@thsottiaux
Codex feedback: Codex should be able to dynamically revise its goal as it works.
Right now, once a goal is set, it appears to remain fixed, and Codex continues working toward it. But during open-ended exploration, Codex may discover that the original goal was poorly specified, too narrow, or simply not the right direction.
It would be extremely useful if Codex could refine, expand, or shift the goal itself based on what it learns along the way. This is especially important in mathematical research, where the right objective often becomes clear only through the process of exploring the problem.
What I love about Codex 5.6 sol: it helps me turn my idea into feature just in hours.
I've built a price tracking dashboard with live price over the weekend and it's been running smoothly so far. Love the UI design as well!
@thsottiaux @ChatGPTapp @OpenAI
@sama we need GPT thinking (and pro) to have more lateral thinking. not just focusing on the current task, but to see the overall bigger picture to avoid drilling down to a specific rabbit hole
@sama able to navigate and stay the course of the directions when reasoning. this is obvious when conducting math and physics research. the direction is offen times deviated from the main problem.
GPT 5.1 thinking model is really good compared to GPT 5 thinking. Before when talking about life in general or discussing life decisions, it felt like talking to a nerd who only knew about science and provided concrete metrics which were only applicable in science field.
Now GPT 5.1 thinking has both depth, warmth and clarity. It feels more like talking to a high intelligence human being who has life experiences and matches with your visions on how to deal with struggles.
Thank you @ChatGPTapp @sama@markchen90 and team!
In terms of intellectual novelty and proof depth, IMO is harder.
IMO leans more toward unknown-unknown. You need to create a lemma no one handed you.
ICPC leans more toward known toolkits, correctly identify and combine known techniques, more of pattern recognition which is suitable for AI. But the search space of implementations and edge cases is vicious.
Our general-purpose reasoning models solved all 12 problems at the 2025 International Collegiate Programming Contest (ICPC) World Finals, the world’s top university programming competition which was enough for a 1st-place human ranking.
Impressive. GPT-5 thinking mode could do 26-digit number by a 22-digit multiplication correctly without any tools after 3 min 55s (checked CoT that no tools were called).
The previous models all failed miserably.
This is a big milestone.
Congrats to @ChatGPTapp @OpenAI !