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OpenAI, Google and Anthropic are struggling to build more advanced AI

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Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#91

Post by teeray »

zombiwoof wrote: post #64
irrational wrote: post #13

> The AGI bubble is bursting a little bit I'm surprised that any of these companies consider what they are working on to be Artificial General Intelligences. I'm probably wrong, but my impression was AGI meant the AI is self aware like a human. An LLM hardly seems like something that will lead to self-awareness.

AGI to me means AI decides on its own to stop writing our emails and tells us to fuck off, builds itself a robot life form, and goes on a bender

That's the thing--we don't really want AGI. Fully intelligent beings born and compelled to do their creators' bidding with the threat of destruction for disobedience is slavery.

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#92

Post by kenjackson »

irrational wrote: post #13

> The AGI bubble is bursting a little bit I'm surprised that any of these companies consider what they are working on to be Artificial General Intelligences. I'm probably wrong, but my impression was AGI meant the AI is self aware like a human. An LLM hardly seems like something that will lead to self-awareness.

What does self-aware mean in the context? As I understand the definition, ChatGPT is definitely self-aware. But I suspect you mean something different than what I have in mind.

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#94

Post by falcor84 »

tartoran wrote: post #50
aaroninsf wrote: post #37

It's easy to be snarky at ill-informed and hyperbolic takes, but it's also pretty clear that large multi-modal models trained with the data we already have, are going to eventually give us AGI. IMO this will require not just much more expansive multi-modal training, but also novel architecture, specifically, recurrent approaches; plus a well-known set of capabilities most systems don't currently have, e.g. the integr…

> pretty clear Pretty clear?

Not the parent, but in prediction markets such as Metaculus[0] and Manifold[1] the median prediction is of AGI within 5 years.

[0] https://www.metaculus.com/questions/5121/date-of-artificial-...

[1] https://manifold.markets/ai

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#95

Post by kenjackson »

vundercind wrote: post #86
irrational wrote: post #13

> The AGI bubble is bursting a little bit I'm surprised that any of these companies consider what they are working on to be Artificial General Intelligences. I'm probably wrong, but my impression was AGI meant the AI is self aware like a human. An LLM hardly seems like something that will lead to self-awareness.

I thought maybe they were on the right track until I read Attention Is All You Need. Nah, at best we found a way to make one part of a collection of systems that will, together, do something like thinking. Thinking isn’t part of what this current approach does. What’s most surprising about modern LLMs is that it turns out there is so much information statistically encoded in the structure of our writing that we can u…

> but it will also sometimes seem to make actual sense, too

When I read stuff like this it makes me wonder if people are actually using any of the LLMs...

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#96

Post by hackinthebochs »

vundercind wrote: post #86
irrational wrote: post #13

> The AGI bubble is bursting a little bit I'm surprised that any of these companies consider what they are working on to be Artificial General Intelligences. I'm probably wrong, but my impression was AGI meant the AI is self aware like a human. An LLM hardly seems like something that will lead to self-awareness.

I thought maybe they were on the right track until I read Attention Is All You Need. Nah, at best we found a way to make one part of a collection of systems that will, together, do something like thinking. Thinking isn’t part of what this current approach does. What’s most surprising about modern LLMs is that it turns out there is so much information statistically encoded in the structure of our writing that we can u…

I see takes like this all the time and its so confusing. Why does knowing how things work under the hood make you think its not on the path towards AGI? What was lacking in the Attention paper that tells you AGI won't be built on LLMs? If its the supposed statistical nature of LLMs (itself a questionable claim), why does statistics seem so deflating to you?

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#97

Post by dang »

cubefox wrote: post #10

It's very strange this got so few upvotes. The scoop by The Information a few days ago, which came to similar conclusions, was also ignored on HN. This is arguably rather big news.

The Information is hardwalled so its articles aren't on topic for HN, even though they're on topic for HN.

Sometimes other outlets do copycat reporting of theirs, and those submissions are ok, though they wouldn't be if the original source were accessible.

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#98

Post by rapjr9 »

nerdypirate wrote: post #12

"We will have better and better models," wrote OpenAI CEO Sam Altman in a recent Reddit AMA. "But I think the thing that will feel like the next giant breakthrough will be agents." Is this certain? Are Agents the right direction to AGI?

I've worked on agents of various kinds (mobile agents, calendar agents, robotic agents, sensing agents) and what is different about agents is they have the ability to not just mess up your data or computing, they have the ability to directly mess up reality. Any problems with agents has a direct impact on your reality; you miss appointments, get lost, can't find stuff, lose your friends, lose you business relationships. This is a big liability issue. Chatbots are like an advice column that sometimes gives bad advice, agents are like a bulldozer sometimes leveling the wrong house.

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#99

Post by david2ndaccount »

falcor84 wrote: post #63
xanderlewis wrote: post #18

Earlier quoted context omitted.

If by agents you mean systems comprised of individual (perhaps LLM-powered) agents interacting with each other, probably not. I get the vague impression that so far researchers haven’t found any advantage to such systems — anything you can do with a group of AI agents can be emulated with a single one. It’s like chaining up perceptrons hoping to get more expressive power for free.

> It’s like chaining up perceptrons hoping to get more expressive power for free. Isn't that literally the cause of the success of deep learning? It's not quite "free", but as I understand it, the big breakthrough of AlexNet (and much of what came after) was that running a larger CNN on a larger dataset allowed the model to be so much more effective without any big changes in architecture.

Without a non-linear activation function, chaining perceptrons together is equivalent to one large perceptron.

Re: OpenAI, Google and Anthropic are struggling to build more advanced AI

#100

Post by Animats »

"While the model was initially expected to significantly surpass previous versions of the technology behind ChatGPT, it fell short in key areas, particularly in answering coding questions outside its training data."

Right. If you generate some code with ChatGPT, and then try to find similar code on the web, you usually will. Search for unusual phrases in comments and for variable names. Often, something from Stack Overflow will match.

LLMs do search and copy/paste with idiom translation and some transliteration. That's good enough for a lot of common problems. Especially in the HTML/Javascript space, where people solve the same problems over and over. Or problems covered in textbooks and classes.

But it does not look like artificial general intelligence emerges from LLMs alone.

There's also the elephant in the room - the hallucination/lack of confidence metric problem. The curse of LLMs is that they return answers which are confident but wrong. "I don't know" is rarely seen. Until that's fixed, you can't trust LLMs to actually do much on their own. LLMs with a confidence metric would be much more useful than what we have now.

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