Mark Cuban on Why You Need to Study Artificial Intelligence
Reading HN I worry that we&#x27;re going to have <i>the opposite problem</i> - a glut of people will try and (badly?) learn ML and then realize there aren&#x27;t enough ML jobs.<p>I&#x27;ve a PhD and held ML-engineer positions in a few different companies - I&#x27;ve good industry awareness.<p>Most applied ML, for most companies, right now, is actually relatively simple models (hand-coded rules! logistic regression! You&#x27;d be shocked how common these are.)  The bulk of the work is data cleaning, gathering, integration, deployment, productisation, reliability, avoiding pathological cases, special-casing, Product, UX.  You do need ML specialists who understand the stuff, to make it all work and come together - but the ratio of ML specialists to the wider team is low.  Maybe 1 or 2 specialist on a team of 10 for an ML heavy product.<p>This is going to remain the case IMO.  Yes, there will be small teams, in highly resourced organizations (GOOG, FB etc), academic research labs, or occasional hard-tech startups, who do new model development.  Maybe if AI becomes huge, you&#x27;ll see more traditional Fortune 500s spin up similar efforts.<p>But there&#x27;ll be a much wider set of people&amp;businesses applying and tuning well understood approaches, rather than doing new model development. And you just don&#x27;t need as many ML specialists, for that approach.<p>Even with deep learning, the tooling will advance. I mean, even look at all the research papers describing applications at the moment - so many of them are using pre-trained models.  Industry will be similar.  Tooling will advance, and you&#x27;ll be able to do increasingly more with off-the-shelf pieces.<p>I think ML is absolutely going to have a big impact - I buy at least some of the hype. But should all developers, or even a substantial minority of developers, start learning ML as a career imperative?  I don&#x27;t think so.<p>Finally, it takes serious time to learn this stuff.
Its easy to dabble (and worthwhile doing - its fun; and sometimes you can do powerful things in a using tools in a very blackbox manner!).  But actually thoroughly learning it takes time.  It takes serious time to build statistical intuition, as just one example.<p>We could easily end up with a great many career developers who have a specialization in ML, frustrated they never get to use it.