Nick Pentreath is a principal engineer at IBM, a member of the Apache Spark project management committee (PMC) and author of Machine Learning with Spark (Packt Publishing, December 2014). In this podcast, Pentreath covers the basics of feature hashing and how to use it for all feature types in machine learning. He will speak on this topic on Wednesday, 8 February 2017, at 12:20 p.m. Eastern in Room 302/304 at Spark Summit East 2017. Register for Spark Summit East 2017 in Boston, Massachusetts, 7–9 February 2017, and learn how IBM is helping organizations accelerate the use of Spark solutions to solve big problems, build faster time-to-business applications and develop a blueprint for innovation.

The Falcons are facing 3rd and goal on the Patriots' 5 yard line. Matt Ryan takes the snap and hands off to Devonta Freeman, already running hard at the goal line. Then, with a crunch audible to the topmost rows of NRG Stadium, Freeman is brought down by Dont'a Hightower right at the goal line. Touchdown?! Silence falls as all eyes turn… not to the referees on the sidelines (there aren't any) but to giant LCD panels behind the end zones. The screens remain black for several long moments until "TOUCHDOWN" lights up.

Reinforcement Learning (RL) was another much-discussed topic at NIPS with an excellent tutorial by Pieter Abbeel and John Schulman dedicated to RL. John Schulman also gave some practical advice for getting started with RL. One of the best papers of the conference introduces Value Iteration Networks, which learn to plan by providing a differentiable approximation to a classic planning algorithm via a CNN. This paper was another cool example of one of the major benefits of deep neural networks: They allow us to learn increasingly complex behaviour as long as we can represent it in a differentiable way. During the week of the conference, several research environments for RL were simultaneously released, among them OpenAI's Universe, Deep Mind Lab, and FAIR's Torchcraft. These will likely be a key driver in future RL research and should open up new research opportunities.

For almost three weeks, Dong Kim sat at a casino in Pittsburgh and played poker against a machine. Kim, 28, is among the best players in the world. The machine, built by two computer science researchers at Carnegie Mellon, is an artificially intelligent system that runs on a Pittsburgh supercomputer. And for twenty straight days, they played no-limit Texas Hold'Em, an especially complex form of poker in which betting strategies play out over dozens of hands. About halfway through the competition, which ended this week, Kim started to feel like Libratus could see his cards.

Foregoing a good night's sleep may wreck the brain's ability to make new memories. A new study from Johns Hopkins University School of Medicine demonstrated that a key purpose of sleep is to recalibrate the brain cells responsible for learning and memory, solidifying lessons learned for when the sleeper is awake. Using a mouse model, the researchers discovered several important molecules that govern the recalibration process, as well as evidence that sleep deprivation, sleep disorders and sleeping pills can interfere with the process. Graham Diering, Ph.D., the postdoctoral fellow who led the study, explained that the results from the mouse study can be used to make determinations about the human brain. "Our findings solidly advance the idea that the mouse and presumably the human brain can only store so much information before it needs to recalibrate," he said in a statement.

Futurist Jack Uldrich warns of technology threats at a conference sponsored by Store Capital. Jack Uldrich flashed a photo showing a homeless man accepting donations through his cellphone. "The world is changing in strange ways," he quipped. It was a lighter moment against a backdrop of some anxiety and uncertainty as Uldrich, an author and futurist, warned a small-business audience in Scottsdale this past week about the accelerating technological changes that already have devastated taxi-cab companies, video-rental stores, some retailers and many other businesses, with more disruption ahead. It was one segment of a conference designed not just to warn businesses about looming threats but to help them identity things they might not be doing well -- tips ranged from honing your marketing message to encouraging a culture of innovation, from acknowledging failures will happen to hiring young adults as "reverse mentors."

Tired of your barista giving you attitude, spitting in your coffee if you only mention Trump, or misspelling your name on your morning cup of joe? Surely a robot could do better. Well, we are about to find out, because on Monday, Cafe X opened its very first robotic cafe in San Francisco's Metreon shopping center Digital Trends reports. Promising "precision crafted specialty coffee in seconds, the way the roaster intended," Cafe X thinks that anything a human can do, its machines can do better. Nicknamed Gordon, after a Cafe X employee, this robot mans, or robots, two standard professional coffee machines in order to serve up espressos and lattes. In the San Francisco location, customers can grab a cup of coffee with beans from AKA Coffee, Verve Coffee Roasters, or Peet's.

Four professionals poker players were convinced they found a flaw in the sophisticated artificial intelligence software that was beating them in a tournament of no-limit Texas Hold'em. The win demonstrates the increasing sophistication of artificial intelligence software as computer scientists work to digitally replicate, and ultimately improve upon,...

Machine learning in 2017 will become a mainstream tool for communications providers struggling to transform data overload into actionable analytics, according to Argyle Data. "The telecommunications industry is drowning in data," said Padraig Stapleton, VP of engineering at Argyle Data. Stapleton said fraud and financial analysts alike are overwhelmed by the struggle to control and harness this fire-hose of information into actionable analytics. There is just too much IP traffic going across mobile networks for humans to review, detect and respond to fraud in the traditional ways such as discovering fraud and writing preventative rules. Machine learning does all the grunt work for analysts, sifting through data in real time and providing output instantly in understandable, accessible formats," said Stapleton.

Last November, during the Web Summit in Lisbon, David Marcus, VP of Messaging Products at Facebook, asked the following question: Who wants to call a brand? He was referring to the ordeal of having to get in touch with a customer service apparatus. Very often, this process is time consuming, stressful and leaves the customer frustrated, an extremely negative outcome for any brand. The current development in AI and machine learning has the potential to solve this situation by bringing a pleasant, time-efficient experience for customers, and efficiency and precious data to the brand. Brands need to be more accessible.