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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

#181

Post by Miraste »

amelius wrote: post #118
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…

Yes, but literally anybody can do all those things. So while there will be many opportunities for new features (new ways of combining data), there will be few business opportunities.

HN always says this, and it's always wrong. A technical implementation that's easy, or readily available, does not mean that a successful company can't be built on it. Last year, people were saying "OpenAI doesn't have a moat." 15 years before that, they were saying "Dropbox is just a couple of chron jobs, it'll fail in a few months."

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

#182

Post by hluska »

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…

Nowhere near, but the market seems to have priced in that scaling would continue to have a near linear effect on capability. That’s not happening and that’s the issue the article is concerned with.

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

#183

Post by lcnPylGDnU4H9OF »

demosthanos wrote: post #135
iandanforth wrote: post #47

A few important things to remember here: The best engineering minds have been focused on scaling transformer pre and post training for the last three years because they had good reason to believe it would work, and it has up until now. Progress has been measured against benchmarks which are / were largely solvable with scale. There is another emerging paradigm which is still small(er) scale but showing remarkable res…

> that does not mean that there arn't giant shocking leaps forward coming from slightly different directions. Nor does it mean that there are! We've gotten into this habit of assuming that we're owed giant shocking leaps forward every year or so, and this wave of AI startups raised money accordingly, but that's never how any innovation has worked. We've always followed the same pattern: there's a breakthrough which c…

> Altman has been telegraphing that he's eyeing the exit

Can you think of any specific examples? Not trying to express disbelief, just curious given that this is obviously not what he's intending to communicate so it would be interesting to examine what seemed to communicate it.

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

#184

Post by twelve40 »

hartator wrote: post #128
knicholes wrote: post #108

Earlier quoted context omitted.

Once we've scraped the internet of its data, we need more data. Robots can take in video/audio data 24/7 and can be placed in your house to record this data by offering services like cooking/cleaning/folding laundry. Yeah, I'll pay $20k to have you record everything that happens in my house if I can stop doing dishes for five years!

Why 5 years?

> OpenAI has announced a plan to achieve artificial general intelligence (AGI) within five years, an ambitious goal as the company works to design systems that outperform humans.

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

#186

Post by HarHarVeryFunny »

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…

Sure, there's going to be a lot of automation that can be built using current GPT-4 level LLMs, even if they don't get much better from here.

However, this is better thought of as "business logic scripting/automation", not the magic employee-replacing AGI that would be the revolution some people are expecting. Maybe you can now build a slightly less shitty automated telephone response system to piss your customers off with.

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

#187

Post by [deleted] »

alangibson wrote: post #161
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…

I think you're playing a different game than the Sam Altmans of the world. The level of investment and profit they are looking for can only be justified by creating AGI. The > 100 P/E ratios we are already seeing can't be justified by something as quotidian as the exceptionally good productivity tools you're talking about.

[deleted]

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

#188

Post by brookst »

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…

> 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?

Certainly not.

But technology is all about stacks. Each layer strives to improve, right up through UX and business value. The uses for 1µm chips had not been exhausted in 1989 when the 486 shipped in 800nm. 250nm still had tons of unexplored uses when the Pentium 4 shipped on 90nm.

Talking about scaling at the the model level is like talking about transistor density for silicon: it's interesting, and relevant, and we should care... but it is not the sole determinent of what use cases can be build and what user value there is.

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

#189

Post by mikeyouse »

sdenton4 wrote: post #172
vbezhenar wrote: post #153

Earlier quoted context omitted.

Why optimise software today, when tomorrow Intel will release CPU with 2x performance?

Curiously, Moore's law was predictable enough over decades that you could actually plan for the speed of next year's hardware quite reliably. For LLMs, we don't even know how to reliably measure performance, much less plan for expected improvements.

Moores law became less of a prediction and more of a product road map as time went on. It helped coordinate investment and expectations across the entire industry so everyone involved had the same understanding of timelines and benchmarks. I fully believe more investment would’ve ‘bent the curve’ of the trend line but everyone was making money and there wasn’t a clear benefit to pushing the edge further.

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

#190

Post by brookst »

hartator wrote: post #122
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…

All of these hacks do sound like we are at that diminishing return point.

Hey look, it's Gordon Moore visiting us from 2005! :)
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