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!
We already know OpenAI has "bel" that is MUCH better than astra and is being used internally
Gov and Corp will throw their hands up and explain how it's not their fault.
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.
Also, Mythos was in fact a significant step-up in several ways. It fits the trend line, but only because the trend line for LLMs is quite steep. Plus Astra is still in many ways less intelligent than Fable/Mythos despite being released much later.
> Because clearly they have no problem with releasing newer versions of models even just a week apart.
You can see how it is pure non-sequitur, right?
> 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.
Fable was absolutely not in line with capabilities of other models when released. For cybersec work it was much, much better.
Makes total sense if they don't have the compute and can't serve it in an economically viable way. Also it lets you build things no one else in the world can build as fast as you until it's released
"We can generate slop faster than anyone in the world" :evil_emoji:
Yeah, it does, it might be misaligned, a snapshot of the going on training, bigger than they can serve publicly, not yet completed the full training pipeline.
If you see the knowledge cutoff you can see that sol 5.6 finished the initial main (+stage edited) of the training pipeline on Feb 16, 2026 but it was publicly released on July 9.
The opposite would be weird: if they do NOT have an unreleased in-house model that would be really odd.
This isn't at all what I said. The original commenter mentioned a model MUCH stronger than Astra.
Indeed it would be really odd if OpenAI were actually open
I mean, isn't it almost a guarantee that what we get is a gimped version of what they use internally? They probably already serve themselves next gen level models at 1k+ tps from cerebras machines hosted on perm while we get quantized astra/opus at 50tps on a good day
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.
In a way: We have had "recursive self improvement" (RSI) - that's what genetics is, giving rise to ... us.-
This time around, I think the truly worrying thing is that, having transcended the biological substrate, the pace is unlike anything previously seen.-
Just a thought.-
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?
I neither use Android devices nor Google Search, so the only Gemini thing I see is the Gemini chat interface.
I understand the pain, though.
It's baffling that OpenAI managed to get better at web search than the company literally synonymous with web search.
I don't want it to fill in the gaps though, but make it reference anything and everything it brings, hence it doesn't hallucinate much.
If something feels off, I ask it to back it with concrete data, and if it can't, I don't consider that information correct. That happened once, though, and web doesn't have any information on that thing either. So in that case, not only it had no information on the web, the training data had no information on that thing either short of feeding confidential design documents if they were ever present in the first place.
The question was about an instrument preamp though, so nothing crucial.