At the moment (April 2019), the economy is in a weird quantum superposition of doom (yield curve inversion) and exaltation, with Lyft recently joining the public markets (always loved the irony of the term…)
I’ve been talking to a few people involved in driverless cars and AI lately, asking them…. when? They usually tell me soon, the problem they have is that the main drawback with learned neural networks is that they are almost impossible to debug. You can try to get insight on how they work (see the fascinating Activation Atlas), but it’s really difficult to rewire them.And it’s actually pretty easy to hack them — you can easily do some random addition to find noise that will activates the whole network. In the real world, you can put stickers at just the right location and… make every other car crash. Pretty scary… Continue reading








