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So yeah Nvidia is mask off now and it is 100% an AI hardware company with a side business of graphics chips
Nvidia has always been a tech company that also happens to make consumer graphics cards.
Hmm, define "always" because at the time of riva and Tnt they definitely were a graphics card only company
Yeah, I misspoke there, but for most of recent memory they've been doing big things besides consumer graphics cards. Nvidia launched its professional oriented graphics Quadro product line in 2000. They launched CUDA architecture in 2006 which opened up parallel processing capabilities of GPUs for use in science and research. They entered the data center and cloud computing market in the early 2010s, and in 2015 they launched the DRIVE product line.
Unfortunately I know Nvidia since the big GC wars with matrix, 3dgx, ATI and the guys that built Kyro...
And before that it was a bit mining company, with a side line of gaming graphics hardware.
It’s always been that way. Whether it’s been AI or something else. Nothing wrong with that.
Not all bad, compared to crypto the vector transformations done for ml are relatively similar to those done by graphics processing. So any innovations on the ml front will probably yield improvements in graphics.
Company focusing on their profits and not my 4k dlss witcher 3 ?!?!
I'm sure the cost to the consumer will remain exactly the same, or somehow increase.
I'm not worried about that. There will be open competition, because most of this stuff is open-source. Cheaper hardware will open the door for anyone like you or me to set up our own services. Anyone can set up a server with their own hardware (or rent it from Amazon or wherever) and run their own chatbot (with blackjack! and hookers!) instead of using ChatGPT.
This is already possible on consumer hardware, just not with the biggest and best networks. Right now, if I wanted to run, say, BLOOM (an open-source LLM), I'd need to spend close to $100K on hardware. Obviously, that's out of reach for a hobbyist, so I'm limited to using smaller, less advanced networks like LLaMa or GPT-J. Cheaper hardware will help break the hold that the big players currently have over the industry.
if I wanted to run, say, BLOOM (an open-source LLM), I’d need to spend close to $100K on hardware
Doesn't that dozens of notes with over a terabyte of RAM each? And state of the art networking?
Sounds closer to $100M than $100K.
If you want to train your own network like they did, you'd want something like that, yeah, but to run the trained network you "only" need ~360GB of memory.
For context, even if you wanted to run this in CPU, there are currently no A5 mobos (Ryzen 7000 series) that support more than 192GB of memory. You literally can't even run it on high-end consumer hardware.
this post was submitted on 10 Aug 2023
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