Are you on your game when it comes to AI?
Every day I read articles about artificial intelligence (AI), and industry giants are already reinventing themselves around deep learning in particular. But it strikes me that even though the industry is clearly embracing AI (with Google even going “AI first”), many people simply don’t know where to begin. I have a few tips on where to start and recently wrote them up for Forbes. Here are a few steps that any engineering team can take right now to get up to speed.
If you’re finding yourself hesitant to jump in with AI (but you know you need to start exploring it), the two most important steps you can take to get things going are: 1) take advantage of open source resources for training; and 2) identify a “low-hanging fruit” project to which you can apply what you learn quickly (keeping in mind that you can see results for your business in as little as six weeks). Vision and text classification projects are often a good place to start.
Then when it comes to identifying a project or feature that is ripe for AI, I recommend asking yourself the following to zero in on a starter project:
Where are the big data sets that you can leverage?
Where can you leverage data to give users a predictive answer?
What are your pain-points in your workflow? Targeting some “grunt work” which is slightly too complex for conventional automation solutions could be a good place to start.
With respect to educating yourself (and your team), I highly recommend taking a look at TensorFlow — an open source library for machine intelligence was originally the brainchild of Google’s machine intelligence research team. It just launched version 1.0, and it’s a great place to start looking at what’s developing. Then there’s Amazon’s deep learning resources (check out Lex and Polly) and Facebook’s explainer videos. I also read experts in the field — I follow and keep up-to-speed with both Danny Britz and Andrej Karpathy’s blog.
Getting going with AI and deep learning isn’t nearly as difficult as you might think. If you take advantage of open source libraries and the insights of experts and identify a starter project, you could be well on your way to leveraging AI to advance your business and stay competitive.