We need AI researchers who are actively trying to defeat AI systems and exposing their inadequacies.
A framework for thinking about AI.
Is it possible for an AI to create revolutionary art?
Greg Brown's new book, Programming Beyond Practices, is a thoughtful exploration of how software gets developed.
Shared learning: It's what we do at O'Reilly, and it's what we’d like to share with you.
If you look carefully at how humans learn, you see surprisingly little unsupervised learning.
Mike Loukides and Ben Lorica examine factors that have made AI a hot topic in recent years, today's successful AI systems, and where AI may be headed.
A lot can happen in biotechnology with plain old organisms.
Open source has victories, but there are battles that still need to be fought.
Whether our prejudices are overt or hidden, our artificial intelligentsia will reflect them.
Finding patterns isn't really a question about random processes; it's a question about the human brain.
Pete Warden’s instructions on building a deep learning classifier looked so simple, I had to try it myself.
If there's anything humans should learn from AlphaGo, it's that our survival depends on constantly looking at the data.
The "sharing economy" has nothing at all to do with sharing.
A lot of young artists are building brand equity and audience, but fame doesn't equal money and you can't eat brand equity.
The crisis of reproducibility is an opportunity to get better at doing science.
The Programmer's Oath is missing one essential element: the customer.
The revolution in automation is fueling biology at scale.
I don't want barely distinguishable tools that are mediocre at everything; I want tools that do one thing and do it well.
Our fears of automation aren’t due to problems of artificial intelligence, but of human intelligence.