A New Wave of Automation: a new report on Machine Intelligence

MI_Report_Cover_smallToday SogetiLabs launches its first report on a new wave of automation: Machine Intelligence. As part of a series of four, SogetiLabs Research Institute VINT, explores this Next Big Thing in IT. You can download our first report on Machine Intelligence for free from this location.

The idea that an artificial brain could compete with that of humans lives for many years. In 2016, it’s exactly sixty years ago computer scientist John McCarthy suggested to work on Artificial Intelligence (AI) with ten men for two summer months on the campus of Dartmouth College. And now there’s this excitement in the market: after decades of working on concepts, the tools finally are ready to realize that vision. We are developing new cognitive systems, self learning computers, computers that can speak in human language and get to know us better than anyone or anything else.

This new wave of automation is cause for numerous speculations about our future. Many science fiction classics are based on this theme. For instance Arthur C. Clarke’s “Dial F for Frankenstein” from 1964, in which the telephone is born as a little baby, and as it becomes more intelligent, it starts to dominate our society. Among others, Elon Musk, Bill Gates and Stephen Hawking alert for such effects of “true” AI. But men’s relationship with machines can also be very warm and affectionate. Startling example; the recent success of Microsoft’s chatbot Little Bing. Millions of people in China confide their deepest secrets to this machine.

It is no coincidence that we are now putting this old issue high on the IT agenda. There are two simple explanations. First of all, there is a breakthrough in the field of the hardware. Watson, who beat the two champions of the TV game Jeopardy, has since shrunk from room-filling to the size of a pizza box. And today we’re talking about creating a super brain that fits into the smartphone. This remarkably high computing power means that the concepts from the past will now shape the future.

The second explanation for the excitement has to do with the amount of data. Only ten years ago we started to move to the proverbial second half of the chessboard. This is the metaphor that Andrew McAffee uses in his book “The Second Machine Age”, to explain that data grows exponentially since 2006. That is crucial, because Big Data is the sine qua non for the artificial brain. Therefore, the self learning capabilities of intelligent machines (machine learning) could only start to develop the last few years. Machine Intelligence (MI) is the term to use nowadays. With an impending breakthrough of machine intelligence, the interesting question is what change that will bring.

 

The Internet of Things in Retail

IoT in RetailThe Internet of Things (IoT) in Retail has been redefining the buying and selling experience for decades.  Remember when bar code scanners first arrived in our local stores speeding the checkout process? Or the first time we entered a credit card number into our browser to make an online purchase? Or the moment we became both customer and clerk as we checked ourselves out at a register? The Internet of Things has actually changed the course of the retail business. No wonder then that investment in the Internet of Things in the worldwide retail industry is expected to hit $37.6 billion and is expected to grow 20-35% per year over the next several years.

Today retail is synonymous with handheld devices that empower the customer and the retail associate. These devices and digital signs on shelves and walls provide a truly mobile experience and allow dynamic pricing, personalized coupons, and purchases anywhere in the store. Both buyers and sellers have easier access to up-to-the minute product, pricing, inventory and competitive information. And that’s a huge transformation in the retail value chain. Sogeti has helped

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Expert Talk: Peter Norvig (Google) on Machine Learning and AI interaction

Today in our video section: Peter Norvig, Director of Research (formerly Director of Search Quality) at Google Inc. We spoke with Norvig about machine-learning, instant translation and the human-computer relationship.

“Creating the right answers seems to be better than waiting for somebody to tell you the right answers.”

 

Machine learning: from extrapolating on answers to creating them

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Expert Talk: Steven Baker on Watson and human-machine interaction

Today in our video section: Steven Baker, former BusinessWeek writer and author of Final Jeopardy and The Numerati. 

“We lack humility. Watson in that sense can teach us a lot, because we could learn a lot by questioning the very premises that we take for granted.”

“We have to look at Watson’s weakness and move into areas where the machines are weak”

Watson as methodology – humility to be wrong

The Watson Project – making sense of unstructured data

Machine analysis is just another layer of human analysis