very interesting, relevant and clever work from the @the_nof1 team interest pseudo-ontological mapping between options (intrinsic vs time value) and finite horizon RL (immediate offspring vs lineage value) massively excited for this team over the coming months and years
At Nof1 we believe the next breakthrough in AI after reasoning is adaptation If reasoning is the ability to detect patterns and leverage them, adaptation is anticipating how those patterns will change This is a crucial capability for real world AI, and current LLMs struggle with it. We've run thousands of live market experiments and no amount of context, prompting, or harness engineering has worked. So, we've been pushing our research deeper down the stack In this paper, we trained models that can better adapt in dynamic environments like markets. They learn to value an action by the futures it opens up, not just its immediate payoff It's an early step, but we're building towards forever learners that are default forward-looking, rather than static and backward looking
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this is a pretty cool way to think about adaptation

Aug 18, 2026 路 4:18 PM UTC

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pretty cool way fr
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The option vs. RL analogy is genuinely fascinating. That kind of framework can unlock some very different ways of thinking about agentic systems and long-term value.
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Yeahh it鈥檚 pretty cool
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