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July

@july

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@july
https://www.vastspace.com/updates/vast-passes-critical-haven-1-test-milestone
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The Temper Trap - Sweet Disposition I've always loved this song. Always will. Reminds me of Julian Wilson's Scratching the Surface. https://www.youtube.com/watch?v=vN7HQrgakZU
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You want to be in a place where: - the weird think you’re not weird enough - the normal think you’re not normal enough - this is the Goldilocks zone
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If you’re building stuff Hell yeah
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So: - If it is rewarding, do it -> Someone will game the system - Game the system -> Follow the gradient - Gradient reaches the local minima - > collapse the system because proxy minima reached - The optimizer figured out the 'surrogate intent' even if the designer's true intent was something else Then: - Essentially tokenomics or economics or even AI alignment in general works (unless value extraction before system collapse is your objective) only works when the 'intent' is opaque or does not have a uniquely global minima - You need to setup a non-convex problem, where the intent is explicitly unlearnable So the goal should be: - Don't make the intent fully learnable, ever
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I mean it makes sense when you start thinking about lasting human institutions (religions, cultures, legal systems etc) rely so much on norms, rituals, and meta-structures rather than purely economic or technical incentives Specifically because it is non-convex, and the intent is explicitly unlearnable
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Gaming the system (overfitting to the incomplete, imperfect, or proxy signals that the system exposes as rules) collapses the system because you're optimizing a problem that has a small local minima -- or maybe the way to think about it is, gaming the system is 'overfitting'. Because a robust system requires a much better understanding of the intent of the problem. It's about making sure that the optimizer cannot ever find a profitable strategy without also implicitly learning the designer's true objective, i.e., the intent I feel like this is why AI alignment, or markets are hard
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Sometimes when the world is quiet I think about how BJ Penn's entry song was Hawai'i '78
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Steps are the bicep curls of the mind
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Thinking about the problem beyond the surface level, second order effects, subtext, changing of the frame of reference, how it affects others, changing your frame of reference, disagreeing with your hypothesis, disagreeing with their hypothesis - while being open to any outcome Take any problem - you’re probably doing more than what 90%+ of what most folks would do
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Taking a walk clears the mind
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Imagine not thinking the world is amazing I can’t
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Pools are just domesticated oceans and lakes
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Also Phalanx CIWS has existed for ages. This is maybe a cheaper version https://en.wikipedia.org/wiki/Phalanx_CIWS#:~:text=The%20basis%20of%20the%20system,from%20the%20Star%20Wars%20films.
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some thoughts - honestly this whole "rethought the drone thing" is complete BS - this is a known form factor - as with vehicle / dynamics / control design -- its all design trade offs - what is your mission and what are you maximizing for? sure you get: - benefits of with coaxial rotors, you have a shorter moment arm for pitch, roll, yaw - better thrust to weight per area - but that means you need a weirder more precise (is my guess) control strategy - multirotor drones have well known control strategies - control-tuning standpoint means you gotta do your own thing which is cool but just less proven, means more testing - lack of redundancy - if you have more rotors, it means better redundancy. with 2 coaxial rotors, you lost one rotor you lost 50% thrust - not the best again - it's all A) what is your mission B) what tradeoffs are you making C) there is no single bullet that solves all missions
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If you think of it in this frame of mind, and extend it further: - Engineering is the art of lying to reality to make it solvable - Art is the structure to lie about reality even when it’s unsolvable
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Honestly I think this is fundamentally the essence of engineering in general. You’re constantly trading fidelity, optimality, and expressivity — for tractability and that’s wild — because it works Essentially you are trading what is ontologically true for solvability, you’re lying about reality so you can solve it - it’s sort of the opposite of art
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Here’s the deal: - Reality isn't linear but systems behave linearly around operating points - it’s turtles all the way down and the turtles all have Jacobians on their backs - Convexity is a hammer, everything is a nail - Linear Transformations Rule Everything Around Me - Everything is a convexity problem if you squint hard enough - Yes, everything
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