681–690 of 1001 posts
I like the chart Bloomberg has of the top 10 largest single day stock drops in history. 8 out of the 10 are NVDA (Meta and Amazon are the other two).
adjusted for inflation?
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Why is there this implicit assumption that more efficient training/inference will reduce GPU demand? It seems more likely - based on historical precedent in the computing industry - that demand will expand to fill the available hardware. We can do more inference and more training on fewer GPUs. That doesn’t mean we need to stop buying GPUs. Unless people think we’re already doing the most training/inference we’ll eve…
Over the long run maybe, but for the next 2 years the market will struggle to find a use for all this possible extra gpus. There is no real consumer demand for AI products and lots of backlash whenever implemented eg: that Coca Cola ad. It's going to be a big hit to demand in the short to medium term as the hyperscalers cut back/reasses.
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> the models are going to get better/smaller/faster overtime reducing our reliance on the GPU Yes, because we've seen that with other software. I no longer want a GPU for my computer because I play games from the 90s and the CPU has grown powerful enough to suffice... except that's not the case at all. Software grew in complexity and quality with available compute resources and we have no reason to think "AI" will be…
because that's what history shows us. back in the 90s, MPEG-1/2 took dedicated hardware expansion cards to handle the encoding because software was just too damn slow. eventually, CPUs caught up, and dedicated instructions were added to the CPU to make software encoding multiple times faster than real-time. Then, H.264 came along and CPUs were slow for encoding again. Special instructions were added to the CPU again,…
He fixes the cable?
But seriously, video encoding isn't AI. Video encoding is a well understood problem. We can't even make "AI" that doesn't hallucinate yet. We're not sure what architectures will be needed for progress in AI. I get that we're all drunk on our analogies in the vacuum of our ignorance but we need to have a bit of humility and awareness of where we're at.
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Honestly, you'd be shocked at how much gaming you can get done on the integrated gpus that are just shoved in these days. Sure, you won't be playing the most graphically demanding things, but think of platforms like the Switch, or games like Stardew. You can easily go without a dedicated GPU and still have a plethora of games. And as for AI, there's probably so much room for improvement on the software side that it w…
Just look at how much insects get done with just a few neurons to run together...
Traders are saying not doing multitoken prediction, not using Sharpe ratio adjusted rewards, using reward models, and not compressing KV cache tokens by >90%, were supposed to be worth hundreds of billions of dollars of future expected revenue flow, at least according to other traders. I say to the traders: you should have just stuck to reading arxiv, TPOT, and jhana twitter for the past 2 years, rather than listenin…
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DeepSeek's stuff is actually more dependent on nVidia shovels. They implemented a bunch of assembly-level optimizations below the CUDA stack that allowed them to efficiently use the H800s they have, which are memory-bandwidth-gimped vs. the H100s they can't easily buy on the open market. That's cool, but doesn't run on any other GPUs. Cue all of China rushing to Jensen to buy all the H800s they can before the embargo…
I was thinking about that, but don’t those same optimizations work on H100s? and the concepts work on every other chip from Nvidia and every other manufacturer’s chip I still think this is bullish: more people will be buying chips once cheaper and more accessible, and the things the will be training with be 1,000% to 10,000% larger
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because that's what history shows us. back in the 90s, MPEG-1/2 took dedicated hardware expansion cards to handle the encoding because software was just too damn slow. eventually, CPUs caught up, and dedicated instructions were added to the CPU to make software encoding multiple times faster than real-time. Then, H.264 came along and CPUs were slow for encoding again. Special instructions were added to the CPU again,…
> Can you guess what the next step will be? He fixes the cable? But seriously, video encoding isn't AI. Video encoding is a well understood problem. We can't even make "AI" that doesn't hallucinate yet. We're not sure what architectures will be needed for progress in AI. I get that we're all drunk on our analogies in the vacuum of our ignorance but we need to have a bit of humility and awareness of where we're at.
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> AI doesn't seem to be one of those things where society as a whole will say, "we have enough of that; we don't need any more". Really? Has anyone made a useful, commercially successful product with it yet?
ChatGPT has over $10 million paying subscriber. No I am not counting the people using the API programmatically
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> the models are going to get better/smaller/faster overtime reducing our reliance on the GPU Yes, because we've seen that with other software. I no longer want a GPU for my computer because I play games from the 90s and the CPU has grown powerful enough to suffice... except that's not the case at all. Software grew in complexity and quality with available compute resources and we have no reason to think "AI" will be…
because that's what history shows us. back in the 90s, MPEG-1/2 took dedicated hardware expansion cards to handle the encoding because software was just too damn slow. eventually, CPUs caught up, and dedicated instructions were added to the CPU to make software encoding multiple times faster than real-time. Then, H.264 came along and CPUs were slow for encoding again. Special instructions were added to the CPU again,…
H.266 32K encoding being slow on cpu
90% of the comments in this thread make it clear that knowing about technology does not in any way qualify someone to think correctly about markets and equity valuations.