There’s a language to proteins, there’s a language to chemicals, and if we can understand the language and represent it in computer science, imagine … - Jensen Huang

20 years ago, all of this [artificial intelligence] was science fiction. 10 years ago, it was a dream. Today, we are living it.

If you were building a chip company and you were taping out a chip, the tapeout of a chip is around $100 million, just the tapeout. Not to mention the tools, which are probably another $100 million, and not to mention all the engineers, all the systems you’re bringing up, things like that. In order to build one of our chips, it’s a few billion dollars. And we’re just one chip company. There’s a whole bunch of chip companies. When they tape out a chip it’s no less than $25 million. Writing, developing a large language model–taping out a chip these days, what the software industry is learning is that building these large language models is kind of like taping out a chip.

The inference, the scale of inference business has gone through a step function, no doubt, and the type of inference that is being done right now where you know that video will have generative AI added to it to augment the video either to enhance the background, enhance the subject, relight the face, do eye reposing, augment with fun graphics, so on and so forth. All of that generative AI work is done in the cloud and so video has generative AI. We know that there’s imaging and 3D graphics for generative AI, video for generative AI.