This article reads as rather lazily-written. Consider: Allstate car insurance already allows users to take photos of auto damage and settle their claims on a

This article reads as rather lazily-written. Consider: Allstate car insurance already allows users to take photos of auto damage and settle their claims on a mobile app. Technology that’s been trained on photos from past claims can accurately estimate the extent of the damage and automate the whole process. How do we make the jump from very well-established (even boring) use of tech--sharing photos--to computer vision and analysis that can value a vehicle, understand the damage both visible and concealed, and assign useful figures for both repair and value? And won't such results be disputed at an astonishing rate? I mean, sure, it's a nice idea, but there does not seem to be any bridge at all from one concept to the other. The good news is that emerging marketplaces for AI algorithms and datasets, such as Algorithmia and the Google-owned Kaggle, coupled with scalable, cloud-based infrastructure that is custom-built for artificial intelligence, are lowering barriers. Renting someone else's algorithm sounds like a very risky proposition, as they can easily drive you out of the market when it becomes worthwhile to do so (see also Amazon's strategy around fungible third-party items that are profitable).