The A16Z AI Playbook is here!

Diego Doval
May 12, 2017 · 2 min read
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Today is launch day for the The A16Z AI Playbook! Thanks to everyone that worked on it, in particular Frank Chen and Michael Wee. It was a privilege to be able to contribute and work with them on this project.

It’s an awesome contribution on the part of A16Z. It’s something that’s a bit unusual: different than just a website, or book, or set of samples, it’s all of those combined and more, since the entire thing is also available on github under the MIT License.

Late last year Frank asked me to propose a followup to a post+video he had authored: AI, Deep Learning, and Machine Learning: A Primer. The post and related talk have been very successful, for good reason: it’s concise, clear, and to the point.

To expand on that we focused on providing a more clear view of where and how to get started for non-experts as well as enough background knowledge and references to know what the next step should be, mixing in live code, data transferred, and a more complex example in the form of a full iPhone app. As explained on the site:

We’ve met with hundreds of Fortune 500 / Global 2000 companies, startups, and government policy makers asking: “How do I get started with artificial intelligence?” and “What can I do with AI in my own product or company?”

This site is designed as an resource for anyone asking those questions, complete with examples and sample code to help you get started.

While there are dozens of excellent tutorials available on the web (once you’ve figured out what library or API you want to use — we’ve listed a few of our favorites in the Reference section), we felt a pre-tutorial — a “Chapter 0” if you will, was missing: something that would help you survey the landscape broadly; to give you a sense of what’s possible; and help you think about how you might use artificial intelligence techniques to make your software smarter, your users happier, and your business better.

Go read it! I hope it’s useful and that it inspires other similar efforts. And if you find issues, errors, or things that can be improved please let us know.

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