Hinton on Back Propagation: I don’t think it’s how the brain works

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

Hinton is quoted as saying, with respect to back propagation, “I don’t think it’s how the brain works”. You can read the full article here. Back Propagation To oversimplify, in Back Propagation, the influence of each neuron is rewarded based on how well it predicts something. Accurate predictions are rewarded with more influence. Bad predictions […]

The Assembly Line And The Artificial Intelligence Line

Posted on Posted in Artificial Intelligence, Big Data Science, Data Driven Culture, Data Science, Machine Intelligence, Machine Learning, Marketing Science, Technology

The other I likened the process for taking apart a Job To Be Done to taking a part a lobster. There’s a very effective way to decompose any problem with enough energy. And then I watched The Founder on Netflix and admired the McDonald brothers using a classic technique in management science to refine a […]

The Marketing Science of Data Science of Marketing Science

Posted on Posted in Artificial Intelligence, Business, Machine Learning, Marketing Science

Earlier in the month, I dined under the space shuttle Endeavour with some of the best minds in marketing science. One mind remarked: “That’s why I bring a glossary with me, oh, you want to do supervised learning? Oh you mean regression? Oh, okay, now we can talk… We’ve been talking to managers about these […]

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 […]

Into the Trough: BitCoin, Machine Learning, Social Analytics

Posted on Posted in Big Data Science, Business, Data Science, Machine Learning, Technology

Into the trough of disillusionment with the hyped technologies! The canary in the coal mine for me, with respect to BitCoin, is this post. Look, nobody has enjoyed more popcorn around BitCoin than I have. From Coinye to Dogecoin, crypto-currencies have delivered the lulz. Do I believe there’s a slope of enlightenment for crypto-currency? Absolutely. Do […]

The Creativity of Data Science for Creative Content

Posted on Posted in Business, Data Science, Design Thinking, Machine Learning, RecSys

Let’s start with a story. Daan did a traditional fast follow. He calls it Netherflix. His story was: “It’s like Netflix…for The Netherlands!”. At first, he buys rights on the cheap, pays for digital subtitling, and has a successful kickoff. He gets through to 10% household penetration, or roughly 700,000 subscribers, with an annualized gross revenue of […]

How to think about Content Scoring and Audience Scoring

Posted on Posted in Data Science, Machine Learning, Marketing Science, Predictive Analytics

A score serves as an ultimate abstraction or summary. That’s especially true in sport. “Who won?” “The Blue Jays. 11 to 5.” The Blue Jays won because they moved men more often across one specific plate more often than the other team. This is all very American. A brief period of action. Collect statistics about […]