Tags: databases



Tuesday, July 10th, 2018

Ways to think about machine learning — Benedict Evans

This strikes me as a sensible way of thinking about machine learning: it’s like when we got relational databases—suddenly we could do more, quicker, and easier …but it doesn’t require us to treat the technology like it’s magic.

An important parallel here is that though relational databases had economy of scale effects, there were limited network or ‘winner takes all’ effects. The database being used by company A doesn’t get better if company B buys the same database software from the same vendor: Safeway’s database doesn’t get better if Caterpillar buys the same one. Much the same actually applies to machine learning: machine learning is all about data, but data is highly specific to particular applications. More handwriting data will make a handwriting recognizer better, and more gas turbine data will make a system that predicts failures in gas turbines better, but the one doesn’t help with the other. Data isn’t fungible.

Wednesday, April 19th, 2017

Approximate Text Search Made Easy

A step-by-step explanation by Henrik on how he implemented fuzzy search on his music site—something I could do on The Session. He even talks about expanding this to work with ABC notation.