kurthr
Joined 12 years ago
Joined 12 years ago
Probably shouldn't be having those Kenyans (Kalenjin) competing in marathons either. Completely unfair advantage.
All models are wrong, some are useful.
My books went from 2 slit experiments, to particle in a box (1d and then 2d harmonic oscillators) with tunneling, and then the Hydrogen atom potential with electron orbitals as an extension, to perturbations for He, to Hartree-Fock and Born-Oppenheimer for large atoms and molecular models. Learning the <bra/ket> formalism can be useful for thinking about it, but it has to be motivated by the math.
I guess black body and scattering were pretty early too as motivation for the developments (as they historically were). Whereas EPR/Bell, Decoherence, and "Interpretations" were mostly discussed as interesting flavor and philosophical arguments.
To add a bit more almost off topic substance from the enshitification of human work. I really do think the idea of hooking these "AI" models up to humanoid robots is a bad idea not for all the mundane reasons, but just because "alignment" seems impossible. All of the world's stories about humanoid robots basically involve them attacking humans and behaving in nefarious destructive ways. It's fundamentally embedded in the models, and there's no reason post training would pull it out, because it's basically in the key value vector meaning "malicious human destroyer". Even to find counter examples like C3PO, Daneel Olivaw, Data, or Wall-ee they come after droid/robot driven wars and apocolypses. It seems unwise.
Notably, neutrons are quite unstable outside of a nucleus and decay generating a proton, electron, and a neutrino. There are many theories on the discrepancy.
https://journals.aps.org/prd/abstract/10.1103/PhysRevD.110.0...
I think the challenge here is that other than a CCTA there's no good way to estimate individual (as opposed to hereditary) ASCVD risk. Sure LDL, ApoB, Lp(a), and BP, are statistical proxies, but tell you little about the individual risk. CAC isn't much better, but if you've been taking EPA and VitK2 you have a much higher chance of more stable plaques, which are also more visible on CAC without much larger X-ray exposure and iodine contrast effects.
Already, the big capabilities are becoming multi-layer/die integration. Whether it's BSPDN, stacked die, optical interconnects, etc it won't be as simple as Denard scaling. It will be dependent on experience and supply chains, which are harder to transfer than equipment or IP.
I do think the market for inference will drive a lot of innovation, and a lot of that will be at larger nodes. A single reticle die masked ROM with CIM can do 7B at 6nm. At 2-3nm you can do 27-32B which is a single expert or router. At that point there's not much reason to shrink for AI since it's mostly 1-hot die per token (except for the router). Update the parameters every 3-6mo when a new frontier comes out, and take the cost/power savings to the bank.
If they had a solution to get to >90% yields on sub 5nm they'd be doing it now. They don't, even the 7-10nm isn't there. Best hope is they get to buy the entire world's supply of EUV in 2027, then they install all of them, then they bring them up, then they build processes around them and make masks, then they ramp the yield on 3-4nm by copying exact TSMC.
The hilarious thing is that TSMC couldn't do this at a new fab in Taiwan, with full access to equipment, supply chain, and people. So, nope.