Data is potential energy until you train on it. Voice recognition got accurate because of massive training datasets and cheaper computing power. That same pattern of abundant data plus cheap compute is about to transform AI across every industry.
Chapters
I mean, data is really like potential energy, so it doesn't do you any good if you just store it away somewhere. It used to be that voice recognition systems were just garbage. Every word would have a mistake in it. And now suddenly they all work. Yeah, right. And why is that? Well, you know, it's really two factors. One is, is that we have enough data to provide a a meaningful corpus as a training set, and we have inexpensive compute power that we can use to sort of, you know, run the training models on and just make them better and better and better. And I think that's generally true across a lot of AI. And, you know, AI has been a pretty big change in the industry. I think we're still in the hype cycle on it, but, you know, maybe today, but, you know, it's going to be, I think, transformative.