Many users are excited by OpenAI using GPT-5.6 to post-train its Luna model as an early step toward recursive self-improvement, while others dismiss the claims as misleading or question the heavily redacted prompt details.
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@kimmonismus @zazmic_inc Calling it "early signs" when it is an entirely different category is not careful articulation; it's straight up wrong and misleading. I am not saying that was intentional; I am claiming something narrower. Your interpretation is poorly developed.
@kimmonismus What a stupid interpretation of what is at most an AI acting as a judge. It's literally training another model, not itself, and you jump to the conclusion that it is RSI.
@sharifshameem Funny y’all keep mentioning this use case… We’re out here literally trying to make gpt-oss-20b run faster. https://x.com/gajesh/status/2075292156328349769?s=46
@sharifshameem @ponnappa "Amazing content! Looking forward to learning more from your future posts. 😊
The workflow initializes training runs from an oai-strawberry checkpoint
@sharifshameem So cool!
@sharifshameem thats fascinating
OpenAI just showed one of the clearest early signs of recursive self-improvement: GPT-5.6 Sol was used to post-train GPT-5.6 Luna. This is not an intelligence explosion (yet). Humans still defined the objective, infrastructure and constraints. But the loop is now visible: frontier models are beginning to perform the engineering work required to build and improve the next generation of models. Once AI meaningfully accelerates AI R&D, every generation helps produce the next one faster. Yes, read that again. That is how recursive self-improvement begins, not with a model rewriting its own weights overnight, but with AI gradually taking over the research and engineering pipeline that creates better AI. And this is further proof that the speed of releases is increasing and models are improving even faster.
Many users are excited by OpenAI using GPT-5.6 to post-train its Luna model as an early step toward recursive self-improvement, while others dismiss the claims as misleading or question the heavily redacted prompt details.
Based on 22 visible X reactions from 80 accounts; directional sample.
Ask a question below.
Published answers will appear here.
@sharifshameem thats fascinating