Earlier quoted context omitted.
It gives them a massive advantage because they can cut the cost per token by a lot and eat Anthropic's market share. In what universe is any company going to give that advantage away? In any case if they take away a lot of market share it's basically the same in the end - most people will be using these optimisations.
Deepseek gave it away with R1. They did it again with V4 and DSpark. You don't use it because it's Chinese
GPT-5.6 Sol Ultra will be in Codex
311–320 of 433 posts
Re: GPT-5.6 Sol Ultra will be in Codex
#312Re: GPT-5.6 Sol Ultra will be in Codex
#313Re: GPT-5.6 Sol Ultra will be in Codex
#314Earlier quoted context omitted.
The US can just ban Chinese weights being used in US companies.
If the Trump administration decides to annoint Altman and Amodei in defiance of market forces it will rapidly discover that it no longer has the sovereign bond auction pricing power to prop them up. This isn't 1998: the Treasury has taken five major body blows in the last 25 years, the world's energy markets, maritime insurance regimes, electronic payments rails, and moral authority in places like the UN Security Cou…
On one hand it appears to cooperate with OpenAI and Anthropic, as big customers.
On the other hand NVIDIA cooperates with Palantir, providing the HW for its "Sovereign AI OS" (a turnkey system including HW and SW for local inference and post-training/fine tuning) which uses the slogan "The future of AI is on-prem" (i.e. not as a customer of OpenAI or Anthropic, but using an open-weights LLM, e.g. a fine-tuned NVIDIA Nemotron or a Chinese LLM).
Presumably with the goal of promoting their competing solution, Alex Karp (Palantir CEO) has delivered a few weeks ago a very harsh criticism of Anthropic and OpenAI (who allegedly inflate the token consumption and they might also steal the data of their customers, which must be sent to them).
So NVIDIA both cooperates and competes with OpenAI and Anthropic.
Re: GPT-5.6 Sol Ultra will be in Codex
#315there seems to be very big misunderstanding about what the "ultra" is, so let me explain it basing on the codex source code: it's similar to Claude code ultracode. there is no ultra effort level implemented on the backend. it's just alias in the codex to max effort setting and single line addition to prompt to use subagents proactively. that's all as far as we know pro models work differently. for once those are back…
Re: GPT-5.6 Sol Ultra will be in Codex
#316I'm working in large US corporation. And I see that I already have access to 5.6-Sol Ultra on my corporate account. I haven't really used it yet. 2 months ago management was showing us scoreboards, praising leaders who used most tokens. Last few weeks, we're getting weekly emails, telling us that whenever we can - we should use cheaper models, and that we should watch the page which shows our tokens usage.
GPT 5.5's double token cost was the threshold for me. These things are getting expensive quickly - the subsidized pricing can't go on forever.
Re: GPT-5.6 Sol Ultra will be in Codex
#317Earlier quoted context omitted.
The big problem is that a person making a mistake can be taught to not make that mistake again. That's also not foolproof but at least it works a lot of the times. AI are unteachable, if you have given them a good prompt and they do something wrong 90% of the time you are shit out of luck. That is to say I do agree that building reliable processes out of unreliable parts with feedback is the modus operandi. However A…
I don't know of any modern workflows that rely on "we'll tell the person not to do it again", though. There's a reason that companies have adopted blameless postmortems, because if your response to the DB going down is "It's fine, Kevin learns and next time he won't misuse the prod credentials", you are guaranteeing prod will go down again in the same way at some point.
Re: GPT-5.6 Sol Ultra will be in Codex
#318Earlier quoted context omitted.
The big problem is that a person making a mistake can be taught to not make that mistake again. That's also not foolproof but at least it works a lot of the times. AI are unteachable, if you have given them a good prompt and they do something wrong 90% of the time you are shit out of luck. That is to say I do agree that building reliable processes out of unreliable parts with feedback is the modus operandi. However A…
I don't know of any modern workflows that rely on "we'll tell the person not to do it again", though. There's a reason that companies have adopted blameless postmortems, because if your response to the DB going down is "It's fine, Kevin learns and next time he won't misuse the prod credentials", you are guaranteeing prod will go down again in the same way at some point.
Re: GPT-5.6 Sol Ultra will be in Codex
#319Earlier quoted context omitted.
The big problem is that a person making a mistake can be taught to not make that mistake again. That's also not foolproof but at least it works a lot of the times. AI are unteachable, if you have given them a good prompt and they do something wrong 90% of the time you are shit out of luck. That is to say I do agree that building reliable processes out of unreliable parts with feedback is the modus operandi. However A…
> AI are unteachable, if you have given them a good prompt and they do something wrong 90% of the time you are shit out of luck. If the Model makes repeated mistakes on the same subject matter, you can update your agent.md file, or you can add skills to deal with specific prompts, or you provide a better default harness. The whole idea of coding agents is their harness makes a big difference vs a pure raw model. > Ho…
That's all just prompting.
> How do you think models are created? They are trained on feedback and learn.
No one is post training models on a single mistake. At least I have not seen it. I also doubt it is effective. Post-training on a single failure will not meaningfully change the model. That even sidesteps the entire problem that you don't even have access to models if you use a provider like anthropic/openai
Re: GPT-5.6 Sol Ultra will be in Codex
#320there seems to be very big misunderstanding about what the "ultra" is, so let me explain it basing on the codex source code: it's similar to Claude code ultracode. there is no ultra effort level implemented on the backend. it's just alias in the codex to max effort setting and single line addition to prompt to use subagents proactively. that's all as far as we know pro models work differently. for once those are back…
sources for easy confirmation: https://github.com/openai/codex/blob/98d28aab54ed86714901b66... https://github.com/openai/codex/blob/98d28aab54ed86714901b66... https://github.com/openai/codex/blob/98d28aab54ed86714901b66...