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• Post #2653457

  I think this is the way. A certain number of times of “[coworker] wasn’t asked because they only respond with LLMs, so I just ask the LLMs directly. I am not sure what [coworker]’s expertise is anymore, I just don’t consult them” and I suspect coworker may in fact stop responding with LLMs.

• Post #935879

  Traditional software was developed by humans as an artifact that, and to the degree that humans improved the software for some task, got better, but it was not guaranteed. Windows 11 is proof of that, and there are a laundry list of regressions and bugs introduced into software developed by humans. I acknowledge you say usually and especially for open source — I lukewarm agree with that statement but disagree that large LLMs or other generative models will follow this trend, and merely want to p...

• Post #531648

  Current models are speculated at 700 billion parameters plus. At 32 bit precision (half float), that’s 2.8TB of RAM per model, or about 10 of these units. There are ways to lower it, but if you’re trying to run full precision (say for training) you’d use over 2x this, something like maybe 4x depending on how you store gradients and updates, and then running full precision I’d reckon at 32bit probably. Possible I suppose they train at 32bit but I’d be kind of surprised.