I would just LOVE to see all the behind-the-scenes shithousery both companies are employing to one-up the other in this, largely, 2-horse AGI race. Someone should make a mockumentary when all is said and done!
It makes sense for them to sit on it until they've finished testing it. More powerful but also more likely to delete all your email by mistake = you shouldn't release it yet.
No? The top of human engineers are much better than any model would be, so AI models really aren't a big advantage when you're trying to develop anything that is SOTA.
> its not done training, why would they release a model that hasn't finished training?
Because clearly they have no problem with releasing newer versions of models even just a week apart.
> besides, we know anthropic are sitting on models too
It is from your crystal ball or from other bullshit you heard from Anthropic employees on Twitter?
We all know Anthropic had Mythos and Fable, and they turned out to be completely normal models, entirely in line with the capability of their predecessors.
All they do is lie, and you're believing their lies.
The poster is not claiming Bel is a secret AGI. Just that it exists and only exists internally at the moment.
It's rumored to be over 10T parameters. When released it'll probably be very good at certain tasks, albeit slow and expensive and not necessarily "wiser". You don't have to make this a binary.
Any strong enough model with weak enough safeguards can cause an AI Chernobyl event that will make people and governments against AI development and deployment, just like Chernobyl did for nuclear energy.
The absolute frontier is largely 2-horse, but the rest of the pack is very close behind, which I'm grateful for. Grok, Facebook, and the Chinese vendors are producing excellent models.
Gemini is also pretty nice for researching things. It turns out that having the whole internet indexed and having unlimited access to YouTube is a force multiplier of some kind.
Since Google has their own TPUs, TPS is also pretty high w.r.t. Claude, for example.
I think Gemini could be a great product, if they didn't decide to stuff it down my throat at every possible occasion.
Recent example: on my e-reader, tapping a word I don't now and clicking "Translate" pulls up the possible translations from a dictionary, a local file just a couple of megabytes big, near instantly, on this tiny processor.
Doing the same on my Android phone starts a Gemini-chat with the prompt "Translate the word x into y". Takes forever, internet access needed, results vary, burns who knows who much energy.
Gemini is unbelievably bad for research in my experience. It hallucinates like it's 2023, doesn't use its own search, makes up fake rationalizations for why it didn't need to etc.
It's baffling that OpenAI managed to get better at web search than the company literally synonymous with web search.
... and, must be said a plethora of largely unsung, small, unknown "labs", outfits, "researchers" and the like. There is a long tail of smart people having at this. I guess, sheer compute aside, I think much progress - or, at least, important pieces thereof, will come from there.-
There are some niche research areas where bog standard machine learning algorithms make miracles. LLM is just the poster child. AI/ML is a much larger and wider research area.
What about those do you think are "shady"? Price discrimination in favor of small customers at the expense of large customers is somewhat common; businesses want customers to buy more of their products, but customers are not obliged to buy more if they like their current deals. Having limits on using finite resources seems even easier to justify.
Humans see differences in prices as unfair. The greatest example of this is price gouging during an emergency, but also look at the level of hate that scalpers get.
Using AI to do this, if anything, given the common negative sentiment, is seen as even worse. People think of this as AI using information asymetry to squeeze more out of users, not to cut people a deal.
Taking advantage of information asymmetry is generally looked down upon as well. Look at all the laws we have protecting kids from this. Businesses often don't seem similar protections because those are businesses with big legal teams (and when it is a big legal team vs a small mom and pop store without a single lawyer on payroll, people do start taking issues with it). The power difference between the average company using AI pricing and the average consumer falls pretty solidly in the 'we don't accept this' side of taking advantage of information asymmetry.
I could keep going, but I think these are already plenty enough reasons to why people look at AI price discrimination as not just a bad business practice they don't like, but an immoral/unethical one.
Sure, one can make economical counter arguments, but that's arguing on an orthogonal dimension that simply isn't relevant to where these feelings/thoughts come from.
This has got to be a panic move from OpenAI, right? They’ve had some bad press lately because from their billing changes, and Anthropic have finally released a fast, relatively cheap Opus with improved written English.
Astra is noticeably smarter than any OpenAI model before it. Sol 6.1 is very noticeably smarter than sol 6 even after half a day of using it (sol 6 was actually terra 6 and opus 5.5 has taken them by a total complete surprise)
Kinda same but I miss my 5.3 Codex. Thing lasted forever on my $20 subscription and with detailed prompts was able to pretty much implement everything I requested it to do with a acceptable quality.
Same. 5.5 got work done then 5.6 was also fine then 6 was maybe not quite as good. Now with 6.1 they are cutting usage and raising prices and introducing ultra fast mode, but things were good enough 5 months ago.
It would be very nice if artificialintelligence.ai actually, from a UX perspective, did the models in more than one thinking mode. I use claude, and I wanna build a feeling for what high, medium, etc. actually gives me. So far their comparisons, and having tried several different models for my work, has given me a feel of what 50 intelligence actually is. And I believe it would be
be of even greater value to get a feel inside the single model I actually use, as most people do, because not many, I believe, switch heavily between models when working. I understand that the cost here is greater but the model provivders should obviously give you free access, because of the great work you are doing.
Every time a new model comes out, people come out in droves "oh I don't notice anything different".
People have been saying this about <currentModel-1> for 2 years now, and the entire state of AI has changed dramatically.
It cannot be that the next AI model isn't better, but also suddenly what they are capable of is on an entirely different level.
We already know OpenAI has "bel" that is MUCH better than astra and is being used internally
You're just believing their own bullshit. There's no indication that this is true except from claims from people working at OpenAI.
If they really had a much more powerful model, it would make absolutely no sense to sit on it.
Plenty of the tasks that keep a company running can benefit from good-enough (and better than the competition).
besides, we know anthropic are sitting on models too
Because clearly they have no problem with releasing newer versions of models even just a week apart.
> besides, we know anthropic are sitting on models too
It is from your crystal ball or from other bullshit you heard from Anthropic employees on Twitter?
We all know Anthropic had Mythos and Fable, and they turned out to be completely normal models, entirely in line with the capability of their predecessors.
All they do is lie, and you're believing their lies.
It's rumored to be over 10T parameters. When released it'll probably be very good at certain tasks, albeit slow and expensive and not necessarily "wiser". You don't have to make this a binary.
The absolute frontier is largely 2-horse, but the rest of the pack is very close behind, which I'm grateful for. Grok, Facebook, and the Chinese vendors are producing excellent models.
Since Google has their own TPUs, TPS is also pretty high w.r.t. Claude, for example.
Recent example: on my e-reader, tapping a word I don't now and clicking "Translate" pulls up the possible translations from a dictionary, a local file just a couple of megabytes big, near instantly, on this tiny processor.
Doing the same on my Android phone starts a Gemini-chat with the prompt "Translate the word x into y". Takes forever, internet access needed, results vary, burns who knows who much energy.
Why? Just why?
It's baffling that OpenAI managed to get better at web search than the company literally synonymous with web search.
Now I can finally build that half a thing I've had my eye on.
Using AI to do this, if anything, given the common negative sentiment, is seen as even worse. People think of this as AI using information asymetry to squeeze more out of users, not to cut people a deal.
Taking advantage of information asymmetry is generally looked down upon as well. Look at all the laws we have protecting kids from this. Businesses often don't seem similar protections because those are businesses with big legal teams (and when it is a big legal team vs a small mom and pop store without a single lawyer on payroll, people do start taking issues with it). The power difference between the average company using AI pricing and the average consumer falls pretty solidly in the 'we don't accept this' side of taking advantage of information asymmetry.
I could keep going, but I think these are already plenty enough reasons to why people look at AI price discrimination as not just a bad business practice they don't like, but an immoral/unethical one.
Sure, one can make economical counter arguments, but that's arguing on an orthogonal dimension that simply isn't relevant to where these feelings/thoughts come from.
The results are less buggy, animations are much better.
It can work autonomously for hours and the result is decent most of the time.
That wasn't usually the case with 5.5, which needed more feedback and iterations to get things right.
But they do. See for example the pareto curve they have, try to locate GPT-6 Luna (max), (xhigh), (high), (medium), (low)
Nothing, really. It's like oversampling your data set. You usually get a much better overall baseline performance if you use the default setting.
…but not for all models, which is pretty annoying.