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Re:Reasoning Is Not Model Improvement by simonw on Thursday October 23, 2025 @05:14PM (#45687260)
If you're not going to believe researchers when they tell you how they did something then sure, we don't know how they did it.

Given how much bad press OpenAI got just last week[1] when one one of their execs clumsily (and I would argue misleadingly) described a model achievement and then had to walk it back amid widespread headlines about their dishonesty, those researchers have a VERY strong incentive to tell the truth.

[1] https://techcrunch.com/2025/10/19/openais-embarrassing-math/

Re:Reasoning Is Not Model Improvement by emp17344 on Thursday October 23, 2025 @05:54PM (#45687774)
Any company will apologize when they receive bad press. That’s basic corporate PR, not integrity.
Re:Reasoning Is Not Model Improvement by simonw on Thursday October 23, 2025 @05:57PM (#45687806)
It illustrates that there is a real risk to lying about research results: if you get caught it's embarrassing.

It's also worth taking professional integrity into account. Even if OpenAI's culture didn't value the truth individual researchers still care about being honest.

Re:Reasoning Is Not Model Improvement by emp17344 on Thursday October 23, 2025 @06:02PM (#45687880)
This exact statement could be said about literally any corporation or organization. And yet, corporations still lie and mislead, because deception helps you make money and acquire funding.

In OpenAI’s case, this isn’t exactly the first time they’ve been caught doing something ethically misguided:

https://techcrunch.com/2025/01/19/ai-benchmarking-organizati...

Re:Reasoning Is Not Model Improvement by simonw on Thursday October 23, 2025 @07:48PM (#45688978)
That story feels very different to me from straight up lying about whether a mathematical competition result used tools or not.