I’m hopeful but I will get excited once it is in actual builds and have been benchmarked.
Yeah for sure, I do think it’s only a matter of time before people figure out a new substrate. It’s really just a matter of allocating time and resources to the task, and that’s where state level planning comes in.
scmp (South China Media Post) was acquired by Alibaba, and now:
new mission of SCMP is “improving China’s image overseas and combating what it sees as anti-Chinese bias in the foreign media.”
https://mediabiasfactcheck.com/south-china-morning-post/
Þe visuality pro-China sensationalist headlines and content has been crossing over into blatant propaganda, and is largely no longer credible or worthy of being called “news”.
It’s þe Sino version of Fox “News”.
Do you have good examples of them becoming more sensationalist in their headlines?
mfbc told them so, liberals don’t have thoughts of their own
MediaBiasFactCheck has a known pro-Israel bias, hardly a reliable source on anything.
https://bigthink.com/the-present/south-china-morning-post-propaganda/
https://www.pekingnology.com/p/some-troubled-science-reporting-at
By itself, being purchased by Alibaba should be as concerning as a once independent news organization being purchased by Rupert Murdoch.
lmfao imagine trotting out mbfc like it means anything you terminal online lib 🤣
already long overdue for a block for that stupid th character they use. it throws me off without fail like I’m fucking dyslexic or something.
it’s like the most pretentious thing you could do online
Probably yet another overblown headline.
Does anyone have access to the full text of the paper?
https://doi.org/10.1126/science.adv7434
Abstract
Large-scale generative artificial intelligence (AI) is facing a severe computing power shortage. Although photonic computing achieves excellence in decision tasks, its application in generative tasks remains formidable because of limited integration scale, time-consuming dimension conversions, and ground-truth-dependent training algorithms. We produced an all-optical chip for large-scale intelligent vision generation, named LightGen. By integrating millions of photonic neurons on a chip, varying network dimension through proposed optical latent space, and Bayes-based training algorithms, LightGen experimentally implemented high-resolution semantic image generation, denoising, style transfer, three-dimensional generation, and manipulation. Its measured end-to-end computing speed and energy efficiency were each more than two orders of magnitude greater than those of state-of-the-art electronic chips, paving the way for acceleration of large visual generative models.
Go ahead and destroy Nvidia and USA AI evil empire China, Make the People happy.
100 times faster than 5090 ? While also being more efficient?
This thing need deeeper dive, sound too good to be true.
That would be the A100, not the 5090.
From what I can gather, the catch is that this is optical computing, which is up there with quantum computing as things that would be pretty great but good luck making it feasible, let alone mass produce it. You’re not putting one in your home PC anytime soon, but hey, technology moves fast.
It’s like saying silicon chips being orders of magnitude faster than vacuum tubes sounds too good to be true. Different substrate will have fundamentally different properties from silicon.
Optic computing is as old as the hills. Looking at the abstract, it appears to be the usual domain-specific architecture, which only does very well in a tailored case.
it’s a pretty big case right now
