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Not sure why this is being downvoted, it's a thoughtful comment. I too see this crisis as an opportunity to push boundaries past current architectures. Sparse
by michelpp 1y ago
Not sure why this is being downvoted, it's a thoughtful comment. I too see this crisis as an opportunity to push boundaries past current architectures. Sparse models for example show a lot of promise and more closely track real biological systems. The human brain has an estimated graph density of 0.0001 to 0.001. Advances in sparse computing libraries and new hardware architectures could be key to achieving this kind of efficiency.
- lazide 1y agoMemristors have been tried for literally decades. If the posters other guesses pay out the same rate, this will likely play out never.
- ilaksh 1y agoOther technologies tried for decades before becoming huge: Neural-network AI; Electric cars; mRNA vaccines; Solar photovoltaics; LED lighting
- lazide 1y agoHo boy, should we start listing the 10x number of things that went in the wastebasket too?
- ToValueFunfetti 1y agoIf I only have to try 11 things for one of them to be LED lights or electric cars, I'd better get trying. Sure, I might have to empty a wastebasket at some point, but I'll just pay someone for that.
- lazide 1y agoThis fundamentally at odds with picking one tech and saying ‘this is the winner’ eh? Which is what the prior comment was about.
- ToValueFunfetti 1y agoWhich prior comment? Top level offers two options plus an 'etc.', second comment adds another and says 'could be', and then first reply to you offers other tech that took decades of R&D to suggest we can't rule out memristors. I don't see what you're referring to.
- lazide 1y agoUh huh, sure.
- ToValueFunfetti 1y ago?
- kelipso 1y agoThere was a bit of noise regarding spiking neural networks a few years ago but now I am not seeing it so often anymore.
- hyperbovine 1y ago> Sparse models for example show a lot of promise and more closely track real biological systems. I think sparsity is a consequence of some other fundamental properties of brain function that we've yet to understand. Just sparsifying the models we've got is not going to lead anywhere, IMO. (For example it's estimated that current AI models are already within 1%-10% of a human brain in terms of "number of parameters" (https://www.beren.io/2022-08-06-The-scale-of-the-brain-vs-machine-learning/ https://www.beren.io/2022-08-06-The-scale-of-the-brain-vs-ma...).)