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Or like providing the world’s information in machine readable format that the AI companies can convert into model weights without getting permission or compensating the rights holders
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"Your text batch moved the weights away from the final values. Your contribution is negative."
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Where do I collect the $0.00000012 antidollars owed to me by OpenAI for my valuable inputs?

Slightly more seriously, you could perhaps make an argument that, just like weight decay, an apparent "anti-contribution" moves the learning trajectory along, and helps the network settle into a more optimal basin eventually.

That way, my contribution is still valuable on the net, and I'm owed $0.00000003 positive dollars instead.

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>you could perhaps make an argument that, just like weight decay, an apparent "anti-contribution" moves the learning trajectory along

Was that not the joke?

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Correct on all points. Nonetheless this leads to a less useful product. I

f we want more useful products, we need to come up with ways to disincentivize this behavior. Even if doing so poses an existential risk, we are better off if companies taking existential risks to please us is a necessary being a top player in this game.

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More to the point - if they expose their model's "thinking" inference, competitors can train on that to replicate the results. If they postprocess that content, e.g. by summarizing it, it's no longer as useful to competitors.
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Exactly. Google won't like it if they spend millions to make Gemini 3.5 Pro's thinking the best in the world, only for Anthropic or OpenAI to copy it by just seeing the thinking process.
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Copying for me, not for thee
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It’s only ‘fair use’ if you have the money to argue your position.
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> This is because revealing the raw reasoning exposes exactly how the AI processes information. These companies spend in huge amounts on R&D to develop a thinking process that is superior to their competition. Exposing those thinking mechanics to competitors would completely defeat the purpose of their spending. They simply won't do it. It's like you telling your exact location to someone who is trying to hunt you down.

I thought the reason was the "reasoning" didn't work very well with "aligned" model output, so they had to remove the alignment during reasoning and then hide it to avoid exposing "unaligned" model output.

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I suspect that you’re both right in the sense that ‘aligned’ is an important component of ‘superior’ from the vendors’ viewpoint.
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Not sure if anyone remembers the brief 12ish hour period when the very first “reasoning” ChatGPT model went public, but it provided credible evidence for this.

Before the massive nerf (showing summaries and suppressing certain aspects of reasoning) you would literally see reasoning text appearing on your screen like “while xyz is true, these facts may be seen as supporting hateful rhetoric or a conspiracy theory which is against my policy guidelines. i should tell the user xyz is not true or steer the conversation in a different direction. according to my instructions misleading the user is permitted in certain contexts where sensitive information is being discussed or could cause liability”

They disabled it shortly after the first screenshots appeared online, and restored it the next day in a way that hid what was actually happening.

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This right here is why I will never subscribe and, as an American, I hope the Chinese kick our butts. Maybe being second place to China will force American AI to dispose of these morality/safety guardrails.
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When you export your personal data Google hides all model responses leaving just user messages. So it's even worse
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> Exposing those thinking mechanics to competitors would completely defeat the purpose of their spending.

I think one of the reasons could be to limit liability too.

What if reasoning helps in establishing provenance for questionable sources ?

What if reasoning and model's "thought" points to fundamental issues in how the model was trained to produce certain problematic responses ?

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There are actually fine tunes of qwen on opus “thinking” tokens that teach it to think like opus does.

https://huggingface.co/Jackrong/Qwen3.5-27B-Claude-4.6-Opus-...

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And those are "amateur hour" distillations that don't have the scale of actual Chinese labs.
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The cynic in me is wondering whether it's more about how revealing how the sausage is made might bring bad publicity.
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It's to mitigate their competitors ability to run distillation on their models. The only advantage frontier models have is being at the frontier.

There's nothing in the reasoning tokens that'll give bad publicity that the final output already wouldn't do.

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Imagine if their target customers, C-suite execs looking to replace workers, knew how unlike "thinking" this process actually was! we can't have that.
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To be honest I'm not sure if many C-suite execs have a good idea of what "thinking" looks like inside in the first place, in the sense of focused mental activity aimed at solving of a hard logical or technical problem.
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How did they became C-suite execs in the first place, if they don't know how to work on problems?
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Mistral displays some “thinking” text (in their basic online chat interface) in the thinking mode, do we know if those are the real tokens?

It’s quite interesting to read. I can’t imagine using a model like this without the ability to peek inside and see if it is getting stuck.

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I wonder if they put all 80k tokens of the GDPR in its system prompt.
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I dunno, I’m in the US, so I’m not sure how much that impacts their processing of data about me.
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I'm in the US and about a month ago Claude decided I wanted UK English for all my answers and couldn't explain why it changed.
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correct. this becomes difficult for us to understand what happens behind the scenes.
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