If you are a fan of Iron Man or the Avengers franchise, you know that when Tony Stark is talking to Jarvis, he is talking with Artificial Intelligence or AI. According to computer science, an'intelligent machine' is a rational agent who perceives its environment and takes those actions, which will maximize its chances of success for the specified goal. In simple terms, intelligence that is exhibited by the machines is termed as'Artificial Intelligence' or AI. Ever wondered how Google Now, Siri, and Cortana help you find information? They are all AI applications used on different platforms.

Wells Fargo -- The bank will eliminate product sales goals for retail bankers and strengthen oversight, controls, and training. Wells Fargo will be the subject of a Senate Banking Committee hearing into its sales practices, after the bank settled a case with regulators by paying a 185 million penalty. The panel wants to question CEO John Stumpf about the practices that led to the case. UnitedHealth Group -- The health insurer's Optum unit and Quest Diagnostics formed a partnership aimed at reducing billing complexity, as well as providing more transparency into health care costs. Separately, UnitedHealth was rated as a "top pick" at Jefferies because of attractive valuation and a best-in-class management team.

Why we urgently need to measure AI's societal impacts How will artificial intelligence systems change the way we live? This is a tough question: on one hand, AI tools are producing compelling advances in complex tasks, with dramatic improvements in energy consumption, audio processing, and leukemia detection. There is extraordinary potential to do much more in the future. On the other hand, AI systems are already making problematic judgements that are producing significant social, cultural, and economic impacts in people's everyday lives. AI and decision-support systems are embedded in a wide array of social institutions, from influencing who is released from jail to shaping the news we see.

Imagine if you can, Japanese punk rock in the background and a motorcycle speeding through the streets of Tokyo. The camera pans around, over the shoulder of the rider and up ahead is a raging monster. A truck pulls up beside the motorcycle and a crane/lift contraption pulls it inside. They spring into action battling the beast as the A.D. Police arrive and bumble around. The armored suits crush the monster and vanish.

Microsoft's attempt to use machine learning to improve on the Duckworth-Lewis method in cricket has been dismissed by the current custodian of the system. For the uninitiated, the Duckworth-Lewis method, or D/L method for short, is used to calculate the score that the team batting second in a limited overs cricket match needs to reach if the match is affected by rain. For example, if the team batting first scores 400 in 50 overs for five wickets, but rain reduces the second team's innings to 40 overs, the D/L method may put forward a score of 300. It was invented by statisticians Frank Duckworth and Tony Lewis and was first used in 1997 in a match between England and Zimbabwe. It is now regularly used at matches at all levels.

Baidu Inc, the Chinese internet search giant, has created a US 200 million venture capital unit to invest in artificial intelligence projects. The new unit, Baidu Venture, is chaired by chief executive Robin Li Yanhong and will focus on projects also in augment reality and virtual reality. "The first-phase investment is planned at US 200 million and the fund will invest in projects that are at their early stage," the company said. The unit will be independently run from Baidu's existing investment teams, allowing it to make fast decisions without having to go through complicated internal approval process, it added. Baidu is betting big on AI technology as a fresh income stream amid a slowdown in its search and advertising business.

Not quite breathtaking speed, yet events of 1895 were still history in the making. It's hard to imagine anything that could transform the way we move around quite as much as this. Yet industry experts recently gathered at Frost & Sullivan's Intelligent Mobility conference in London to consider innovations that could be every bit as history making as the arrival of the first motor cars. From the rise of electric vehicles to the arrival of a super-connected world, to a shift towards car-sharing apps and a need to keep crowded cities moving, mobility is rapidly evolving. Add artificial intelligence (AI) to the equation, and the changes ahead seem even more dramatic. Our forefathers gazed in wonder at the horseless carriage – are we now staring at a world once more about to be transformed?

US chipmaker Nvidia Corp showed off on Monday a smaller and more efficient artificial intelligence computer for self-driving cars, saying it would power Baidu's mapping and autonomous vehicle technology. Chinese web services company Baidu will deploy Nvidia's new Drive PX 2 as its in-vehicle car computer for its self-driving system, Nvidia said in a press release as it unveiled the computer at the GPU Technology Conference in Beijing. As more carmakers develop plans for self-driving technology to roll out in their vehicles in the next decade or less, Nvidia is trying to lower the barriers to entry, providing powerful computers to help automakers enter the market. Earlier this month, Nvidia and Baidu announced a partnership to develop a full self-driving car architecture from the cloud to the vehicle using both companies' expertise in artificial intelligence (AI). Nvidia said its new Drive PX 2 computer uses 10 watts of power and is half the size of the original version, launched in January.

It's a problem we can all relate to: sitting in traffic and waiting for a green light. While waiting, you may have even pondered how you would try to improve traffic efficiency--surely there's got to be some way for everyone to get to work on time. But ponder no longer, because a team of engineers from Tsinghua University in China has handed the problem over to machines. The team's recent study makes use of deep reinforcement learning algorithms to optimize traffic signaling, and its promising results suggest there may be a way to arrive on time after all. Let's be clear: traffic is a complex problem to solve, and traffic control engineers have long worked on improving efficiency.

Artificial Intelligence has always been a hot topic. The problem of creating a machine that can think, make its own decisions and at the same time lacks human limitations, has always aroused controversies. We all remember what the infamous Skynet has done to our planet in Terminator series, right? We can also recall this nasty feeling of a cold shiver running down our spines when Neo has woken up from the Matrix. After watching such films, we can wonder why our scientists want to build intelligent machines in a first place. One would ask: why putting humanity at risk?