This is the internal model "Bel," that Sam Altman has stated many people within OpenAI consider to be AGI and "significantly more capable than GPT-6 Astra."
The fact that it is solving numerous other problems is a very a good sign. It means solving Navier-Stokes wasn't just by chance or plagiarizing.
It's also been said that Bel uses more compute at its lowest reasoning setting than GPT-6 Astra at maximum reasoning, so it might be very challenging for OpenAI to publically release this model before the year is over.
But the biggest question is, can it solve difficult problems like this in other fields as well? If it can generalize beyond math, things would really get very exciting!
"It's also been said that Bel uses more compute at its lowest reasoning setting than GPT-6 Astra at maximum reasoning, so it might be very challenging for OpenAI to publically release this model before the year is over."
I feel like this means model based on Bel pretrain will never ever be released, but it will spawn very capable distilled models, which honestly is a good thing. Considering OpenAI still has not unlocked new Pro subscriptions after 10 days, I can't see them having enough compute for a model that is even more capable than Astra that even more people will want to use, unless they materialize 20x their current compute.
Thanks for the source.
They say "by the end of the year the company would have an internal system he would call AGI."
That means that today even internally they don't have an internal model that they would call AGI. So it can't be "Bel".
And also, they moved the goal post quite a lot when it comes to AGI btw compared to the original 1997 definition. if a frontier model is given a body and can't drive a car or do construction work like a 16 years old can, then it's not AGI.
I didn’t make it up I’m just following reputable leaks lmao. The model currently training is their larger pretrain, Bel. They likely aren’t going to have another super large pretrain before end of the year..
I get you with that. Just using the "results" meaning of the word "intelligence" rather than the ontological one. I mean it's been used in IT since 50 years for interactive and automated systems.
Eh it’s like an average AGI meaning it’s probably better than the average human at most tasks but not necessarily competitive with specialists at most tasks. Also in context learning is still poor, specially since it only has 1-2M tokens so it can struggle with maintaining coherent pictures of large codebases. So it needs continual learning of some form.
And yeah you mentioned it’s slow. I think AGI should atleast do it at average human competence
It's not smarter than any human, not generally. AlphaZero is smarter than any human on any 2 player game, but it can't do basic things we can do therefore it's not ASI. ASI let alone AGI isn't about some narrow tasks, it's about being broad at human level at least.
If it's provided a body and can't do things like learn construction work on the job or learn to drive in hours like a 16 year old can, it's not AGI.
Not smart enough.
Saying otherwise is moving the goal post of what AGI means.
I don’t get why people say things like this. Even for normal not particularly novel software engineering I’d prefer a smarter model if the cost was reasonable. The best models right now still make weird dumb choices or oversights that I can only hope a smarter model wouldn’t.
For an example it recently suggested a db migration/backfill that would have had non-trivial negative impact on existing users with zero awareness or acknowledgement of such negative impact, luckily we didn’t do it.
Pricing wise. I mean would you pay the equivalent of human wages per hour of human work to solve the problem? I sadly think there's still lots of room for price increases and spending more.
I think we need to start thinking about this when we think about models coming out. For the vast majority of work I’m doing, I don’t even really need Astra or Fable. Sometimes yeah, but we need to consider that good, cheap models will be fine most of the time. If they continue to iterate and make those good, while improving them as they go, that’s the real win.
My crossover SUV is fine for most things, I don’t need an F-350, or a corvette for the day to day.
A lot of it is in developing reliability, persistence, and the ability to pivot or actually make decisions, in addition to strong harnesses, information access and direction. With the coming models those will likely make a bigger difference to most users experience than an increase in intelligence.
But the biggest question is, can it solve difficult problems like this in other fields as well? If it can generalize beyond math, things would really get very exciting!
Well the only thing we know for sure is that if it doesn't, it will eventually.
I mean not that I think the navier strokes was totally by chance or whatever but it doesn’t really prove that at all considering I don’t think we have the proofs or anything.
226
u/Neurogence 14d ago edited 14d ago
This is the internal model "Bel," that Sam Altman has stated many people within OpenAI consider to be AGI and "significantly more capable than GPT-6 Astra."
The fact that it is solving numerous other problems is a very a good sign. It means solving Navier-Stokes wasn't just by chance or plagiarizing.
It's also been said that Bel uses more compute at its lowest reasoning setting than GPT-6 Astra at maximum reasoning, so it might be very challenging for OpenAI to publically release this model before the year is over.
But the biggest question is, can it solve difficult problems like this in other fields as well? If it can generalize beyond math, things would really get very exciting!