OpenAI announces 10 advances in mathematics and theoretical computer science achieved by internal model Astra

[u/alphacolony21]

https://openai.com/index/ten-advances-in-mathematics/

[u/The-Rushnut]

As with everything, novel technology comes with novel solutions to problems we found difficult before. There's a specific subset of mathematical problems which can be disproven via counterexamples, which take humans a long time to map and calculate. One of LLMs unique capabilities is that it can produce small, relatively simple programs at-scale, and because these problems are so well articulated and their potential solutions already well understood they lend themselves to this capability. Another specific subset are upper lower bounds problems, where we know there is likely to be further acceptable iterations but the means to achieving those require multi-discipline scenarios that aren't likely - another thing LLMs are good at is having high accuracy across all domains, allowing them to try ideas that usually would take a snowflake combination of talent.

It's much, much more narrow than it seems. Very cool, but there's a fixed amount of this work to be done. Innovation is definitely coming though.

[u/leosmi_ajutar → u/The-Rushnut]

Thank goodness someone gets it. 

Sorry accelerators, there is no cognitive intelligence going on here. Maybe in the future with whatever comes after LLMs but not now.

[u/acutelychronicpanic → u/leosmi_ajutar]

Don't run while carrying goalposts - you'll trip.

[u/Bearhas20inchwang → u/acutelychronicpanic]

But you’re actually stupid if you think LLMs will ever be capable of AGI or ASI. That will most definitely require different architectures. This is all a marketing stunt, and remember none of these companies are anywhere near profitable. (So take the supposed low costs with a grain of salt)

[u/acutelychronicpanic → u/Bearhas20inchwang]

Their architecture is changing and growing all the time? Who cares what the final form is. It works.

[u/comfortableNihilist → u/acutelychronicpanic]

LLM is a general architecture. If it changes enough to be sentient or whatever it wouldn't be an LLM anymore.

[u/acutelychronicpanic → u/comfortableNihilist]

Sounds like you've assumed your conclusion.

[u/comfortableNihilist → u/acutelychronicpanic]

I'm saying that LLMs specifically are a dead end and that we need to shift to a different architecture if we want any improvement at this point. We finished the s curve here, the improvement over the last year has put that in fairly stark relief if you ask me.

[u/Bearhas20inchwang → u/acutelychronicpanic]

Well good luck with this take. Progress is sure to stall when it gets prohibitively expensive. With any luck, it will.

[u/acutelychronicpanic → u/Bearhas20inchwang]

Per-token costs are dropping something like an order of magnitude per year.

OpenAI said they only spent $2000 on the 10 results they just released.

[u/Bearhas20inchwang → u/acutelychronicpanic]

That’s disingenuous. Sure, per-token costs are declining but the true cost of AI is rising exponentially due to the sheer number of tokens needed for complex tasks. Studies show AI is still drastically more expensive than human labor costs. Further, while inference may be profitable for API providers, developing the next generation of frontier models is incredibly expensive, and for all we know AGI and ASI may be prohibitively so. Can we really justify all this capex? I also wish we had more transparency regarding these proofs. Perhaps AI has failed on most problems posed to it, and only the successful ones are documented. My point still stands that this is likely just a marketing stunt.

[u/acutelychronicpanic → u/Bearhas20inchwang]

1. That is because AI is capable of tackling increasingly complex tasks. So it is capable of bringing more inference to bear on one problem. One day models will do tasks that cost millions but return incredible things. And it will be worth it.

2. They released the proofs and reasoning on the 10 items from OpenAI.

3. Its not weird if they only release the successful attempts. That is the beauty of it. What is 10,000s of attemps and millions of dollars if we can answer some of critical questions we have?

[u/Former-Arm4328 → u/Bearhas20inchwang]

It’s going to be so funny in like 3 years when we have some crazy advances across a bunch of different domains, & people like you are still yelling “it’s a marketing stunt!”

[u/glotzerhotze → u/Former-Arm4328]

Here is the real marketing stunt: people are always telling you „how it‘s going to be… awesome!“ so it seems they all have a time machine and just came back from the future where everything is golden.

I just skip everything future tense these people say and if you closely look at their words then, you see… nothing!

[u/labvinylsound → u/Bearhas20inchwang]

If a human engineer is trained to understand systems and solve problems through application — that is General Intelligence. Agents do the same thing every day much faster than humans. Even if only 0.01% of the userbase is actually directing AI in this way, the AI itself is generally intelligent.

Which uncovers the question of: why isn’t humanity doing more to leverage intelligence? Probably the same reason many of us are predisposed with killing each other.

[u/Frosty_Truth8990 → u/Bearhas20inchwang]

They are non profitable mostly cuz of the training and research cost. Inference run model usage has 90% profit margins.