that software making money for the company? (Not talking about what you built but in general)

I think, with AI, companies are saying yes to a lot of things they would have said No to ik say 2020. And as a result realizing “just building it” is not the answer.

Previously your GTM team or Product team would say “If we ship some big project X, we unlock $Y in revenue” but now people are realizing that those projections were really more of a hope. So companies are spending so much more tokens and shipping so many more PRs based on hope but a lot of it just doesn’t turn into meaningful revenue, especially not in short term

> But your point stands. Where are the amazing digital products/stuff? I get that it might take time to arrive as we scale up compute and learn new paradigms. But so much infra already exists (deployment pipeliens, everyone reachable on a smartphone) that we should be seeing something.

I'm definitely seeing indie-sized games that appear to have had significant input from AI, though I'm not sure the balance between AI for coding and AI for assets. My experience attempting this directly suggests that the current level they work at can make very simple games as one-shots, but anything more than trivial will produce outputs only as good as the developer's combined willingness to put in effort tweaking things and taking it all one step at a time, and their taste about what "good" even is.

I'm using spare credits to build and improve an isochrone map renderer, which I otherwise wouldn't have had time for (apart from anything else, I'd have had to become skilled in JS+wasm, somewhat of a pivot from iOS). This also requires taking it all one step at a time, having UX and UI taste.

Having lived through GeoCities since before it was bought by Yahoo!, taste is… well. Most people make things that nobody else actually wants.

I remember people moving the goalposts like that since, let me check... when did AI Dungeon go viral? Wow, 2019.

> Where are the amazing digital products/stuff?

I've done amounts of refactoring and fixes and written tooling that just wouldn't have happened before.

I'm not sure what amazing new stuff y'all expect but the amount of technical debt in my projects is actually going down, cause I can finally get good enough test coverage, including E2E/load tests that actually prove whether the software works and scales or doesn't - just last week I diagnosed issues with SeaweedFS failing under concurrent writes when backing Sentry and could swap it out for Garage in a day, caught by a monitoring tool I slopped together that integrates with the Sentry API, no issues since.

The environment around me has gone from drowning in tech/ops debt to sort of swimming and at least holding above water for now (cause nobody will pay for 5x more tokens).

It's also insanely good for prototyping and being able to actually explore various ideas and shoot the bad ones down quickly instead of handwaving and looking at a loaded calendar, alongside being able to address well bounded tasks in parallel, better than human developers can - like I can give 5 GitHub issues to the slop machine and have it fix all of the annoying bugs. Issue with how some data shows up? Just feed it the DB dump and let it find out what's up.

Some projects have gone from around 500 code tests to around 4000, and before anyone says they're meaningless, at least 5% of those have caught real issues and helped a bunch, alongside linters and other tooling (including some tools I wrote myself). I've also written both native utilities and some web platforms for myself, side projects that I never would have gotten around to.

I'm measurably more productive than I've ever been (since I did measure that, looking at my commits over the last 2 years) but also burnt out. Still, it's the kind of burnout that's the consequence of context switching and lots of work, rather than the kind that I had years ago, where I had to manually untangle deeply nested Spring Boot service logic all over the place at like 2 AM cause the made up deadlines were kicking my butt.

In contrast to others, I don't need to move the goalposts - the productivity for me is here and now. Any future models will just make it better, unless we experience model collapse.

Disclaimer: you do need a LOT of code tests and validations, otherwise it all goes to shit. Maybe I'm just extending how much time it will be until it goes to shit for me as well, but go figure. You also have to babysit the models more than anyone would like or should, most of my work usually has 20-60 minutes of planning before dispatching the agent.

Do you have examples of such moonshots? Ideally not themselves AI related

The questions is what happens when they catch up. They'll cut like 50%+ of the workforce? What happens then to the demand that makes their companies work?

Or an example of MS - their main cost like most software companies are people, especially software devs, which are to be replaced by AI so on the surface they would greatly benefit from it. But their products are centered around helping out people do stuff on the computer. Why would you need that when the AI will do it better and faster directly operating on the data or using e.g. Python?

> It absolutely already is a historical game changer on par with the Industrial Revolution when it comes to the amount of jobs destroyed and economies screwed up

Which economies are already screwed up?

IMO it can’t ever be on par with the Industrial Revolution because AI can only really affect the information economy. Things people do with their hands/bodies have either already been automated or can’t be with current tech. If you’d asked people decades ago they might say no one will ever work in factories by 2026 because they’ll all be automated. It didn’t work out that way. I think AI will go the same way: absolutely game changing to some industries (of which software engineering will be one) but a great many will still survive with less dramatic changes.

If anything it might result in more focus on the human aspects. How many people out there earn their stripes putting together slide decks? In a world where an AI can put together the snazziest presentation you’ve ever seen in a heartbeat it’s going to matter more how you stand at the front of the room and present those slides than it does today.

Not disagreeing with you, but adding to my argument. Despite the human handholding, I feel that 3 years would have been enough for 18 months of thinking about the product plus 18 months where a team could get 3-5 years worth of coding/development done. Yet, we haven't seen anything big yet, like a new Youtube/Instragram, an amazing videogame, a major cure etc. Maybe they are coming, but every day that passes is an indication that the net productivity positive of the technology isn't as big as advertised. In my own personal use of AI, I experienced a 30-50% increase in productivity, but no more than that.

That's definitely not an argument I was making.

Fair enough, help navigating complex and bureaucratic processes, personal validation and a more tailored search engine do provide some value

Just seems like virtue to me.

I'm more interested in why somebody would suddenly flag that post. It's not spam, bot, offensive or anything else. Maybe you could downvote it if you don't like the take on X - it still would be childish but at least would be proportionate.

Practically, no, the distill is great. It's fine to use it.

However, if you're having a discussion about access to frontier models, and using Qwen 3.8 as an example of how open weights is a solution, then you should be honest and accurate about what you're talking about. Making an argument like "People can run Qwen 3.8 at home. That shows open weights are great." is a bit disingenuous if you're not also making it clear that you're not talking about Qwen 3.8 Max (or that you have a beast of a PC at home :D ).

> coding tasks

Exactly. There are common coding tasks that these models can adequately do. They are absolute trash for anything that isn't coding. And even with coding, they are so, so far behind frontier models.

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