If you want it well rounded I can see the argument for enterprise but for me personally I programmed one on my workstation and it’s trained on very specific things I think it barely uses up all 24gb vram I have available.
come on, I’ve trained toy size models too, you can’t seriously say they’re even vaguely approaching the capability of models that takes a whole massive server farm weeks or months to train.
Right, and what proportion of enterprise use cases genuinely need an appreciable fraction of that power (because they are wide ranging and non-repeating)?
Anyone that says these things aren’t impressive is kidding themselves. But how do we get from impressive to productivity enhancing in excess of cost? I find smaller specialised models more plausible on that front, but jury is still out on the financials, we’ll find out I guess!
If you want it well rounded I can see the argument for enterprise but for me personally I programmed one on my workstation and it’s trained on very specific things I think it barely uses up all 24gb vram I have available.
come on, I’ve trained toy size models too, you can’t seriously say they’re even vaguely approaching the capability of models that takes a whole massive server farm weeks or months to train.
Right, and what proportion of enterprise use cases genuinely need an appreciable fraction of that power (because they are wide ranging and non-repeating)?
Anyone that says these things aren’t impressive is kidding themselves. But how do we get from impressive to productivity enhancing in excess of cost? I find smaller specialised models more plausible on that front, but jury is still out on the financials, we’ll find out I guess!