Ajit Jaokar is a leading expert working at the intersection of Data Science, IoT, AI, Machine Learning, Big Data, Mobile, and Smart Cities. He teaches IoT and Data Science at Oxford and also is a director of Smart Cities Lab in Madrid. Ajit's work involves applying machine learning techniques to complex problems in the IoT and Telecoms domains. You can follow him on twitter @AjitJaokar and his blogs at Future Text. We are beyond thrilled to announce that Ajit will not only be speaking at our Big Data, Berlin meetup February 17, but he will also be at the head of the second workshop of our'Dataconomy Presents' series.

Ian H. Witten is a professor of computer science at the University of Waikato in New Zealand. He directs the New Zealand Digital Library research project. His research interests include information retrieval, machine learning, text compression, and programming by demonstration. He received an MA in Mathematics from Cambridge University, England; an MSc in Computer Science from the University of Calgary, Canada; and a PhD in Electrical Engineering from Essex University, England. He is a fellow of the ACM and of the Royal Society of New Zealand.

Cult indie-folk band the Mountain Goats is known for having fans that are rabidly devoted--and you'd almost have to be like that just to keep up. Led by John Darnielle--a charmingly nerdy 49-year-old songwriter whose professed admirers include Stephen Colbert, and whom Rolling Stone recently dubbed rock's "best storyteller"--the Goats have put out 15 albums since 1994, using simple chord structures as a framework for Darnielle's complex lyrical narratives. Fans have even petitioned to make him America's Poet Laureate, so maybe it's no surprise that Darnielle recently stumbled into literary success as well. His debut novel, Wolf in White Van, about a reclusive, disfigured game designer who seeks refuge in a role-playing game, was a 2014 National Book Award finalist. Out February 7, Darnielle's latest, an enchanting horror mystery called Universal Harvester, follows a video store clerk in small-town Iowa whose customers begin complaining of disturbing footage spliced into their rented VHS tapes. When he's not writing something, Darnielle, raised in a progressive activist household, is out fighting for reproductive justice--serving, for instance, on the board of the National Abortion Rights Action League and performing in support of Planned Parenthood.

The biggest deal in the poker calendar kicks off tomorrow, but only humans will be allowed to sit in on the final table of the World Series of Poker's main event. This Las Vegas knock-out tournament whittled 7,319 entrants down to nine back in July, and after a four-month wait to build media interest in the mainly no-name internet-honed players, this merry band can now get down to playing for the $8.9m (£5.5m) top prize. But has poker bot development reached a level where a bot could be in with a shout for this prize? The short answer is not yet, unless it got lucky. In the short term, luck can override skill, but over time a good player will take a lesser opponent to the cleaners.)

A week after Donald Trump's election, a thirty-year-old cognitive scientist named Maya Shankar purchased a plane ticket to Flint, Michigan. Shankar held one of the more unorthodox jobs in the Obama White House, running the Social and Behavioral Sciences Team, also known as the President's "nudge unit." When she launched the team, in early 2014, it felt, Shankar recalls, "like a startup in my parents' basement"--no budget, no mandate, no bona-fide employees. Within two years, the small group of scientists had become a staff of dozens--including an agricultural economist, an industrial psychologist, and "human-centered designers"--working with more than twenty federal agencies on seventy projects, from fixing gaps in veterans' health care to relieving student debt. Usually, the initiatives had, at their core, one question: Could the growing body of knowledge about the quirks of the human brain be used to improve public policy? For months, Shankar had been thinking about how to bring behavioral science to bear on the problems in Flint, where a crisis stemming from lead contamination of the drinking water had stretched on for almost two years. She wondered if lessons from the beleaguered city could inform the Administration's approach to the broader threat posed by lead across America--in pipes, in paint, in dust, and in soil. "Flint is not the only place poisoning kids," Shankar said. In recent years, behavioral science has become a voguish field. In 2002, the Israeli psychologist Daniel Kahneman won a Nobel Prize in Economic Sciences for his work with a colleague, Amos Tversky, exploring the peculiarities of human decision-making in the face of uncertainty. A basic premise of the discipline they'd helped to create was that people's cognition is bias-prone, and susceptible to the cognitive equivalent of optical illusions. As a result, small tweaks of presentation or circumstance could make a major difference: if a judge rendered a decision about granting parole just before a meal, the inmate's odds for a favorable outcome dipped to near zero; just after the judge ate, the chances rose to around sixty-five per cent. Grocers had learned that they could sell double the amount of soup if they placed a sign above their cans reading "limit of 12 per person." But, for all the field's potential, its advances seemed mostly to have served the private sector. A prominent exception was the "nudge," a notion advanced by the legal scholar Cass R. Sunstein, now at Harvard Law School, and the University of Chicago behavioral economist Richard Thaler, in their 2008 best-seller "Nudge: Improving Decisions About Health, Wealth, and Happiness."

Objective: Errors of omission are a common cause of systems failures. Physicians often fail to order tests or treatments needed to monitor/ameliorate the effects of other tests or treatments. The authors hypothesized that automated, guideline-based reminders to physicians, provided as they wrote orders, could reduce these omissions. Design: The study was performed on the inpatient general medicine ward of a public teaching hospital. Faculty and housestaff from the Indiana University School of Medicine, who used computer workstations to write orders, were randomized to intervention and control groups. As intervention physicians wrote orders for 1 of 87 selected tests or treatments, the computer suggested corollary orders needed to detect or ameliorate adverse reactions to the trigger orders. The physicians could accept or reject these suggestions. Results: During the 6-month trial, reminders about corollary orders were presented to 48 intervention physicians and withheld from 41 control physicians. Intervention physicians ordered the suggested corollary orders in 46.3% of instances when they received a reminder, compared with 21.9% compliance by control physicians (p 0.0001). Physicians discriminated in their acceptance of suggested orders, readily accepting some while rejecting others. There were one third fewer interventions initiated by pharmacists with physicians in the intervention than control groups. Conclusion: This study demonstrates that physician workstations, linked to a comprehensive electronic medical record, can be an efficient means for decreasing errors of omissions and improving adherence to practice guidelines.

A chatbot is an artificial person, animal or other creature which holds conversations with humans. This could be a text based (typed) conversation, a spoken conversation or even a non-verbal conversation. Chatbot can run on local computers and phones, though most of the time it is accessed through the internet. Chatbot is typically perceived as engaging software entity which humans can talk to. It can be interesting, inspiring and intriguing.

Today, we are honored to have Michael Wu, Principal Scientist at Lithium Technologies, participate in our social media Q&A. I was a pure academic track research scientist before I entered the industry. I did research in computational neuroscience and my thesis was on modeling visual processing in the human brain using mathematical approaches, such as statistics and machine learning. Because computer vision is nowhere near the performance of humans in terms of its ability to segment objects, recognize people and understand a scene, my goal was to understand the computations that occur in our brains so we can recreate them in a machine vision system. I joined the industry right after finishing my PhD.

Victor David Scheinman, a pioneer in industrial robotics and a longtime Woodside resident, died Tuesday, Sept. 20, of complications of heart disease. Mr. Scheinman, starting as a graduate student at Stanford University, developed a robotic arm that allowed the use of robotics in industry to leap forward. A version of the arm, called the Scheinman Arm, was used for research in dozens of research labs, inspiring a generation of robotics engineers. Stanford professor Bernie Roth, who was at first Mr. Scheinman's adviser at Stanford and later his close friend, said that Mr. Scheinman's robotic arm was unique because it included sensors that gave the feedback to the computer controlling it. Professor Roth said Mr. Scheinman was "tenacious and very active," always trying to figure out how things worked and fixing anything that was broken.

The 2012 publication Race against the Machine makes the case that the digitalization of work activities is proceeding so rapidly as to cause dislocations in the job market beyond anything previously experienced [1]. Unlike past mechanization/automation, which affected lower-skill blue-collar and white-collar work, today's information technology affects workers high in the education and skill distribution. Machines can substitute for brains as well as brawn. On one estimate, about 47% of total US employment is at risk of computerization [2]. If you doubt whether a robot or some other machine equipped with digital intelligence connected to the internet could outdo you or me in our work in the foreseeable future, consider news reports about an IBM program to "create" new food dishes (chefs beware), the battle between anesthesiologists and computer programs/robots that do their job much cheaper, and the coming version of Watson ("twice as powerful as the original") based on computers connected over the internet via IBM's Cloud [3]. On the darker side, you do not have to be paranoid to be paranoid about the potential technologies that the super-secret computers of the US National Security Agency (NSA) have on their digital drawing-boards.