Last week, NVIDIA (NASDAQ:NVDA) released its first-quarter fiscal 2017 report, which included some impressive results. The graphics-processor maker posted Q1 revenue of 1.3 billion, an increase of 13% year over year, and non-GAAP earning per share were up 39% from the year-ago quarter to 0.46. Wall Street analysts had been expecting revenue of around 1.26 billion and EPS of 0.41. NVIDIA co-founder and CEO Jen-Hsun Huang said the revenue and earnings growth were spurred on by all of the key segments of its business. "We are enjoying growth in all of our platforms -- gaming, professional visualization, datacenter and auto," Huang said in a press release.

Man Group is changing the focus of an Oxford University department it funds to machine learning. Investors have been urged to reject its pay plans later this month. City Talk: Barratt Developments sees strong market, Compass profit rises, Experian plans share buyback. Bank league tables can be a surprisingly thorny issue. Cut the right way, anyone can be number one.

Big data analytics and the Internet of Things are still relative newcomers. Given how quickly technology moves, though, it's not surprising that their next incarnations are already being talked about: cognitive analytics and a much-grown Internet of Things (IoT). We all know about the Internet of Things: it's data from a host of Web-connected devices that can be analyzed and studied, just like traditional data analytics. But what is cognitive analytics? Well, think back to old sci-fi shows.

While in Hollywood films hi-tech robots are portrayed as a threat, Chinese engineers might be able to change your mind. We take a closer look at the role artificial intelligence might play in the future RT LIVE http://rt.com/on-air Follow us on Twitter http://twitter.com/RT_com Follow us on Google http://plus.google.com/ RT (Russia Today) is a global news network broadcasting from Moscow and Washington studios.

Video Friday is your weekly selection of awesome robotics videos, collected by your dance-challenged Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. SNUMAX is a "multi-functional soft robot" developed by Seoul National University's Biorobotics Laboratory, which won the RoboSoft Grand Challenge this year. "Boomf is the noise a marshmallow makes when it falls through your letterbox and lands on your doormat."

Today's security systems usually fall into one of two categories: man or machine. So-called "analyst-driven solutions" rely on rules created by human experts and therefore miss any attacks that don't match the rules. Meanwhile, today's machine-learning approaches rely on "anomaly detection," which tends to trigger false positives that both create distrust of the system and end up having to be investigated by humans, anyway. But what if there was a solution that could merge those two worlds? What would it look like?

IBM plans to launch a cloud-based version of Watson's cognitive computing technology, designed solely to zero in on cybersecurity language, as a part of a year-long research project, the company announced Tuesday. The Watson for Cyber Security platform is touted as the first technology to offer cognition of security data. Watson will pull the majority of its cognitive data from the X-Force research library: a threat intelligence platform with 20 years of security research, details on 8 million spam and phishing attacks and more than 100,000 documented vulnerabilities. "Even if the industry was able to fill the estimated 1.5 million open cybersecurity jobs by 2020, we'd still have a skills crisis in security," Marc van Zadelhoff, general manager of IBM Security said in a statement. "The volume and velocity of data in security is one of our greatest challenges in dealing with cybercrime."

The use of machine learning has allowed us to solve many of our problems. It can allow us to effectively manage bandwidth, possibly predict solar flares, automate the rooting out of weeds, and so much more. The ability to learn and experience the world much as humans do allows our machines to be better at the tasks we give them. Sometimes, they're even better than humans are. US chemists have created a machine-learning algorithm that studies successful and failed experiments in order to beat humans at predicting ways to make crystals.

In the early 1990s, executives and managers welcomed information technology -- databases, PC workstations, and automated systems -- into their offices. They saw the potential for significant business gains. Computers wouldn't just speed up processes or automate certain tasks -- they could upset nearly all business processes and allow executives to rethink operations from the ground up. And so the reengineering movement was born. Powerful machine-learning algorithms that adapt through experience and evolve in intelligence with exposure to data are driving changes in businesses that would have been impossible to imagine just five years ago.

Video Friday is your weekly selection of awesome robotics videos, collected by your dance-challenged Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. SNUMAX is a "multi-functional soft robot" developed by Seoul National University's Biorobotics Laboratory, which won the RoboSoft Grand Challenge this year. "Boomf is the noise a marshmallow makes when it falls through your letterbox and lands on your doormat."