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Check out the BLOOM models if you want to see a first stab at that. If you can find an economical way of running it though, let me know.
A cluster of 6 year old 24GB NVIDIA Teslas should do the trick...they run for about $100 apiece. Put 12 or so of them together and you have the VRAM for a GPT3 clone.
But yes, it's a very good value.
For perspective the likes of Instagram and Twitter have take from a few months to a few dozen months to get to a million users all while doing less work to service a request for a "page."
Hats of to OpenAI for not falling over more often under a hug of death that doesn't seem to be letting up.
[1] https://twitter.com/sama/status/1599668808285028353 [2] https://www.afr.com/technology/chatgpt-takes-the-internet-by...
LLM's are incredibly expensive to run. I imagine the huge demand that ChatGPT is seeing would make any cloud vendor sweat if you were to suddenly lump it on top of the usual demand. To me it's entirely unsurprising that OpenAI would have trouble keeping up. Good luck to them.
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I think from Apple’s POV, this is great news. Moore’s Law has been dead for years, and there has been no good reason to upgrade your devices until now. AI means it’s 1990 again, and you need to buy a new device every 18 months because the performance leap is so meaningful to the UX.
I'd agree if Apple were in the business of making datacentre infrastructure. Nobody is running these large scale models on their personal devices. Sure, some of the image generation tech is seeing personal use, so you'd have a point there, but these immense language models are something else entirely.
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Seems like the more likely option. They could be used to live scan every post to work out what it's about and it's sentiment. Similar to how ChatGPT can work out if you are asking for something it won't answer, they could be used to work out if you are saying something not allowed.
Why stop there, when many of them could transform it into something that is allowed in-flight?
Everybody, as far as anyone could tell, in complete agreement with the regime, all the time.
Signing and encryption will come in useful. But not sure of much good it will do under an authoritarian regime.
Gpt3 will fit on iPhone locally in 3 generations
Truly remarkable.
I wonder how OpenAI will cope on it’s own… unless Stability strikes again, with it’s own LLM?
Apparently ChatGPT went from zero to a million users in five days[1], at a cost of "single-digits cents per chat." For perspective the likes of Instagram and Twitter have take from a few months to a few dozen months to get to a million users all while doing less work to service a request for a "page." Hats of to OpenAI for not falling over more often under a hug of death that doesn't seem to be letting up. [1] https:…
To put this in perspective: the outage was 52 min. The total number of employees OpenAI have are 375. The launch date was just some months ago. At Google, the Cloud SQL dashboard was unavailable for around 12 hours a couple of weeks ago if I read this correctly: https://status.cloud.google.com/incidents/xg2qrL1UuSJiPDZALJ... The total number of employees of Google are 156 500. Google Cloud was launched 2008. So when…
I am available for hire to teach a thing or two to Google (and OpenAI).
/s
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A cluster of 6 year old 24GB NVIDIA Teslas should do the trick...they run for about $100 apiece. Put 12 or so of them together and you have the VRAM for a GPT3 clone.
Note: I assume you mean the Tesla K80. It's actually 2 GPUs on one card. But yes, it's a very good value.
Why is this? Did some large cloud vendor just upgrade?
Are there any deals like this on AMD hardware? Not having to deal with proprietary binary drivers is worth a lot of money and reduced performance to me. A lot.