It was a treat to see these three – Yoshua Bengio, Yann Lecun, and Geoffrey Hinton – for an afternoon. Easily the best three consecutive hours I’ve ever seen at a conference. They remarked that Canada continues to invest in primary research. And this is a strength. Much of the exploratory work these three executed in the 80’s, 90’s and naughties was foundational to industrial applications which came after. Much of reinforcement and deep learning has moved on into industrial application. For the three grandfathers of deep learning, all of these algorithms and methods move into the realm of solved problems. For those of us in industry, there remains a lot of work to realize the benefits of deep learning.[…]

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 system on a tennis court. And I loved it. They really refined hamburger and frenched fry delivery. And then this morning I read that Andrew Ng in working on a new coursera course for AI. And I’m thankful for his initiative and optimism. Out of those three threads, this one post. The Assembly Line The assembly line was an American invention for Americans. It could[…]

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 paying to solve a problem. Why is TAM important? TAM determines the life and death of a firm. The leading cause of startup failure, and perhaps all business failure in general, is the failure to penetrate and/or retain TAM (Including bureaucratic capture and rent-seeking). In this context, I’m concerned about the introduction of a new product into the market in an effort to generate both[…]

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 concept, let’s start off with the idea that people have goals, people have emotions, and that time moves forward. As people make progress towards their goals, their emotions change over time. They start off in a good mood, in a state of uninformed optimism. Then, as negative information overwhelms their ignorance, they enter into a state of informed pessimism. So much negative information builds up[…]

In general, information retrieval from analytics systems becomes harder with the degree of customization (It gets harder to find things over time). That customization is frequently an expression of the values of a culture over time. The inertia of the technical debt caused by early customization is greater than the inertia of a data driven culture. There are no silver bullets. The rest of this post unpacks that paragraph. Information retrieval from analytics systems becomes harder with the degree of customization Assume a vanilla implementation of Open Web Analytics. Or Google Analytics. Or Adobe Analytics. It’ll tell you a lot about a web system on its own. The optimization objective that is at the core of the business will typically[…]

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 I believe that’s imminent? Nope. Banks are apex ruminants. The lessons from BitCoin have to be fully digested before something really good comes out of it. Machine learning. Huge potential and the best is yet to come. The first wave around machine learning gave us Netflix and Amazon. And then the bloom came off the rose a bit. And now there’s deep learning and we’re[…]

Some reports have adblocking penetration at anywhere between 10% and 40%. Some publishers are blocking content from the adblockers. Others are making the ads unskippable with ad block. Broken systems are interesting, aren’t they? The system of advertising is broken. Here’s the best that I can explain it from as many perspectives as I can rally. Advertising in the early days, radio, was incredibly lucrative. The development of a consumer economy in the roaring 20’s and consumerism in general was huge. A marketer could spend $1 on advertising and got $4 back. Paid media was crazy effective. The same went for television. And then there was a sort of grand bargain, a big deal, struck between creatives, those that create[…]

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 about 60 million Euros. The strength of the Euro lets him raid the Anglosphere and he can stock 10,000 hours of content reliably [1]. He gets through the struggle of getting his stack to deliver content and minimize churn. He’s able to host and deliver 10,000 hours reliably, in spite of supporting video players across 11 different front end platforms, and the costs associated with hosting,[…]

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 that brief period. ???. Profit. And it’s easy. Baseball is nice for the 1 to 1 correspondence of points to a single event. American football and basketball are spicier. Cricket, with all due respect to my antipodean friends, is ridiculous. There’s so much more to the performance of The Blue Jays or the Australian National Cricket Team. But the score is the ultimate summary. There’s[…]

That title, ‘morphing the lean startup’, may be technical jargon. But it is literal. And brief. I have a few thoughts to share about them both. Morphing There’s a very small sliver of research in the Marketing Science on morphing. Two papers, ‘website morphing‘, and its adtech successor, ‘morphing banner advertising‘, stand out as giants. This technology makes snap changes to a digital user experience. The ultimate reason why you’re not hearing more about morphing in adtech is because paid agencies can’t figure out how to scale the creative necessary to drive it. I’m convinced that morphing is the ultimate promise I bought into back in the mid-nineties – the perfect intersection of recsys and experience.     It requires an extreme[…]