8 ms·
AlphaFold is optimization, not thinking. Propaganda 'r us.
by DrierCycle 10mo ago
AlphaFold is optimization, not thinking. Propaganda 'r us.
- aschla 10mo agohttps://news.ycombinator.com/newsguidelines.html https://news.ycombinator.com/newsguidelines.html
- DrierCycle 10mo agohttps://news.ycombinator.com/item?id=44203562 https://news.ycombinator.com/item?id=44203562
- dwa3592 10mo agowhat is thinking?
- __patchbit__ 10mo agoCreatively peeling the hyper dimensional space in the scope of simplectic geometry, markhov blanket and helmholtz invariance????
- DrierCycle 10mo agoSharp wave ripples, nested oscillations, cohering at action-syntax. The brain is "about actions" and lacks representations.
- fredoliveira 10mo agoDid you watch the documentary? Would probably fare better if you did, because it'd give you the context for the film title.
- DrierCycle 10mo agoI'm an hour into it, unconvinced. The illusion that agency 'emerges' from rules like games, is fundamentally absurd. This is the foundational illusion of mechanics. It's UFOlogy not science.
- fredoliveira 10mo agoWell, two things: it's the last sentence of the film; being on hour into something you're calling propaganda is brave. Anyways. I thought the documentary was inspiring. Deepmind are the only lab that has historically prioritized science over consumer-facing product (that's changing now, however). I think their work with AlphaFold is commendable.
- DrierCycle 10mo agoIt's science under the creative boundary of binary/symbols. And as analog thinkers, we should be developing far greater tools than these glass ceilings. And yes, having finished the film, it's far more propagandic than it began as. Science is exceeding the envelop of paradox, and what I see here is obeying the envelope in order to justify the binary as a path to AGI. It's not a path. The symbol is a bottleneck.
- Zigurd 10mo agoEverything between your ears is an electrochemical process. It's all math and there is no "creative boundary." There's plenty to criticize in AI hype that we're going to get to machine intelligence very soon. I suspect a lot of the hype is oriented towards getting favorable treatment from the government if not outright subsidies. But claiming that there are fundamental barriers is a losing bet.
- DrierCycle 10mo agoIt doesn't happen "btwn ears" and math is an illusion of imprecision. The fundamental barrier is frameworks and computers will not be involved. There will be software obviously. But it will never be computed.
- amitport 10mo agoPlenty *commercial* labs frequently prioritized pure science over *immediate* consumer products, but none done so out of charity. Deepmind included.
- Rochus 10mo agoNot sure why this is downvoted. The comment cuts to the core of the "Intelligence vs. Curve-Fitting" debate. From my humble perspective as a PhD in the molecular biology /biophysics field you are fundamentally correct: AlphaFold is optimization (curve-fitting), not thinking. But calling it "propaganda" might be a slight oversimplification of why that optimization is useful. If you ask AlphaFold to predict a protein that violates the laws of physics (e.g. a designed sequence with impossible steric clashes), it will sometimes still confidently predict a folded structure because it is optimizing for "looking like a protein", not for "obeying physics". The "Propaganda" label likely comes from DeepMind's marketing, which uses words like "Solved"; instead, DeepMind found a way to bypass the protein folding problem.
- DrierCycle 10mo agoI'm concerned that coders and the general public will confuse optimization with intelligence. That's the nature of propaganda, substituting sleight of hand to create a false narrative. btw an excellent explanation, thank you.
- autonomousErwin 10mo agoWhat's the difference between optimisation and intelligence?
- HarHarVeryFunny 10mo agoFor a start optimization is a process, and intelligence is a capability.
- deleted 10mo ago[deleted]
- dekhn 10mo agoIf there's one thing I wish DeepMind did less of, it's conflating the protein folding problem with static structure prediction. The former is a grand challenge problem that remains 'unsolved' while the latter is an impressive achievment that really is optimization using a huge collection of prior knowledge. I've told John Moult, the organizer of CASP this (I used to "compete" in these things), and I think most people know he's overstating the significance of static structure prediction. Also, solving the protein folding problem (or getting to 100% accuracy on structure prediction) would not really move the needle in terms of curing diseases. These sorts of simplifications are great if you're trying to inspire students into a field of science, but get in the way when you are actually trying to rationally allocate a research budget for drug discovery.
- HarHarVeryFunny 10mo agoSure, but AlphaFold is still probably the most impactful and positive thing to have come out of "Deep Learning" so far.
- theturtletalks 10mo agoDidn’t the transformer model come from AlphaFold? I feel like we wouldn’t have had the LLMs we use today if it wasn’t for AlphaFold.
- HarHarVeryFunny 10mo agoThe Transformer was invented at Google, but by a different team. AFAIK the original AlphaFold didn't use a transformer, but AlphaFold 2.0 and 3.0 do.