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I regulate this primarily by simply minimizing my surface area for such things. So for eg. I never got into SBIR/STTR type funding sources for small businesess, and tend to avoid using any service that involves interacting with highly involved UXes.
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There's a hierarchy here. Minimize energy use is the foundational drive, but is rarely directly triggered, since we're rarely at the limits there So in practice regulate uncertainty is the dominant one. It modulated by our sense of the maximum energy we *could* put out
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So for example, I react to the potential for traffic delays by getting to the airport extra early, but that in turn is driven by my sense that I hate sprinting for the gate, and extra-hate the energy demands of rearranging plans if I miss a flight. I do not like having to spike.
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"Minimize energy" is a very illegible optimization problem, since our energy efficiency is a complex function of physiology, cognitive style, and output efficiency. I'm more wasteful in sprint/spike mode. Otoh, I both hate planning and am inefficient/chafing in working to one.
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So I end up solving for minimal energy use/least resistance by a) adopting a highly improv style b) building in lots of time for everything, so I can figure things out by trial and error in a *relaxed* unhurried way. I like to iterate, but not fast.
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A preference for improv over planning is about narrowing the uncertainty band (improv uses more up-to-date info) but also about limiting rework energy (since waterfall plans need higher-energy reworking when they fail, where improv is typically just 1-step backtrack)
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Replying to
Hmm, I am very skeptical about this article. Seems to me a deliberately uncharitable reading. Could we apply the same critique ("isn't sufficient to build GAI") to Friston's FEP? Similar aims: a theoretical foundation of agency. Maybe I'm wrong, have you seen other critiques?
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Gotcha. If you care to share any more details about the substance of the critiques, I'd be very interested -- might save me from going down the wrong rabbit hole!
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