So now it's just a question of, do you sit on your advances or release them? Why would sitting on them be the 'right thing'?
AI has made strides in programming, but mainly in web development (which nowadays is the largest market), but there are other more demanding areas like embedded development where they'd find plenty of signal.
The promised "drop-in replacement remote worker" also requires a lot more capability than these models currently have, albeit more qualitative - architecturally based - than quantitative, so out of reach for now.
It seems OpenAI are trying to promote frontier math capability as relevant to the commercial market for AI, which it is not (something like Jev, much less glamorous, is much more relevant), and most businesses not only have no use for anything remotely approaching this level of math ability, but also more generally have no need for expensive frontier models which constitute a small percentage of revenue for the AI companies.
If it's investors rather than customers that OpenAI are trying to impress with math results, then I think they are wasting their time - investors are increasingly worried about AI revenue and the financial viability of the business as currently structured, with OpenAI looking like the least connected to reality.
AI is in some ways still a technology looking for applications, at least applications with a large enough commercial market to justify the valuations these companies are seeking. The answer is not math.
And you seem to be confusing the immediate commercial value of a particular math reuslt with the commercial value of a system capable of producing original math research. Thise are 2 different things, and the latter is worth a lot of money.
>AI is in some ways still a technology looking for applications, at least applications with a large enough commercial market to justify the valuations these companies are seeking.
These companies already have the fundamentals they need to justify current valuations. ~1T is nothing to a company that has over 1.2B+ weekly users (and growing) and is entering the ad space, nevermind everything else. What they are hoping to achieve will give them power akin to nation states. Current Valuations would be nothing compared to that.
I'd agree, although I doubt you'll like my framing: it's a commodity business - a race to the bottom on cost of production and pricing
> commercial value of a system capable of producing original math research
I'm not sure if you're claiming a market for original math research, large enough to be more than a distraction, or perhaps you are imagining AGI will emerge from pursuing the problems that mathematicians have set for themselves?
> 1T is nothing to a company that has over 1.2B+ weekly users
Sounds like they are wishing for a return of the dot com era where companies are valued on eyeballs rather than revenue growth
> and is entering the ad space
Good luck with that. Let's see how much ad revenue OpenAI can take away from Google and Meta. The ad-serving product better be free, since the competition is.
> What they are hoping to achieve will give them power akin to nation states
Sure that's what they are hoping. That customers will be spending trillions on their commodity product, but the question is what is the product? Decision models? Free chatbots? Coding agents competing with free weight models unencumbered by development cost? Does OpenAI envisage a trillion dollar market for Terrance Tao automation?
>Coding agents competing with free weight models unencumbered by development cost?
Prices falling doesn't mean a market dissapears. Compute, Bandwidth and Storage requirements have already undergone reductions orders of magnitudes in the last few years and consumption has only exploded. The vast majority of customers, consumer and enterprise alike do not give a shit about open weight models. I have no idea why people here think they do. If they pull ahead significantly enough then they might attract people by value of the amazing service they're providing (nothing to do with open weights).
If they're just going to be playing catchup then they're not gong to gain any signifcant share no matter how free model dev costs become. This is just not how customers work. They're sticky. They value reliability and familiriality and simply having something that works. If you want to unseat google search then you need something so far better people start talking crazy about it. Creating Bing won't do shit even if it's the default search engine on your default browser (you'll just change it).
>I'm not sure if you're claiming a market for original math research, large enough to be more than a distraction, or perhaps you are imagining AGI will emerge from pursuing the problems that mathematicians have set for themselves?
The economic output of math research is very often something other than mathematics. It's not about the market for math papers.
When you see stuff like this
>> Earlier in the year, we had largely handwritten the first version of the git-to-Scion ingestion pipeline as a prototype. We thought it was good—until we got our hands on an early internal snapshot of Claude Mythos Preview. We asked it to rewrite the whole thing, and with no further instructions, it produced a version that consumed 20x less memory and was 4x faster, while preserving all of the implicit invariants around ingestion ordering and data structures.
Do you imagine the gaining advances in math competence had nothing to do with it ? I'm telling they'd be well justified even if their only customer was themselves.
>Good luck with that. Let's see how much ad revenue OpenAI can take away from Google and Meta. The ad-serving product better be free, since the competition is.
They hit $1B in annualized ad revenue run rate ~200 days after launch. They'll be just fine. That you think they might have any trouble taking away or generating their own ad revenue is quite bizarre. If the metrics are good businesses will pay hand over fist, and it seems to me that OpenAI should have a much more complete profile of their median user than Facebook or Google.
>Coding agents competing with free weight models unencumbered by development cost?
The utility of frintier agets isn't remotely limited to software developers. Whoever cracks marketing for agents towars non software professionals will make a lot of money.
Yes - I would expect that the models' coding competence came from being trained to code, not being trained to do math.
There is very little cross-domain generalization from RLVR training, which is why they need thousands of simulation environments. The models are memorizing how to reason in specific domains/situations.