3 ms·

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.

nfw2 3y ago
My takeaway is that the chip's goal is to provide a way to produce random numbers with some configurable distribution that is faster and more energy efficient. As far as the feasibility and impact on AI in general, I have no idea.
deleted 3y ago
[deleted]
nfw2 3y ago
I have a suspicion that a lot of people are nodding along because they don't want to seem like the village idiot.
- zooq_ai 3y ago
  on the other hand, HN is filled with self-proclaimed critics that they dismiss everything and display their utter lack of imagination -- like AI, Metaverse, (success of) Snapchat, AirPods before
  - api 3y ago
    Did HN dismiss AI? I saw some skepticism and still do but not dismissal. This site doesn’t get everything right. It tends to miss things that succeed in the consumer space because this is a pro audience not a mainstream audience. But it usually gets hard science right.
- deleted 3y ago
  [deleted]
- shermantanktop 3y ago
  nods vigorously
digging 3y ago
I'm similarly suspicious, and find it curious that this is the first I'm hearing about this at all. I don't have personal connections in physics or AI circles but I feel like I'd usually expect to have read mention of these ideas before finding this press release.
jpm_sd 3y ago
It sounds like complete BS, unfortunately.
the__alchemist 3y ago
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.
- spiantino 3y ago
  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!
  - pclmulqdq 3y ago
    I can sell you a solution to that in AWS/Azure (or on prem) today if you really want to use a TRNG for your ML training :) 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.
- pclmulqdq 3y ago
  As far as I can tell, as someone with relevant hardware expertise, this is a quantum machine learning startup.
rq1 3y ago
This is hype. Someone should tell them about MCMC and alike. Or if they want to accelerate MCMC for a particular problem, they can build a classical ASIC and scale it.
swatcoder 3y ago
It's a startup with well-credential and very technical founders and a fair seed round focused on accelerating one bottleneck in a newly popular computing paradigm using techniques that are known in research but never yet commercialized. It might fail for the reasons many startups fail, but it's not prima facie fantasy.
- teucris 3y ago
  But I don’t see the bottleneck. What are they optimizing that’s worth all this effort? As others have noted, RNGs are not a notable bottleneck in AI.
api 3y ago
Sounds like a really convoluted new agey way of talking about some kind of analog computing. 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.
inasio 3y ago
I don't know about the AI aspect, but this sounds perhaps related to probabilistic finance simulations (Black-Scholes, Heston, etc). I've heard rumors that these types of simulations account for an obscene amount of compute at AWS

nfw2 3y ago

My takeaway is that the chip's goal is to provide a way to produce random numbers with some configurable distribution that is faster and more energy efficient. As far as the feasibility and impact on AI in general, I have no idea.

deleted 3y ago

[deleted]

nfw2 3y ago

I have a suspicion that a lot of people are nodding along because they don't want to seem like the village idiot.

zooq_ai 3y ago
on the other hand, HN is filled with self-proclaimed critics that they dismiss everything and display their utter lack of imagination -- like AI, Metaverse, (success of) Snapchat, AirPods before
- api 3y ago
  Did HN dismiss AI? I saw some skepticism and still do but not dismissal. This site doesn’t get everything right. It tends to miss things that succeed in the consumer space because this is a pro audience not a mainstream audience. But it usually gets hard science right.
deleted 3y ago
[deleted]
shermantanktop 3y ago
nods vigorously

digging 3y ago

I'm similarly suspicious, and find it curious that this is the first I'm hearing about this at all. I don't have personal connections in physics or AI circles but I feel like I'd usually expect to have read mention of these ideas before finding this press release.

jpm_sd 3y ago

It sounds like complete BS, unfortunately.

the__alchemist 3y ago

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.

spiantino 3y ago
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!
- pclmulqdq 3y ago
  I can sell you a solution to that in AWS/Azure (or on prem) today if you really want to use a TRNG for your ML training :) 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.
pclmulqdq 3y ago
As far as I can tell, as someone with relevant hardware expertise, this is a quantum machine learning startup.

rq1 3y ago

This is hype. Someone should tell them about MCMC and alike. Or if they want to accelerate MCMC for a particular problem, they can build a classical ASIC and scale it.

swatcoder 3y ago

It's a startup with well-credential and very technical founders and a fair seed round focused on accelerating one bottleneck in a newly popular computing paradigm using techniques that are known in research but never yet commercialized. It might fail for the reasons many startups fail, but it's not prima facie fantasy.

teucris 3y ago
But I don’t see the bottleneck. What are they optimizing that’s worth all this effort? As others have noted, RNGs are not a notable bottleneck in AI.

api 3y ago

Sounds like a really convoluted new agey way of talking about some kind of analog computing. 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.

inasio 3y ago

I don't know about the AI aspect, but this sounds perhaps related to probabilistic finance simulations (Black-Scholes, Heston, etc). I've heard rumors that these types of simulations account for an obscene amount of compute at AWS