Data Science

Opining about the future of AI at the recent Brilliant Minds event at Symposium Stockholm, Google Executive Chairman Eric Schmidt rejected warnings from Elon Musk and Stephen Hawking about the dangers of AI, saying, "In the case of Stephen Hawking, although a brilliant man, he's not a computer scientist. Elon is also a brilliant man, though he too is a physicist, not a computer scientist." This absurd dismissal of Musk and Hawking was in response to an absurd question about "the possibility of an artificial superintelligence trying to destroy mankind in the near future." However, in Commander #1's immortal words, "We've analyzed their attack, sir, and there is a danger." Continue Reading →

When you analyze the effects of fraud, viewability and ad blocking on the digital display advertising business, then add the ever-increasing abilities of the traffic launderers to game the system, you reach an inevitable conclusion: ad tech has evolved into a toxic ecosystem that is killing itself, and it is taking digital advertising with it. Continue Reading →

Sometimes I walk into a room and say, “Alexa, what’s the temperature outside?” She answers by speaking the current temperature followed by an abbreviated weather report. She’s so human-like, I have to resist the temptation to say “Thank you” when she finishes. Importantly, Alexa is not a she; it is a component of Amazon's Echo natural language processing system. Amazon has anthropomorphized Echo with a female voice and a feminine name, which makes it easy to call Alexa a “she.” Should we be polite when we speak to it, or is it OK to be abrupt or even abusive? The device won’t care. It doesn't have feelings; but how will we teach our children to differentiate between machines that sound and act like people, and other disembodied voices that actually are people? Continue Reading →

Generally speaking, there are two kinds of companies in the world: data rich and data poor. The richest of the data rich (Google, Facebook, Amazon, Apple, etc.) are easy to name. But you don't need to be at the top of this list to use data to create value. You need to have the tools in place to turn information (data) into action -- that's what the data rich do that the data poor and the data middle class do not. Continue Reading →

Because the velocity of data is increasing and will always increase, the need for data literacy is increasing and will always increase. This does not mean that to be successful executive you have to become a data scientist -- quite the contrary. It means that in order to be a successful executive, you need to understand how data is turned into action, be familiar with the methods of data science and data scientific research, and be able to think strategically about how to use data to create value for your business. All other things being equal, there is a significant difference between being literate and being fluent. Continue Reading →

How soon will TV transform from wall-mounted 4K flat-screens to a 99-cent app in a VR/AR App Store? That's a question few will ponder this week as the National Association of Broadcasters gathers in Las Vegas for the NAB Show 2016. TV has both defined and enlarged mass communication for more than a half-century. No one in their right mind would suggest that big-screen TVs might go away – ever! Well, no one ever said I was in my right mind. Continue Reading →

Tay is a combination chatbot and AI system designed by Microsoft to "engage and entertain people where they connect with each other online through casual and playful conversation." It was specifically "targeted at 18 to 24 year olds in the U.S., the dominant users of mobile social chat services in the U.S." If the words "designed" and "targeted" are off-putting, then you're really not going to care for one of the system's recent, now infamous, tweets ... but, there is much, much more to learn from Microsoft's mistake. Continue Reading →

What made move 37 so interesting is that no one expected it. It was early in game two of the million-dollar Google DeepMind Challenge Match, and AlphaGo, an artificial intelligence (AI) system developed by Google, placed its 19th stone on a part of the game board that no human Go master would have considered. Some called it a "mistake." Others called it "creative" and "unique." But considering that AlphaGo went on to win its third game in a row against one of the strongest Go players in the world, the move should probably have been called what it really was: "intuitive." Continue Reading →

Hello Barbie! is an IoT-enabled Barbie Doll with blonde hair, blue eyes and a built-in surveillance system. She's not the first of her kind (and she won't be the last), but here's what you should know about bringing it, or any connected device, into your home. Continue Reading →

Bots generate more than half the traffic on the public Internet. This is indisputable. In fact, the Association of National Advertisers believes that advertisers will lose $6.3 billion globally to bots in 2015. This will not stop until someone (the marketers, the government, the justice department) makes it stop because everyone – the ad networks, the traffic sellers, the bot creators, the publishers, the ad agencies, the trading desks, the DMPs, the SSPs, everyone – except the marketers – is making money. Continue Reading →