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Joined 1 year ago
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Cake day: May 31st, 2023

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  • That’s only for cabin luggage. In checked luggage, Lithium Ion batteries are completely banned. If a battery bursts into flames in the cabin, it can be handled with hopefully minimal damage. You do not want that to happen in the belly of the plane packed in closely between everyone else’s luggage with no way of getting it contained until the planes lands.




    • Waking up via lights slowly dimming on is much nicer than an acoustic alarm.
    • Light temperature adjusting to current time of day is very nice and does loads for my mood
    • Lights automatically turning on and off based on presence and measured light levels is totally unnecessary but just so convenient
    • Getting a reminder to take the wash out when the machine is done
    • Smart plug automatically turns off power to other devices when the TV is turned off


  • From the article:

    For many years, we’ve had software that can generate lists of valid conclusions that can be drawn from a set of starting assumptions. Simple geometry problems can be solved by “brute force”: mechanically listing every possible fact that can be inferred from the given assumption, then listing every possible inference from those facts, and so on until you reach the desired conclusion.

    But this kind of brute-force search isn’t feasible for an IMO-level geometry problem because the search space is too large. Not only do harder problems require longer proofs, but sophisticated proofs often require the introduction of new elements to the initial figure—as with point D in the above proof. Once you allow for these kinds of “auxiliary points,” the space of possible proofs explodes and brute-force methods become impractical.

    So, mathematicians must develop an intuition about which proof steps will likely lead to a successful result. DeepMind’s breakthrough was to use a language model to provide the same kind of intuitive guidance to an automated search process.