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Previewing GPT‑5.6 Sol: a next-generation model

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Re: Previewing GPT‑5.6 Sol: a next-generation model

#671

Earlier quoted context omitted.

The first sentence is “understand or learn any intellectual task that a human can.” Whatever you think of the benefits of LLMs, they don’t understand and they can only learn during the training period and with very minor adjustments in post training. So, no I don’t think any of these models are generally intelligent.

> they don’t understand I have not seen any instance of this frequently-made assertion which is at all justified. It seems to rely on a definition of "understand" which is more about spirituality than actual observable evidence (they clearly can comprehend even complex tasks well enough to execute on them, and if you won't call that "understanding", you're playing word games rather than stating an objective fact). Li…

It seems to rely on a definition of "understand" which is more about spirituality than actual observable evidence

"Understanding" has enough philosophical leeway in its use to allow at least the possibility of sentience as a prerequisite.

This is where the discussion about LLM capabilities becomes genuinely difficult, and dismissing that difficulty as "word games" or "spirituality vs evidence" is not helpful.

Re: Previewing GPT‑5.6 Sol: a next-generation model

#673
post #497

Earlier quoted context omitted.

This is genuinely confusing to my senses. The future is going to be so strange/neat/me unemployed.

> strange/neat/me unemployed I'm not sure if that's what you were going for, but I read it as if it were written by The Board in the game Control, and found myself with the appropriate level of existential dread.

We love/help/replace you

Re: Previewing GPT‑5.6 Sol: a next-generation model

#674
post #56

Earlier quoted context omitted.

If you have no need for Anthropic/OpenAI's frontier model capability, you may be better served with an open-weight model that can't be taken away. Edit: > GPT-5 does the job. I bring up DeepSeek V4 Flash a lot on HN, but I want to mention that according to Artificial Analysis, it trades blows with GPT-5 (high) (from August, 2025) [0] [0]: https://artificialanalysis.ai/models/comparisons/deepseek-v4...

deepseek has no part of their privacy policy on their API about training. They are 100% training on every single word you give it. If your customers are fine with that, your IP is not interesting, then you can use it.

You don’t have to access Deepseek through Deepseek. You can self-host it and your data never leaves your premises.

Re: Previewing GPT‑5.6 Sol: a next-generation model

#675
post #56

Earlier quoted context omitted.

If you have no need for Anthropic/OpenAI's frontier model capability, you may be better served with an open-weight model that can't be taken away. Edit: > GPT-5 does the job. I bring up DeepSeek V4 Flash a lot on HN, but I want to mention that according to Artificial Analysis, it trades blows with GPT-5 (high) (from August, 2025) [0] [0]: https://artificialanalysis.ai/models/comparisons/deepseek-v4...

deepseek has no part of their privacy policy on their API about training. They are 100% training on every single word you give it. If your customers are fine with that, your IP is not interesting, then you can use it.

I don't believe a single word from AI companies, no matter where they are from. Sourcing their training data is run like genuine criminal enterprises - last year Anthropic settled for 1.5 billion, and and if they settled so quickly it might mean what we would see in court is even worse.

Re: Previewing GPT‑5.6 Sol: a next-generation model

#676

Earlier quoted context omitted.

I think you're speeding past the word "average" in the sentence. I'd argue that current frontier models already exceed the abilities of average humans across the majority of tasks you can do on a computer, although you might be able to argue that they tend to be a bit slower? That latter part is debatable though - have you seen a non-technical person try to figure out something new on a computer?

" I'd argue that current frontier models already exceed the abilities of average humans " for things that fit in their context window sure but LLMs can't learn over time the way humans can. One example is LLMs are very good at writing a few thousands line of code but they absolutely cannot write coherent million line codebases. By average human I meant the average skill level for the job. AGI would need to be able to…

Yeah it's not true that for every job, it is better than median worker of that job. But it is conceivable that for almost all jobs it is already better than the median human (not just workers of that job).

Re: Previewing GPT‑5.6 Sol: a next-generation model

#677

Earlier quoted context omitted.

I think you're speeding past the word "average" in the sentence. I'd argue that current frontier models already exceed the abilities of average humans across the majority of tasks you can do on a computer, although you might be able to argue that they tend to be a bit slower? That latter part is debatable though - have you seen a non-technical person try to figure out something new on a computer?

" I'd argue that current frontier models already exceed the abilities of average humans " for things that fit in their context window sure but LLMs can't learn over time the way humans can. One example is LLMs are very good at writing a few thousands line of code but they absolutely cannot write coherent million line codebases. By average human I meant the average skill level for the job. AGI would need to be able to…

But in any case, I think more than 10% of information workers today can be replaced by current-generation models indefinitely.

Re: Previewing GPT‑5.6 Sol: a next-generation model

#678
post #497

Earlier quoted context omitted.

Hopefully like this (but smarter): https://chatjimmy.ai/

This is genuinely confusing to my senses. The future is going to be so strange/neat/me unemployed.

Yeah. It keeps catching me off guard that it answered me already.

Re: Previewing GPT‑5.6 Sol: a next-generation model

#680
post #470

Earlier quoted context omitted.

> I think GPT writes code the best. How well will it write in version 5.6? It gives me chills. Heard this exact sentence multiple times a few months ago about Opus 4.6, then 4.7 and 4.8 were considered a disappointment and today people miss "the good old times of 4.6" (referring to a few weeks of February 2026). Very fascinating to look at all of this unfolding.

Reading this thread makes me feel like I'm taking crazy pills. The folks on this train in my team do not produce anything significant that we can rely on or use. A lot of hollow prototypes that join the prototype graveyard and code that needs extra scrutiny on critical areas ultimately leading to taking longer. It's a shame, they were smart and productive engineers. Now? I guess everyone is just all-in on the slot ma…

This split in what different people or groups get out of LLMs is pervasive and really interesting. In the beginning I was dismissive of those with bad experience with a "you are holding the tool wrong" smugness. But as I read more and more experience, I see all combos and I now know my initial knee jerk conclusion was clearly wrong. There are newbie programmers getting good or bad results as well as experienced developers getting either flip of the coin. I don't know what to conclude. I really want to know what are the lines that explain these very different outcomes. Is it the types of problems being solved? The harnesses? The programming languages? FWIW, my experience has been that among my cohorts of mid to deeply experienced developers working in the domain of experimental physics, all have leveled up various degrees after adopting Sonnet and Opus level LLMs using claude code CLI in Python, C++ and web tech, small scale scripts up to multi-package novel system develop and green field as well as incremental development and code maintenance.
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