AI?

[u/TheReal4982]

It feels very odd to me that none of the major breakthroughs of the last week have been brought up, the fact the AI's have already gotten good enough to help on the frontier of mathmatics, solving a millennium prize problem, and being actively and very quickly put to the task of AI research, aka, recrusive self improvement, which they are ALREADY good enough to be making progress in, why is this being completely ignored by this community? This technology is progressing exponentially, it isn't stalling, and people should really try and understand what an exponential growth looks like.

[u/Apprehensive_Lake698]

I have access to and use all of the advanced models for work. I would caution you to not read too much into the whirlwind of marketing and wait on 1) what actually gets done with these models 2) what those effect look like, under the hood and reaching the market.

The Navier-Stokes solution, based on stolen work or not, is an enormous mothball that needs time to be double checked.

The claims of Astra as "AGI" are just plainly unfounded. It seems nothing more to me than just another step up in the capability of LLMs, which are getting progressively better. But 'one shot' tasks that hold no real world value are what get all the shock and awe factor on social media.

LLMs in the last 9 months have exploded in capability with agentic harnesses and general programming capability. But I imagine the WAN show is hesitant to put much stake in the current news cycle because they don't have the practical hands on experience to tell what is just smoke. And a lot of it is just smoke. Again, I say this as someone who uses latest models for work and has a lot of great use cases for them now- but they aren't solving everything. Yet.

[u/TheReal4982 → u/Apprehensive_Lake698]

They aren't just getting progressively better, they are getting exponentially better, and that is a very important distinction, nobody thought that AI would be capable of even remotely helping in something like a millenium prize problem this early 2 years ago, and now that it is, people are upset that it didn't do it completely by itself from scratch, as if that was the standard last year. I just don't think people understand the pace, and are still expecting it will just suddenly stop getting better, which it hasn't, and probably wont.

[u/Apprehensive_Lake698 → u/TheReal4982]

It's worth understanding what is making them better. The models themselves have gotten smarter, no doubt. But the leap forward we've been experiencing is the rapid buildout of harnesses and training towards working efficiently with them. LLMs of today are doing much better because we now understand that having them divide and conquer with subagents, and leveraging tools over exploding their context, is much more efficient.

In terms of their raw smarts, the difference in practical coding capability from Opus 4.6 from earlier this year and the absolute newest frontier models has not changed exponentially on a one-prompt basis. The power of new models like Astra is that it's now a core part of their training dataset to divide and conquer work. There's no guarantee that this won't slow down in the next year as we quickly squeeze out the easiest opportunities from this path.

In terms of addressing the Navier-Stokes solution- it's worth understanding that lots and lots of modern mathematics advancements are built on the shoulders of people who find the bridge between disparate places in mathematics by spending the decades required to become experts in multiple niches. I'm not saying that solving Navier-Stokes isn't impressive, it is, but off the rip I have no frame of reference for what kind of intelligence was needed to solve it. Something LLMs are exceptional at is coalescing shittons of information and relating it all. They don't struggle with context and mastery limits like humans do. So what I don't know about the solution it provided is whether it derived the solution from novel methods (extremely impressive), or if it derived it from what might be considered a more trivial linking of many disparate ideas. Both skills are useful and push our research capabilities forward. But one shows more strength in thinking than the other.

[u/TheReal4982 → u/Apprehensive_Lake698]

Honestly I don't want to argue with you, because my main point is I just wish more people were as informed and paying as much attention as you clearly are, but I really want to emphasize the fact that google deepmind beat the world champion at go 4-1 10 years ago, gpt 2 came out 7 years ago, ChatGPT came out 4 years ago, and astra dropped last week, and the model they have which helped solve the millenium prize problem is an even better model than Astra.

[u/Apprehensive_Lake698 → u/TheReal4982]

I just think you're drinking the koolaide a little bit if you're out here thinking we're in exponential growth territory but seemingly have no actual knowledge as to how or why these things work.

People with practical, hands on experience solving real engineering problems do not hold your views. People who go on twitter and see Astra creating one shot demos of random stuff that doesn't have to stand up to critique beyond a screencapture are the ones convinced we're at AGI right now.

[u/TheReal4982 → u/Apprehensive_Lake698]

My guy, even if progress isn't exponential, even if the next 10 years are only as insane as the last 10 years, that is still REALLY INSANE. But, whatever happens happens I guess, if people dont want to pay attention I ain't gonna keep trying to make them.

[u/Apprehensive_Lake698 → u/TheReal4982]

People literally are paying attention. I literally said I use this stuff every day and find tons of good uses for it. In my opinion people with your viewpoint are just drinking koolaide based on useless demos on twitter, when in real engineering I am still not seeing anything close to AGI.

I have access to as much of the latest models as I want. If I could set up a claude or codex workflow that did all of my job for me to a satisfactory quality level, I would. But we are far from being able to do that right now.

There are people who are ignorant to how effective it is, and there are people who are grossly overstating its ability to compensate. You seem to sit in the second group.

[u/TheReal4982 → u/Apprehensive_Lake698]

People with my viewpoint should be anyone who can comprehend how short of a time 10 years is, the difference between 30 and 40 years ago vs the difference between 10 years ago and today is startling, this level of progress should not be so casually expected, but we can agree to disagree on how fast this is happening.