I mean your article literally suggests that CUDA was a misstep. It failed to bring supercomputing to the masses until they got bailed out by AI coinciding with

I mean your article literally suggests that CUDA was a misstep. It failed to bring supercomputing to the masses until they got bailed out by AI coinciding with needing supercomputer powers. > In marketing cuda, Nvidia had sought a range of customers, including stock traders, oil prospectors, and molecular biologists. At one point, the company signed a deal with General Mills to simulate the thermal physics of cooking frozen pizza. One application that Nvidia spent little time thinking about was artificial intelligence. There didn’t seem to be much of a market. > Despite the snub, Hinton encouraged his students to use cuda, including a Ukrainian-born protégé of his named Alex Krizhevsky, who Hinton thought was perhaps the finest programmer he’d ever met. In 2012, Krizhevsky and his research partner, Ilya Sutskever, working on a tight budget, bought two GeForce cards from Amazon. Krizhevsky then began training a visual-recognition neural network on Nvidia’s parallel-computing platform, feeding it millions of images in a single week. “He had the two G.P.U. boards whirring in his bedroom,” Hinton said. “Actually, it was his parents who paid for the quite considerable electricity costs.” Basically Hinton thought CUDA was a better platform and kept encouraging his acolytes to utilize it with NVidia completely ignoring it. For what it’s worth ChatGPT and LLMs are not the start of the story. I remember seeing Hinton present his research in 2009 and thought it was a revolutionary step forward. It took a much longer amount of time for NVidia to notice that they should be marketing CUDA to AI. They did so around the same time that Google started building their own inference accelerators for Tensorflow. So at that point NVidia was getting multiple signals already from a big customer that there’s something here.