(EDITOR: This is the best article I have seen on something that is going to further impact Medicine, Big Data and Artificial Intelligence. So, grab a cup of strong Costa Rican coffee and read this comprehensive piece of great work!)
I have a challenge for you.
In a few seconds, I want you to stop reading this article, and follow the instructions below.
Not being one to enjoy surprises, I decided to spend my free time learning as much about the space (and what the future holds) as possible. ML and AI are having a huge impact on our lives, and their roles are only increasing. The better informed you are, the better prepared you’ll be to handle these changes as they happen.
Rather than sit here and pretend I know everything there is to know about ML and AI, I’m going to hand you the resources I use to educate myself.
I hope you will use them too.
How to Use This List
There is already a ton of technical content being produced about artificial intelligence and machine learning. This list is a primer for non-technical people who want to understand what machine learning makes possible.
To develop a deep understanding of the space, reading won’t be enough. You need to: have an understanding of the entire landscape, spot and use ML-enabled products in your daily life (Spotify recommendations), discuss artificial intelligence more regularly, and make friends with people who know more than you do about AI and ML.
News: For starters, I’ve included a link to a weekly artificial intelligence email that Avi Eisenberger and I curate (machinelearnings.co). Start here if you want to develop a better understanding of the space, but don’t have the time to actively hunt for machine learning and artificial intelligence news.
Startups: It’s nice to see what startups are doing, and not only hear about the money they are raising. I’ve included links to the websites and apps of 307+ machine intelligence companies and tools.
People: Here’s a good place to jump into the conversation. I’ve provided links to Twitter accounts (and LinkedIn profiles and personal websites in their absence) of the founders, investors, writers, operators and researchers who work in and around the machine learning space.
Events: If you enjoy getting out from behind your computer, and want to meet awesome people who are interested in artificial intelligence in real life, there is one place that’s best to do that, more on my favorite place below.
NYAI has managed to rise above the noise and organize ~1,500 researchers, students, founders, and investors who are genuinely awesome people.
The impacts that machine learning and AI have on our world will not be felt in isolation. These changes will affect all of us. NYAI’s monthly events are the best way, that I’ve found so far, to learn about, collaborate on and network over emerging trends in artificial intelligence.
Did I miss any awesome people/companies/resources? Let me know on Twitter!
Machine Learning and AI are having a huge impact on our lives. Our mission is to create space for discussion and learning that helps you stay informed and well-prepared to handle these changes as they happen.
Thanks to Rizwan Habib for co-authoring this post and to Nick Frost, Andy Sparks, Avi Eisenberger, Jason Cohen, Rob McInerney and Dakota McKenzie for reading and talking through earlier drafts.