Thinking about Machine Learning

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Ways to think about machine learning  By Benedict Evans

 I work at Andreessen Horowitz ('a16z'), a venture capital firm in Silicon Valley that invests in technology companies. I try to work out what's going on and what will happen next. 
I write a blog here, do an annual presentation, send out a popular weekly newsletter, talk too fast on podcasts and think aloud on Twitter. 

We're now four or five years into the current explosion of machine learning, and pretty much everyone has heard of it. It's not just that startups are forming every day or that the big tech platform companies are rebuilding themselves around it - everyone outside tech has read the Economist or BusinessWeek cover story, and many big companies have some projects underway. We know this is a Next Big Thing.

Going a step further, we mostly understand what neural networks might be, in theory, and we get that this might be about patterns and data. Machine learning lets us find patterns or structures in data that are implicit and probabilistic (hence ‘inferred’) rather than explicit, that previously only people and not computers could find. They address a class of questions that were previously ‘hard for computers and easy for people’, or, perhaps more usefully, ‘hard for people to describe to computers’. And we’ve seen some cool (or worrying, depending on your perspective) speech and vision demos. 

I don't think, though, that we yet have a settled sense of quite what machine learning means - what it will mean for tech companies or for companies in the broader economy, how to think structurally about what new things it could enable, or what machine learning means for all the rest of us, and what important problems it might actually be able to solve. 

This isn't helped by the term 'artificial intelligence', which tends to end any conversation as soon as it's begun. As soon as we say 'AI', it's as though the black monolith from the beginning of 2001 has appeared, and we all become apes screaming at it and shaking our fists. You can’t analyze ‘AI’.  .... "