At any rate, one basic communication's satellite worth of compute would be more than enough. No need for TPUs.
I think it's good to engage this way, but I have a lot of thoughts on things to do that are more effective than giving public comment, and a caution that if you have strong opinions about ALPRs and you choose to pay attention to this issue you're going to be confronted with a lot of opinions that may surprise/discomfit you.
In my experience, a sizable chunk of people who are anti-surveilance are pretty staunchly rightwing.
This is bad news in that it means that there isn't a pre-formed anti surveillance coalition, but good news in every other way imo.
I don't see why a non-western military alliance wouldn't be eligible, so long as the meet the criteria — treaty registered with the UN etc.
When I drive my daughter to school when it’s -40 fucking degrees, a lot of the energy I use goes into heating my vehicle, swearing, moving and swearing. But this energy also leaks through my windshield, through my exhaust system and through my engine. This energy (heat) doesn’t provide any benefit to anyone and just leaks out into the atmosphere (which we’ve already established is trying to kill me).
That’s rejected energy. Or when it’s below -40, rejected motherfucking energy. :)
Sounds like a very unique experience :)
In practice, I find it much more productive to start with a computational solution - write the algorithm, make it work, understand the procedure. Then, if there's elegant mathematical structure hiding in there, it reveals itself naturally. You optimize where it matters.
The problem is math purists will look at this approach and dismiss it as "inelegant" or "brute force" thinking. But that's backwards. A closed-form solution you've memorized but don't deeply understand is worse than an iterative algorithm you've built from scratch and can reason about clearly.
Most real problems have perfectly good computational solutions. The computational perspective often forces you to think through edge cases, termination conditions, and the actual mechanics of what's happening - which builds genuine intuition. The "elegant" closed-form solution often obscures that structure.
I'm not against finding mathematical elegance. I'm against the cultural bias that treats computation as second-class thinking. Start with what works. Optimize when the structure becomes obvious. That's how you actually solve problems.
https://www.youtube.com/watch?v=ltLUadnCyi0
Personally, I find a mix of all three approaches (programming, pen and paper, and "pure" mathematical structural thought) to be best.
Microsoft’s IP rights for both models and products are extended through 2032 and now includes models post-AGI...
To me, this suggests a further dilution of the term "AGI."
If you believe in a hard takeoff, than ownership of assets post agi is pretty much meaningless, however, it protects Microsoft from an early declaration of agi by openai.
If you get sick of MILPs, maybe you could use a representation of your finite field instead of the field itself? That way you could do everything in C^n, and preserve differentiability to use SGD or something like it.
They're no longer officially supported though.