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The main issue it's CUDA. Most ML developers use it, or use libraries that depends on CUDA as an envoirments. There are brand agnostic alternatives, but they a
by javchz 3y ago
The main issue it's CUDA. Most ML developers use it, or use libraries that depends on CUDA as an envoirments.
There are brand agnostic alternatives, but they are less popular and usually slower.
- TradingPlaces 3y agoOP here. That’s exactly right. In the article, I describe CUDA and the rest of the software suite as their competitive moat to hardware competition from AMD or AI accelerators.
- p4ul 3y agoYes, CUDA is their moat. And it's a very deep moat, filled with sharks, alligators, and mines. It will take a truly massive effort to unseat CUDA and NVIDIA as the dominant software/hardware tools for deep learning. I'm curiously watching Intel and their OneAPI platform; but it just feels like they're starting from so far behind. And Intel hasn't exactly had a stellar few years on top of that.
- TradingPlaces 3y agoDon’t sleep on the Modular inference engine https://www.modular.com/engine https://www.modular.com/engine
- p4ul 3y agoI had not yet heard of them! Thank you!
- TradingPlaces 3y agoChris Lattner and Tim Davis. Google in on A-round https://www.modular.com/about https://www.modular.com/about
- lmpdev 3y agoI really hope CUDA doesn't end up being the PostScript of ML
- javchz 3y agoMe too. My hope is that Intel, AMD, Google, MS and others eventually catch up with a common standard and the software doesn't require special customization as an end user (on paper something like DirectML has potential for this). Another thing that could happen with so much money in the AI hype train right now, I wonder if we will see something similar to bitcoin, with special ASIC chips optimized for specific models like ChatGPT, CLIP or Stable Diffusion, or some shift to FPGAs.
- LegitShady 3y agoI don’t think its CUDA. If it was CUDA people would use AMDs Radeon Open Compute and save tons of money on cards with more memory. The issue is that the Radeon platform isn’t well developed, and AMD is charging as much as they can get for their cards just like Nvidia. if they had working competitive compute they’d also charge as much as Nvidia, and make more money on fewer cards sold. I think there’s just something with card architecture that makes it not as good as Nvidia for this purpose. Just like mining bitcoins or VR, sometimes card architecture makes a difference.
- WeMoveOn 3y agoEh its more so that the entire ecosystem is built on CUDA. I don't think most developers would care or even notice if you swapped out CUDA for something that'll work seamlessly with the existing Python libraries. Sadly such an alternative doesn't exist and probably won't exist.