Could someone smarter than me explain if this is a big deal or just hype? The work sound promising, but I wonder how long it would take to build and validate.
As far as the feasibility and impact on AI in general, I have no idea.
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Could someone smarter than me explain if this is a big deal or just hype? The work sound promising, but I wonder how long it would take to build and validate.
As far as the feasibility and impact on AI in general, I have no idea.
Could someone smarter than me explain if this is a big deal or just hype? The work sound promising, but I wonder how long it would take to build and validate.
It might fail for the reasons many startups fail, but it's not prima facie fantasy.
Could someone smarter than me explain if this is a big deal or just hype? The work sound promising, but I wonder how long it would take to build and validate.
AFAIK there are other efforts to develop analog neural network ASICs. Since neural networks are noise-tolerant this could work and could allow faster computations than conventional must-be-perfect digital circuits. IBM, Intel, and others have experimented with this.
I wouldn't believe there's anything particularly novel here unless a lot more detail or test hardware is given.
I'm not 100% sure this is true but I've heard that this fellow was involved with the NFT craze and made money there, and that sets off alarm bells. I've suspected for a while that e/acc is a marketing thing since it's just repackaging old extropian stuff from the 1990s.
"I want to believe" but have seen enough to be skeptical of extreme claims without hard evidence.
Uninmportant, but if you're citing Moore's paper I feel like you're just trying to pad out the references to make it look like you're serious
Pragmatically, it doesn't make much sense given that it would take years for this approach to have any real work use cases in a best case scenario. It seems way more likey that efficiency gains in digital chips will happen first making these chips less economically valuable.
Could someone smarter than me explain if this is a big deal or just hype? The work sound promising, but I wonder how long it would take to build and validate.
After skimming the article, go back to the beginning, and ponder the opening stanza: > We are very excited to finally share more about what Extropic is building: a full-stack hardware platform to harness matter's natural fluctuations as a computational resource for Generative AI. This is New Age, dressed up with the latest fashion.
I have no idea about the merits of this approach, but I found this interview with the founders a lot more sensical than the linked article: https://twitter.com/Extropic_AI/status/1767203839818781085
edit: btw the bottleneck in AI algos is matrix multiply and memory bandwith.
Earlier quoted context omitted.
After skimming the article, go back to the beginning, and ponder the opening stanza: > We are very excited to finally share more about what Extropic is building: a full-stack hardware platform to harness matter's natural fluctuations as a computational resource for Generative AI. This is New Age, dressed up with the latest fashion.
So exciting! We'd be walking amongst our GAI brethren this very day if it weren't for the computational limits of those pesky RNGs!
They are very energy efficient (measured in pJ/bit), but non-cryptographic PRNGs, which are typical for ML, are far more efficient.
It's not obviously wrong to think that AI algorithms will pick up bias from "overfitting" to their PRNGs used during training, but I'm not expecting the benefits to be very large.