91–100 of 169 posts
I’m bearish on new hardware for AI training. The most important thing is the software stack, and thus far everyone has failed to support pytorch in a drop-in way. The philosophy here seems to be “if we build it, they’ll buy it.” But suppose you wanted to train a gpt model with this specialized hardware. That means you’re looking at two months of R&D minimum to get everything rewritten, running, tested, trained, and w…
What does the programming model look like for one of these (like at the assembly level)? I’m not even sure what to google.
I’m bearish on new hardware for AI training. The most important thing is the software stack, and thus far everyone has failed to support pytorch in a drop-in way. The philosophy here seems to be “if we build it, they’ll buy it.” But suppose you wanted to train a gpt model with this specialized hardware. That means you’re looking at two months of R&D minimum to get everything rewritten, running, tested, trained, and w…
> The philosophy here seems to be “if we build it, they’ll buy it.” Supposedly Cerebras is already profitable, so it's hardly a situation where they are building something and hoping people buy it eventually. > That means you’re looking at two months of R&D minimum to get everything rewritten, running, tested, trained, and with an inferencing pipeline to generate samples. Again, based on the companies representations…
There is a very specific test for “supports pytorch / tendorflow”: show an MLPerf imagenet resnet benchmark. It’s impossible to fake that. If you come anywhere close to TPUs in tensorflow, people (like me) will leap: https://mlcommons.org/en/training-normal-06/
Till then, it’s a “proof, please” type of situation.
Earlier quoted context omitted.
It's because you made a false analogy. AI isn't literally "the future". Billions of $ are being invested in deep-learning focused AI right now (which you call "the future"), and yes it could be a bubble and it could burst. You can disagree, but it's still a sensible thing to predict.
By bursting you mean humanity will never create artificial intelligence? Or you mean that there will be a cool off period as for example what happened with quantum physics at some point? Because it sure looks to me that there is no future without AI regardless of cool off periods. That makes my statement true. If you think humanity will never progress from where we are now then we pretty much are on very opposite sch…
I’m bearish on new hardware for AI training. The most important thing is the software stack, and thus far everyone has failed to support pytorch in a drop-in way. The philosophy here seems to be “if we build it, they’ll buy it.” But suppose you wanted to train a gpt model with this specialized hardware. That means you’re looking at two months of R&D minimum to get everything rewritten, running, tested, trained, and w…
There is also webGPU which is experimental on Safari and Chrome. But that doesn’t touch the ML accelerators on the M1.
I’m bearish on new hardware for AI training. The most important thing is the software stack, and thus far everyone has failed to support pytorch in a drop-in way. The philosophy here seems to be “if we build it, they’ll buy it.” But suppose you wanted to train a gpt model with this specialized hardware. That means you’re looking at two months of R&D minimum to get everything rewritten, running, tested, trained, and w…
> “if we build it, they’ll buy it.”
This is literally how any new thing is invented and commercialized.
Earlier quoted context omitted.
I don’t think it’s straightforward to do a head to head comparison. from: https://www.youtube.com/watch?v=yso2S2Svdlg @ 25:14 James Wang: "If a model doesn’t fit into a GPU’s HBM, is it smaller when it’s laid out in the Cerebras way relative to your 18 gigabytes?" Andrew Feldman: "It is — it’s smaller in that we hold different things in memory than they do. One can imagine a model that has more parameters than we can…
Are there any good resources out there describing in practice how existing training workloads are distributed among GPUs? (using tensorflow, pytorch, or whatever else?). I'm curious how the problem effectively gets sliced.
Super curious, how much do one of these cost? Like 10K,100K, or 1M range?