> More likely (without careful vetting by the folks aggregating these models) is that the quality will go down as more and more AI-generated output gets subsumed into these models.

This assumes that there aren't algorithmic breakthroughs which reduce training/inference costs by several OOMs.

How much do these models need to do before people throw their hands in the air and say, ok this is happening. The Erdos unit distance problem, which as far as I understand was approached by multiple competent mathematicians was solved by a frontier model. Sure people argue there was no novelty there (I cannot comment as a non-mathematician) but it feels like they can draw lines laterally from deep knowledge in different fields (in this case combinatorics and algebraic number theory I believe) and solve problems.

Now if you have millions of instances running in parallel, all "probabilistic", working on frontier AI research I really don't see the blocker (and believe me I wish I did).

It’s no longer true that AI tools primarily get knowledge from their pre-training input data. That gives them a baseline, but nowadays AI chatbots and coding agents routinely assume they need to get up-to-date information in other ways, via web searches and other tool calling.

So I don’t see accuracy declining at least for programming.

> The only thing that matters is if LLMs with sufficient scaling can become frontier AI researchers kicking off the exponential

I agree with your sentiment (about the noise), however I think this over simplifies it a bit. We may get AI that is super-human at frontier research and dramatically accelerates the pace, and still have to wait decades before it disrupts the job market (or maybe never displaces all work).

For one, the answer may depend on material science and chip manufacturing that can take a very long to build out a supply chain for even with super AI help.

And we may just find that the human mind is way more capable than we thought and even with accelerating research it's just a harder problem than anyone expected, even algorithmically.

I expect it to be a bit of both, and from ~2015 - 2025 I was in the "AI is coming for all our jobs" camp. My perspective changed last year after doing a deep dive into latest science on the human brain. (I've kept a very close eye on AI dev progress for 12+ years.

It's important not to miss the fact that AI productivity was a useful excuse for companies looking to conduct layoffs. Did some companies buy the hype? Sure - but the biggest companies would have wanted that sweet stock price layoff bump anyways and AI was a readily available justification to get it.

> The only thing that matters is if LLMs with sufficient scaling can become frontier AI researchers kicking off the exponential.

I think we know the answer to that already - LLMs show no sign of improving intelligence and instead providers are going down the ‘agentic’ rabbit hole.

There are too many things missing, like a world model, understanding, and taste (in the sense of knowing what is good and what is not good).

Sure, but let’s not pretend that people treated the statements of these ceos as strategic messaging. People very clearly treated what Altman, Zuck, Amodei etc have been saying as predictions, and it hasn’t been until they’ve been proven wrong that people have started with the counter-narrative.

> The only thing that matters is if LLMs with sufficient scaling can become frontier AI researchers kicking off the exponential.

What if the answer is flatly: no? All that other stuff starts to matter a lot then.

Predicating your business decisions on a potential breakthrough that may never come is frankly insane. Imagine if at the dawn of the car industry Ford decided that it's actually a race to build the first flying car and nothing else matters.

It's a rather useful tool... and it absolutely has been overhyped repeatedly and sold as a panacea.

If you believe AI will 10x you're developers you've drunk the kool-aid, if you believe AI will have no impact on your developers then you're being stubbornly ignorant.

This is just based on Ramp’s data about their customers, but it seems that some companies are hiring more people after adopting AI?

https://econlab.substack.com/p/we-can-finally-say-ai-isnt-ki...

Now let’s see if there will be any real consequences for such reckless stupidity: my bet, nah.

Afer COVID and AI, the only buzzword left is WAR. Doesn't rhyme but we are well beyond funny.