Way back in 2013, Toyota showed off its self-driving testbed for autonomous vehicle features like safety braking and automatic lane control. Now, the company is pulling the dust sheets off the second-generation of the ride, which is designed to do a whole lot more. The Toyota Research Institute 2.0 Advanced Safety Research is the first that the company can say was built entirely in-house. The technology has been built on top of a current-generation Lexus LS600hL, kitted out with layered and overlapping LIDAR, Radar and camera sensors. This, paired with machine vision and machine learning, should reduce the car's dependency on high-definition maps that may not yet exist.

High-performance graphics cards, typically associated with gaming, have become popular over the last few years in an area many might not expect: artificial intelligence. Many experts attribute recent acceleration of success in AI to a wider availability and use of graphics processing units (GPUs), as their advantages include cores designed for running multiple tasks simultaneously, which can efficiently handle the vector and matrix operations that are prevalent in deep learning. Training and deploying state of the art deep neural networks is very computationally intensive, and, while modern GPUs offer high density computation, researchers need more than a fast processor -- they also need optimized libraries, and tools to efficiently program so that they can experiment with new ideas. Bryan Catanzaro, VP of Applied Deep Learning Research at NVIDIA, joined us at the 2017 Deep Learning Summit in San Francisco, to share expertise on GPUs and platforms for deep learning, as well as giving insights on the latest deep learning developments at NVIDIA. I asked him some questions at the summit to learn more about his work. What motivated you to begin your work in deep learning?

Simply reading someone's facial expressions and body language is not enough to understand the experiences of others, new research has found. The new study found that people who'put themselves in the shoes of others' are far more empathetic. While most people assume they can understand another's emotions simply by watching them, the study's results suggest otherwise. Simply reading someone's facial expressions and body language is not enough to understand the experiences of others, new research has found. The new study found that people who'put themselves in the shoes of others' are far better at understanding them (Stock image) But the findings showed they were actually better at estimating how they had felt if they simply viewed the pictures again.

Marketing and sales seemed to be much easier in the past. Customers simply visited a retail shop, where they could ask a knowledgeable salesperson about a product they discovered in a local newspaper. In recent years, the ubiquity of the internet and a state-of-the-art technology changed everything. Customers became prosumers, well informed about the product before the purchase. And what is even more important, customers frequently use a variety of channels: online and traditional stores, mobile apps, online auctions, price comparison websites, social media and more. Today, in spite of all the available technologies, life is more challenging for both marketers and salespeople.

Amper, a startup that offers AI-powered music composition, is announcing that it has raised $4 million in funding. The round was led by Two Sigma Ventures, with participation from Foundry Group, Kiwi Venture Partners and Advancit Capital. Amper previously raised funding from Brooklyn Bridge Ventures. You might not expect a film composer like Drew Silverstein (who founded the company with Sam Estes and Michael Hobe) to create a product that is ostensibly competes with his own work, but Silverstein doesn't see that way. Instead, he pitched Amper as a fast, affordable and royalty-free way to create the music for more "functional" projects (like commercials a or short online videos), where most companies would currently use pre-written stock music.

Don't be alarmed, but a computer just beat 11 professional poker players in a 3,000 hand match of the incredibly complex Texas Hold'em, using'intuition'. DeepStack is the first computer programme to outplay humans at the game, which it played over a period of four weeks. Card players tend to rely on microexpressions – tiny subconscious flashes of emotion across the face that last no longer than a quarter of a second. The computer, which was developed by scientists at the University of Alberta, Charles University in Prague and Czech Technical University, honed its'intuition' through deep learning – allowing it to reassess its strategy with each move. Professor Michael Bowling, from Alberta, said: 'Poker has been a longstanding challenge problem in artificial intelligence.

March 2, 2017 --Computer engineers have created some amazingly small devices, capable of storing entire libraries of music and movies in the palm of your hand. But geneticists say Mother Nature can do even better. DNA, where all of biology's information is stored, is incredibly dense. The whole genome of an organism fits into a cell that is invisible to the naked eye. That's why computer scientists are turning to microbiology to design the next best way to store humanity's ever-increasing collection of digital data.

Nearly half of consumers expressed interest in biometrics and other forms of authentication to deliver enhanced security in a new survey commissioned by payments firm Mastercard. The company's Mastercard Digital Payments Study found that 43 percent of respondents wanted to know more about biometrics and other forms of authentication. Mastercard wrote that New developments in facial recognition and fingerprint and touch authentication drove over half of biometric/authentication conversations at 51 percent. Meanwhile, facial recognition conversations focused on the Mastercard Identity Check Mobile app, Google's Hands Free app and a Snapchat patent to incorporate a payments platform with real time services. "Technology is making the promise and the potential of a less-cash life a reality for more people every day," said Marcy Cohen, vice president of digital communications at Mastercard.

The Terminator, Ava and bicentennial man Andrew Martin have one thing in common -- all are robots with human tissue that makes them look like real humans. While they may pass for humans in their own cinematic universe, they are now viewed differently by real-life scientists. Apparently, scientists are now seeing the most practical use of humanoid robots in the field of medicine. For two University of Oxford biomedical researchers Pierre-Alexis Mouthuy and Andrew Carr, building robots with human tissue is very possible and should be the next breakthrough in regenerative medicine. They say that robots are actually what the human race needs if people want tissue transplants that actually work and do not require human donors.

In a feat reminiscent of the controversial victory by supercomputer'Deep Blue' over world chess champion Garry Kasparov, a computer program has managed to beat a string of professional poker players at the game. DeepStack, as it was called, defeated 10 out of 11 players who took part in a total of 3,000 games as part of a scientific study into artificial intelligence. The 11th player also lost, but by a margin that the researchers decided was not large enough to be statistically significant. This is not the first time a computer has won at poker. Libratus, a program developed by Carnegie Mellon University academics, won $1.76m (£1.4m) from professionals in January, for example.