Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

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

bloomberg.com

Post reply on HN
Print view View original

281–290 of 622 posts

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

#281

Post by mtkd »

pluc wrote: post #43

They've simply run out of data to use to fabricate legitimate-looking guesses. They can't create anything that doesn't already exist.

And that is potentially only going to worsen as:

1. more data gets walled-off as owners realise value

2. stackoverflow-type feedback loops cease to exist as few people ask a public question and get public answers ... they ask a model privately and get an answer based on last visible public solutions

3. bad actors start deliberately trying to poison inputs (if sites served malicious responses to GPTBot/CCBot crawlers only, would we even know right now?)

4. more and more content becomes synthetically generated to the point pre-2023 physical books become the last-known-good knowledge

5. goverments and IP lawyers finally catch up

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

#282

Post by JumpCrisscross »

HarHarVeryFunny wrote: post #257
JumpCrisscross wrote: post #192

Earlier quoted context omitted.

> level of investment and profit they are looking for can only be justified by creating AGI What are you basing this on? IT outsourcing is a $500+ billion industry. If OpenAI et al can run even a 10% margin, that business alone justifies their valuation.

It seems you are missing a lot of "ifs" in that hypothetical! Nobody knows how things like coding assistants or other AI applications will pan out. Maybe it'll be Oracle selling Meta-licenced solutions that gets the lion's share of the market. Maybe custom coding goes away for many business applications as off-the-shelf solutions get smarter. A future where all that AI (or some hypothetical AGI) changes is work being…

> you are missing a lot of "ifs" in that hypothetical

The big one being I'm not assuming AGI. Low-level coding tasks, the kind frequently outsourced, are within the realm of being competitive with offshoring with known methods. My point is we don't need to assume AGI for these valuations to make sense.

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

#283

Post by nomel »

nuancebydefault wrote: post #206
swatcoder wrote: post #74

Earlier quoted context omitted.

On the contrary, I think you're conflating the narrow jargon of the industry with what "most people" would define. "Most people" naturally associate AGI with the sci-tropes of self-aware human-like agents. But industries want something more concrete and prospectively-acheivable in their jargon, and so that's where AGI gets redefined as wide task suitability. And while that's not an unreasonable definition in the cont…

There is no single definition, let alone a way to measure, of self awareness nor of reasoning. Because of that, the discussion of what AGI means in its broadest sense, will never end. So in fact such AGI discussion will not make nobody wiser.

I agree there's no single definition, but I think they all have something current LLM don't: the ability to learn new things, in a persistent way, with few shots.

I would argue that learning is The definition of AGI, since everything else comes naturally from that.

The current architectures can't learn without retraining, fine tuning is at the expense of general knowledge, and keeping things in context is detrimental to general performance. Once you have few shot learning, I think it's more of a "give it agency so it can explore" type problem.

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

#284

Post by HarHarVeryFunny »

famouswaffles wrote: post #216
HarHarVeryFunny wrote: post #162

Earlier quoted context omitted.

Obviously adding more data is a game of diminishing returns. Going from 10% to 50% (500% more) complete coverage of common sense knowledge and reasoning is going to feel like a significant advance. Going from 90% to 95% (5% more) coverage is not going to feel the same. Regardless of what Altman says, its been two years since OpenAI released GPT-4, and still no GPT-5 in sight, and they are now touting Q-star/strawberr…

>Regardless of what Altman says, its been two years since OpenAI released GPT-4, and still no GPT-5 in sight. It's been 20 months since 4 was released. 3 was released 32 months after 2. The lack of a release by now in itself does not mean much of anything.

By itself, sure, but there are many sources all pointing to the same thing.

Sutskever, recently ex. OpenAI, one of the first to believe in scaling, now says it is plateauing. Do OpenAI have something secret he was unaware of? I doubt it.

FWIW, GPT-2 and GPT-3 were about a year apart (2019 "Language models are Unsupervised Multitask Learners" to 2020 "Language Models are Few-Shot Learners").

Dario Amodei recently said that with current gen models pre-training itself only takes a few months (then followed by post-training, etc). These are not year+ training runs.

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

#286

Post by devit »

It seems obvious to me that Common Crawl plus Github public repositories have more than an enough data to train an AI that is as good as any programmer (at tasks not requiring knowledge of non-public codebases or non-public domain knowledge).

So the problem is more in the algorithm.

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

#287

Post by in_a_society »

thousand_nights wrote: post #15

not long ago these people would have you believe that a next word predictor trained on reddit posts would somehow lead to artificial general superintelligence

Expecting AGI from Reddit training data is peak "pray Mr Babbage".

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

#288

Post by nomel »

layer8 wrote: post #146
nomel wrote: post #77

Earlier quoted context omitted.

> than a self aware entity. What does this mean? If I have a blind, deaf, paralyzed person, who could only communicate through text, what would the signs be that they were self aware? Is this more of a feedback loop problem? If I let the LLM run in a loop, and tell it it's talking to itself, would that be approaching "self aware"?

Being aware of its own limitations, for example. Or being aware of how its utterances may come across to its interlocutor. (And by limitations I don’t mean “sorry, I’m not allowed to help you with this dangerous/contentious topic”.)

> Or being aware of how its utterances may come across to its interlocutor.

I think this behavior is being somewhat demonstrated in newer models. I've seen GPT-3.5 175B correct itself mid response with, almost literally:

>

> Wait, that's not right, that .

> .

Later models seem to have much more awareness of, or "weight" towards, their own responses, while generating the response.

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

#289

Post by kenjackson »

23B1 wrote: post #218
LASR wrote: post #115

Question for the group here: do we honestly feel like we've exhausted the options for delivering value on top of the current generation of LLMs? I lead a team exploring cutting edge LLM applications and end-user features. It's my intuition from experience that we have a LONG way to go. GPT-4o / Claude 3.5 are the go-to models for my team. Every combination of technical investment + LLMs yields a new list of potential…

The user interface for LLMs is stuck in C:\ That's where I'd focus.

Voice for LLMs is surprisingly good. I'd love to see LLMs used in more systems like cars and in-home automation. Whatever cars use today and Alexa in the home simply are much worse than what we get with ChatGPT voice today.

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

#290

Post by moogly »

LASR wrote: post #115

Question for the group here: do we honestly feel like we've exhausted the options for delivering value on top of the current generation of LLMs? I lead a team exploring cutting edge LLM applications and end-user features. It's my intuition from experience that we have a LONG way to go. GPT-4o / Claude 3.5 are the go-to models for my team. Every combination of technical investment + LLMs yields a new list of potential…

> you can have LLMs create reasonable code changes

Could you define "code changes" because I feel that is a very vague accomplishment.

Post reply on HN