Recently I took the Coursera Machine Learning course from Stanford and got to implement a lot of these kinds of algorithms (HIGHLY recommend the course). \u00a0This guy took it a step or two further and added some clever visualizations and additional training tricks. \u00a0Very good work – especially considering it was done by a seaming amateur implementer.<\/p>\n
It’s fascinating how we can now write small neural nets like this and very quickly train our computers to do work not only as good as us, but in growing numbers of\u00a0cases, better than the BEST humans in the world could do. \u00a0The implications are staggering…and somewhat disconcerting. \u00a0What happens when we have enough compute and enough data that our racks of machine learning systems can do all the analysis and optimization of every facet of our society? \u00a0What does that leave us to do, and how does our economic system work when many of these thinking jobs go away?<\/p>\n
While this has been argued all the way back to the industrial revolution, there is some growing work by more respected people that we are turning a tipping point (http:\/\/www.businessinsider.com\/technology-is-destroying-jobs-and-it-could-spur-a-global-crisis-2015-6<\/a>). \u00a0Or more interestingly, do we go through another era much like the industrial revolution in which broad swaths of the population become cogs in a bigger machine until we re-adjust. \u00a0Much food for thought and social rumination…<\/p>\n