Nothing says machine learning can't outperform humans, but it's important to realize perfect machine learning doesn't, and won't, exist.
Mike Loukides is Vice President of Content Strategy for O'Reilly Media, Inc. He's edited many highly regarded books on technical subjects that don't involve Windows programming. He's particularly interested in programming languages, Unix and what passes for Unix these days, and system and network administration. Mike is the author of System Performance Tuning and a coauthor of Unix Power Tools. Most recently, he's been fooling around with data and data analysis, languages like R, Mathematica, and Octave, and thinking about how to make books social. Mike can be reached on Twitter @mikeloukides and on LinkedIn.
The tools of defensive computing, whether they involve mascara and face paint or random autonomous web browsing, belong to the harsh reality we've built.
Is it possible to imagine an AI that can compute ethics?
If behavioral authentication could be made to work, it could be a big part of our future.
It makes no sense at all for programming to be stuck on laptops, but that's where we are.
Machines learn what we teach them. If you don't want AI agents to shoot, don't give them guns.
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.