What if Total Addressable Market can’t be estimated accurately?

Posted on Posted in Data Science, Economics, Machine Intelligence, Marketing Science

What if Total Addressable Market can’t be estimated accurately? What then? What is Total Addressable Market (TAM)? Total Addressable Market, or TAM, is the number of buyers who are Willing To Pay (WTP) for a solution to a problem they have now, or are Willing To Pay (WTP) your firm instead of the firm they’re currently […]

Goal Formation

Posted on Posted in Business, Data Driven Culture, Data Science, Decision Neuroscience, Design Thinking, Economics, Machine Intelligence, Technology

Bart Gajderowicz delivered a great talk at Machine Intelligence Toronto about how people go through stages in accomplishing a goal [1]. The talk was about homelessness and AI approaches to public policy. I instantly saw a connection to all sorts of tensions that people endure when they set out on a goal. To distill the […]

Predicting technical change in three variables

Posted on Posted in Data Driven Culture, Machine Intelligence, Machine Learning, Marketing Science, Predictive Analytics, Technology

A great mind in public policy told me, just this last September, that people are really bad at judging the rate of technological change and when it’ll affect them. It’s like standing on a railway. You can see the train out there. Some people assume that the train is going to hit them very soon. […]

Machine Intelligence, Artificial Intelligence, Machine Learning

Posted on Posted in Artificial Intelligence, Machine Intelligence, Machine Learning

You’re going to hear a lot more about Artificial Intelligence (AI) more generally, and Machine Intelligence more specifically. Valuation is the core causal factor. Here’s why: We’ve gotten pretty good at training a machine on niche problems. They can be trained to a point to replace a median-skilled/low-motivated human in many industries. Sometimes they can make […]