Data as a Moat
We enjoyed this talk by Stanford Professor Andrew Ng. He makes the case that in an era of Artificial Intelligence, access to data with which to train your algorithms can create an economic moat. While the algorithms themselves can be easily replicated or copied, the huge data sets required to train the algorithms can be difficult or expensive to collect. Sometimes scarcity of data shifts the goal from big data to good data as Professor Ng says in this related article: “In many industries where giant data sets simply don’t exist, I think the focus has to shift from big data to good data. Having 50 thoughtfully engineered examples can be sufficient to explain to the neural network what you want it to learn.” Which companies have or are collecting hard-to-replicate data today that will strengthen their competitive positioning tomorrow? This is a question we have incorporated into our investment research.