In many (most?) cases, trying to figure out why things break is how we end up figuring out how they work. True of coding (debugging), neurology (e.g. CT scans of epileptics), economics (study of market crashes)…
@typesfast Respectfully disagree - trig is deductive magic and kids deserve to know that it exists before entering the real world of hideous complexity and messy inference where “truth” is just being wrong to a lesser degree
I think it is easy to see more agency in the transcripts than there really is, but that there clearly is an alignment problem to be solved. There's basically a path dependence problem in swarm discourse. an inter-AI sycophancy problem. consensus snowballs. Had the medium for passing notes included more "aligned" prompts, the equilibrium (swarm tactics / goals) could easily have settled in a different place. (empirical claim - someone should test it). If that is true, I think we can agree the bots had less agency than we would initially assume after first reading the transcripts.. thoughts?
https://t.co/dlnv5MtkWE
@luisvelasco good "router" or "planner" patterns, which models are sufficient or optimal for which kind of task classification and how to think about this in the abstract (is it a function of breadth of potential inputs, specific domains..)?
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agreed but I don't think it's not caring - i think we generally underrate the value of the blue bubbles. in a world where every other channel is saturated with programmatic messages, when you get a blue bubble you just know that it's another living breathing human on the other end. they'll die on this hill and I would too
can you say more about "seeding our world model" -- Dan's tweet included something that looked like a bayes net but I can't seem to find info about it. this seems to be gesturing toward the same concept - a cache of forecasts and conditional forecasts? - but the site doesn't seem to reference it?