This YouTube video (Jason M. Lemkin, May 19, 2018) discusses how advances in AI—especially voice recognition—are becoming transformative for industry. The speaker frames data as "potential energy" that must be used, attributes recent voice-recognition improvements to two factors (large training corpora and inexpensive compute), and situates AI in a hype cycle while predicting it will be transformative.
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. And why is that? Well, it's really two factors. One 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 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 AI has been a pretty big change in the industry. I think we're still in the hype cycle on it, but maybe today. But it's going to be, I think, transformative.
