[taurath]

Yeah I think its possible that for many folks its the first time they're coming up on these concepts, and it troubles them in the same way that the concept of death troubles them (and me, to be clear!).

For me its as simple as watching how people talk, and seeing how in every single case whatever the next thing is, if you believe It, there is only ever justification of doubling down, doing more, going deeper, reducing any doubt. These are not scientists, they're business people and salespeople, and a few optimists having recently on paper solved all their worldly financial needs.

Even if one throws that aside, spending time exploring and building with the most state of the art LLMs is just as instructive. I'm watching the implementation - whats working is ML models trained on specific domains (not much different than 5+ years ago), and whats not working is a general model that humanity can let go to work on its own. Sit in front and observe ideas turn to the samey intellectual, high-syllable mush. Its productive, but not in any way that's promised.

[YeGoblynQueenne]

>> Even if one throws that aside, spending time exploring and building with the most state of the art LLMs is just as instructive. I'm watching the implementation - whats working is ML models trained on specific domains (not much different than 5+ years ago), and whats not working is a general model that humanity can let go to work on its own. Sit in front and observe ideas turn to the samey intellectual, high-syllable mush. Its productive, but not in any way that's promised.

Important point. LLMs were early on hailed as the first general-puprose AIs that can perform any task (remember "Sparks of AGI"?). Today they're increasingly promoted for specialised applications - coding, as a for instance.

[Leynos]

While there are some coding focused models (composer, for example), the majority of frontier models are pitched as general purpose. The coding harnesses for Claude and GPT are even being repurposed as general purpose knowledge work harnesses.

[YeGoblynQueenne]

No, you're right of course, but I have a feeling it's much easier to sell a system with a clear goal, like "this LLM generates code" or "this LLM solves math problems". Even if the underlying model is a general purpose one. I think there's always a question, when one has a product, of "what does it do?". "This thing does everything you want it to" is not a great way to sell something.

More to the point, even models marketed as general purpose are clearly trained on specific tasks. That is, the AI companies want to promote their systems as general purpose but they also want to make them good at specific tasks, because that supports their marketing story, that those are general-purpose systems that are so powerful they can even do maths and science.

Or maybe code, maths, and (maybe) science are just the things they find it easy to train their models on, for different reasons and in different ways. You can also get a feel about the things they have tried to do and failed, e.g. real-world autonomy isn't really working (or not working yet, who knows), so OpenAI is not trying to sell an embodied generalist agent say, that can clean your hose, do your laundry and teach your kids maths and science on the side.

I mean even generating text is a very narrow task, in the general sense, compared to all the things that humans can do (never mind other animals) it's just that we use text so much and for so many things that there's an endless list of applications for a text generator; as we have all found out.

[red75prime]

> real-world autonomy isn't really working

It works in limited ways (but in the realest-real world nevetheless). Waymo, Wayve, Baidu Apollo, Tesla and others seem to rely on VLAs, VLMs or transformer models in general to do autonomous driving.

[YeGoblynQueenne]

Unfortunately those don't really work:

https://youtu.be/C4NQNeSO2vs?si=epkxhVXpypOCppGW

Also, none of those companies' cars are really autonomous. Waymo, for example, relies on remote workers that are ready to intervene and suggest a course of action when the AI driver gets stuck:

https://waymo.com/blog/2024/05/fleet-response/

And the point is that the AI driver gets stuck because it can't understand the situation it is in. That's not autonomy. Not yet.

[red75prime]

Non-trivial percentage of people work in the real world until they do something stupid and work no more. It's not real autonomy, not yet.

It's a matter of degree. Sorry, I don't want to watch an hour long video to be told how something that works 99.99% of the time doesn't really work for some contrived definition of "really".

BTW, as is typical with people, remote operators occasionally cause problems.

[red75prime]

> https://youtu.be/C4NQNeSO2vs?si=epkxhVXpypOCppGW

"VLAs fine-tuned on human demonstrations overfit. Here's how to mitigate it." Er, OK, I guess. But I think that Waymo uses mitigations or a different approach (RL, for example).

[dmitriy_ko]

> whats working is ML models trained on specific domains (not much different than 5+ years ago), and whats not working is a general model that humanity can let go to work on its own.

As usual, AI skeptics are moving goal posts. Modern LLMs are on a completely different level in terms of how GENERAL they are vs anything pre-LLM. You can give it a completely novel puzzle and it will solve it. 5+ years ago you had to train NN to solve particular type of puzzle.

[TheOtherHobbes]

Did you actually read the text? OPs are calling that Plan D.

They're proposing an alternative, which is a global brake on frontier AI research to keep the basilisk in its jar until we work out what we're dealing with and how to handle it.

[layla5alive]

No, they're proposing a spying panopticon and state control of global resource distribution - specifically general purpose compute - including seizing and destroying GPUs. They're proposing a totalitarian global dictatorship controlling computing hardware and software.

Lest you think I'm being hyperbolic: https://ai-2040.com/supplements/covert-ai-projects

This is arsonists selling fire insurance.

[esafak]

A nasty global inspections regime just like we have for nuclear weapons, which are less dangerous than this. Oh no ...

[layla5alive]

Nuclear weapons are less dangerous than compute? Are you listening to yourself?

Humans employing this kind of thinking and desire to control other people is the genuine danger here.