TightWind is written by Kyle Baxter. Stay Hungry. Stay Foolish.

Andrew Ng is helping lead a group at Google dedicated to making giant advances with neural networks:

It was a shift that would change much more than Ng’s career. Ng now leads a new field of computer science research known as Deep Learning, which seeks to build machines that can process data in much the same way the brain does, and this movement has extended well beyond academia, into big-name corporations like Google and Apple. In tandem with other researchers at Google, Ng is building one of the most ambitious artificial-intelligence systems to date, the so-called Google Brain.

Pretty good piece about the increasing overlap of neuroscience and neural network research for technological purposes, but what I want to emphasize is how much Google has invested in neural networks (or “artificial intelligence” generally, if you’d rather, but that term is pretty misleading). Both Apple’s and Google’s futures depend heavily on using user data and other data sources to provide value for users, and Google has a huge advantage here because they’ve been investing heavily in it for a very long time. It’s just as important to Apple, but Apple had to acquire the Siri team to gain the capability. That’s a huge disadvantage.

This isn’t just about speeding up voice recognition or making it more accurate, although that is an advantage Google Now has over Siri—using voice recognition in Google’s iOS search app feels much faster than Siri because it shows you what it thinks you’re saying as you say it. It’s much more than that; since this has been something very important to Google for a long time, and something of an intrinsic organizational competence, Google can move much quicker to develop the capability in Google Now than Apple can. Apple must move even quicker to make it a skill for Apple, too, and to take advantage of their own unique resources that Google doesn’t have.