John Carmack pointed out (and I learned it here at HN) that what training really needs is the *sign" of each individual gradient parameter. I.e., you can quantize gradient to -1, 0 and 1 and still have neural network learn much of the dataset.
Why isn't John Carmack working for OpenAI? Hell, why did he waste years at Meta to work on a VR headset and NOT AI? He even announced he wants to focus on AGI but he missed out on literally all the action.
That game engine was over 3 decades ago! John is one of the sharpest minds I've ever seen, if he's passionate on AGI, he surely has much deeper understanding what he's doing than the AI trendies on social media.
> It is interesting that things still train even when various parts are pretty wrong — as long as the sign is right most of the time, progress is often made.
