> I don't see this getting better.

We went from 2 + 7 = 11 to "solved a frontier math problem" in 3 years, yet people don't think this will improve?

I’ve seen this style of take so much that I’m dying for someone to name a logical fallacy for it, like “appeal to progress” or something.

Step away from LLMs for a second and recognize that “Yesterday it was X, so today it must be X+1” is such a naive take and obviously something that humans so easily fall into a trap of believing (see: flying cars).

Scaling law is a power law , requiring orders of magnitude more compute and data for better accuracy from pre-training. Most companies have maxed it out.

For RL, we are arriving at a similar point https://www.tobyord.com/writing/how-well-does-rl-scale

Next stop is inference scaling with longer context window and longer reasoning. But instead of it being a one-off training cost, it becomes a running cost.

In essence we are chasing ever smaller gains in exchange for exponentially increasing costs. This energy will run out. There needs to be something completely different than LLMs for meaningful further progress.

I tend to disagree that improvement is inherent. Really I'm just expressing an aesthetic preference when I say this, because I don't disagree that a lot of things improve. But it's not a guarantee, and it does take people doing the work and thinking about the same thing every day for years. In many cases there's only one person uniquely positioned to make a discovery, and it's by no means guaranteed to happen. Of course, in many cases there are a whole bunch of people who seem almost equally capable of solving something first, but I think if you say things like "I'm sure they're going to make it better" you're leaving to chance something you yourself could have an impact on. You can participate in pushing the boundaries or even making a small push on something that accelerates someone else's work. You can also donate money to research you are interested in to help pay people who might come up with breakthroughs. Don't assume other people will build the future, you should do it too! (Not saying you DON'T)

The problem class is rather very structured which makes it "easier", yet the results are undeniably impressive

LLMs in some form will likely be a key component in the first AGI system we (help) build. We might still lack something essential. However, people who keep doubting AGI is even possible should learn more about The Church-Turing Thesis.

https://plato.stanford.edu/entries/church-turing/

But can it count the R's in strawberry?

if you let million monkeys bash typewriter. something something book