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Cake day: June 12th, 2023

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  • The solution is for states to allocate delegates proportionally. That is in the best interest of each state, so it’s not fragile. It can be accomplished one state at a time, so it’s logistically easier.

    Isn’t this overlooking that each state that does this, especially swing states, does it at their own disadvantage? States that allocate their electoral votes all-or-nothing have more sway over politicians who receive those votes (because the politicians are, in turn, are incentivized to spend their effort on states where the return on that effort is larger, and an effort that wins you 5% of the vote in an all-or-nothing swing state could win you the whole state’s worth of electoral votes, compared to 5% of electoral votes in a proportionally allocated state).







  • When ChatGPT first started to make waves, it was a significant step forward in the ability for AIs to sound like a person. There were new techniques being used to train language models, and it was unclear what the upper limits of these techniques were in terms of how “smart” of an AI they could produce. It may seem overly optimistic in retrospect, but at the time it was not that crazy to wonder whether the tools were on a direct path toward general AI. And so a lot of projects started up, both to leverage the tools as they actually were, and to leverage the speculated potential of what the tools might soon become.

    Now we’ve gotten a better sense of what the limitations of these tools actually are. What the upper limits of where these techniques might lead are. But a lot of momentum remains. Projects that started up when the limits were unknown don’t just have the plug pulled the minute it seems like expectations aren’t matching reality. I mean, maybe some do. But most of the projects try to make the best of the tools as they are to keep the promises they made, for better or worse. And of course new ideas keep coming and new entrepreneurs want a piece of the pie.