Automating machine learning will make the technology more accessible to non–AI experts.
At first blush, Scot Barton might not seem like an AI pioneer. He isn’t building self-driving cars or teaching computers to thrash humans at computer games. But within his role at Farmers Insurance, he is blazing a trail for the technology.
Barton leads a team that analyzes data to answer questions about customer behavior and the design of different policies. His group is now using all sorts of cutting-edge machine-learning techniques, from deep neural networks to decision trees. But Barton did not hire an army of AI wizards to make this possible. His team uses a platform called DataRobot, which automates a lot of difficult work involved in applying such techniques.
The insurance company’s work with DataRobot hints at how artificial intelligence might have to evolve in the next few years if it is to realize its enormous potential. Beyond spectacular demonstrations like DeepMind’s game-playing software AlphaGo, AI does have the power to revolutionize entire industries and make all sorts of businesses more efficient and productive. This, in turn, could help rejuvenate the economy by increasing overall productivity. But in order for this to happen, the technology will need to become a whole lot easier to use.
The problem is that many of the steps involved in using existing AI techniques currently require significant expertise. And it isn’t as simple as building a more user-friendly interface on top of things, because engineers often have to apply judgment and know-how when crafting and tweaking their code.
Read the rest here: You Could Become an AI Master Before You Know It. Here’s How.