81–90 of 331 posts
Seems like a much better mission for George Hotz to go on than single handedly trying to fix Twitter.
Why wouldn't AMD throw a few million at this? Worst case they lose a small amount of money, but best case they finally get good software for their hardware. The past decade or so, they haven't been able to create any good software for their hardware. They made small improvements but the competition, Nvidia, has also made improvements to their already good software. It too the point where their software is the reason…
AFAIK the "AMDs drivers are bad" meme is outdated. Sure, their AI/ML software is garbage, but the graphics drivers are fine.
So in the gaming market, Nvidia still commands a huge premium. No AMD card can play Cyberpunk on overdrive 4k.
Seems like a much better mission for George Hotz to go on than single handedly trying to fix Twitter.
I thought he was doing AI self-driving. I see we are now moving the goalposts to "generalized intelligence" so I suppose there was no point for him to put up with just cars anymore.
I was always surprised at how AMD hasn't already thrown a bunch of money at this problem. Maybe they have and are just incompetent in this area. My prediction is AMD is already working on this internally, except more oriented around PyTorch not Hotz's Tinygrad, which I doubt will get much traction.
AMD is limited by numerous patent and other legal issues. For this reason small company that releases everything as open source have some chances to beat AMD on their own hardware.
I’d love to see this succeed, because I own a 7900 XTX already, but there’s so much already built on top of PyTorch. Why would anyone port it all to tinygrad or whatever? Bummer.
Seems like a much better mission for George Hotz to go on than single handedly trying to fix Twitter.
I think that was a great mission for the individual, George Hotz. It's beneficial to be humbled by complex systems and imposing bureaucracy -- it makes future endeavors better informed.
This project fits the pattern of his previous projects: he gets excited about the currently hot thing in tech, makes his own knockoff version, generates a ton of buzz in the tech press for it, and then it fizzles out because he doesn't have the resources or attention span to actually make something at that scale.
In 2016, Tesla and self-driving cars led to his comma one project ("I could build a better vision system than Tesla autopilot in 3 months"). In 2020, Ethereum got hot and so he created "cheapETH". In 2022 it was Elon's Twitter, which led him to "fixing Twitter search". And in 2023 it's NVIDIA.
I'd love to see an alternative to CUDA / NVIDIA so I hope this one breaks the pattern, but I'd be very, very careful before giving him a deposit.
For background, "geohot", is George Hotz, who's a known hacker / tech personality[0] This project fits the pattern of his previous projects: he gets excited about the currently hot thing in tech, makes his own knockoff version, generates a ton of buzz in the tech press for it, and then it fizzles out because he doesn't have the resources or attention span to actually make something at that scale. In 2016, Tesla and s…
> There’s a [Radeon RX 7900 XTX 24GB] already on the market. For $999, you get a 123 TFLOP card with 24 GB of 960 GB/s RAM. This is the best FLOPS per dollar today, and yet…nobody in ML uses it. > I promise it’s better than the chip you taped out! It has 58B transistors on TSMC N5, and it’s like the 20th generation chip made by the company, 3rd in this series. Why are you so arrogant that you think you can make a bet…
Because there's no real evidence that AMD cares about this problem, and without them caring your efforts may well be replaced by whatever AMD does next in the space. Their Brooks language[1] is abandoned, OpenCL doesn't compare well, ROCm is like the Sharepoint of GPU APIs (it ticks boxes but doesn't actually work very well).
> So why not just fix AMD accelerators in pytorch
Why not just buy NVidia? They care deeply about the space, will actually help you if you have trouble, etc etc.
Even using Google TPUs is better: Google will help you too.
While everyone using NVidia isn't great for the market as a whole as an individual company or person it makes a lot of sense.
Read "The Red Team (AMD)" section in the linked article:
> The software is called ROCm, it’s open source, and supposedly it works with PyTorch. Though I’ve tried 3 times in the last couple years to build it, and every time it didn’t build out of the box, I struggled to fix it, got it built, and it either segfaulted or returned the wrong answer. In comparison, I have probably built CUDA PyTorch 10 times and never had a single issue.
This is geohot. He knows how to build software, and how to fix problems.
Note that "Our short term goal is to get AMD on MLPerf using the tinygrad framework."
> There's a clear difference in how AMD and Nvidia measure TFLOPS. techpowerup shows AMD at 2-3x Nvidia, but performance is similar. Either AMD is crazy underutilized or something is wrong. Does anyone know the answer?
From the linked article:
> That’s the kernel space, the user space isn’t better. The compiler is so bad that clpeak only gets half the max possible FLOPS. And clpeak is a completely contrived workload attempting to maximize FLOPS, never mind how many FLOPS you get on a real program