There are a lot of conspiracy theories about robots taking over our jobs or killing the humanity. In fact, famous physicist Professor Stephan Hawking agrees with researchers who claim AI robots will leave humanity ''Utterly Defenceless.'' Now, researchers at IOActive, a cyber security company has revealed that [Pdf] programs which "bring them (robots) to life" carry critical vulnerabilities which can be used by threat actors for negative purposes. The development of artificial intelligence (AI) robots is on the rise. Last year, IBM developed Ross – World's first AI lawyer and plans are to license it for being utilized in domains like bankruptcy, restructuring and creditors' rights team.

Quora Questions are part of a partnership between Newsweek and Quora, through which we'll be posting relevant and interesting answers from Quora contributors throughout the week. Who is leading in AI research among big players like IBM, Google, Facebook, Apple and Microsoft? First, my response contains some bias, because I work at Google Brain, and I really like it there. My opinions are my own, and I do not speak for the rest of my colleagues or Alphabet as a whole. I rank "leaders in AI research" among IBM, Google, Facebook, Apple, Baidu, Microsoft as follows: I would say Deepmind is probably #1 right now, in terms of AI research.

More than two years after a multi-sided civil war erupted inside Yemen that allowed Al Qaeda's local franchise to amass power and seize territory, President Trump has directed the Pentagon to embark on a complicated counter-terrorism campaign. Trump's decision, just six weeks into his presidency, intends to reverse the largely unchecked expansion across southern Yemen of the group, Al Qaeda in the Arabian Peninsula. The willingness to expand counter-terrorism operations inside war-torn Yemen was the latest signal that Trump is more willing to defer to military commanders on national security policy than President Obama, who was criticized publicly by three of his four Defense secretaries and privately by uniformed officers for micromanaging the military. Over two days this week, armed drones and warplanes conducted more than 30 airstrikes against suspected Al Qaeda positions in three Yemeni provinces, marking the first U.S. attacks in the country since an ill-fated Navy SEAL raid in January that killed two dozen civilians, including women and children, Al Qaeda militants and Chief Petty Officer William "Ryan" Owens. The aerial bombardment is expected to continue into the coming week.

A few years back, a prospective doctoral student sought out Sylvia Serfaty with some existential questions about the apparent uselessness of pure math. Serfaty, then newly decorated with the prestigious Henri Poincaré Prize, won him over simply by being honest and nice. "She was very warm and understanding and human," said Thomas Leblé, now an instructor at the Courant Institute of Mathematical Sciences at New York University. "She made me feel that even if at times it might seem futile, at least it would be friendly. The intellectual and human adventure would be worth it."

What if instead of searching through menus within programs like Microsoft Excel, our computers could understand the problem we're trying to solve and write the software to solve it? It's a hyper-futuristic idea, but one that has recently seen progress from Microsoft Research and the University of Cambridge. In a November 2016 paper, which gained notoriety after being accepted into one of the year's largest artificial intelligence conferences, Microsoft and Cambridge built an algorithm capable of writing code that would solve simple math problems. The algorithm, named DeepCoder, would be able to augment its own ability by also looking at potential combinations of code for how a problem could be solved. However, this doesn't mean it steals code, or copy and pastes it from existing software, or searches the internet for solutions, as some reports have claimed. "We're targeting the people who can't or don't want to code, but can specify what their problem is," says Marc Brockschmidt of Microsoft Research, a co-author of the paper, likening the work to Excel formulas that could take simple commands to solve for answers without being given the mathematical equation.

The nagging frustrations of ill-fitting shoes could soon be a thing of the past thanks to technology developed by Swedish company Volumental. New Balance has partnered with Volumental to install 3-D foot scanners in select stores worldwide that use foot measurements such as width, height and girth to determine a customer's ideal shoe model and shoe size. Although the technology behind Volumental's scanners may be complex, the process is simple: Customers step into the 3-D foot scanner, which transfers information from their feet to a tablet within seconds. The data is then matched with the proper shoes and size for a perfect fit. "Volumental's product has created a completely new way of interacting with our customers. It brings New Balance's unique fit story to life in a personal & relevant way for each of them. Customers love it and our staff love it," said New Balance international retail director Jonathan Clark.

The Government's new digital strategy has outlined key changes it wants to make in 2017, including a heavy focus on AI, data and to create new markets for the UK's creative industries. In a speech today (1 March), culture secretary Karen Bradley says the digital sector needs to be taken seriously as it is now worth 7% of the the economy and grew nearly three times faster than comparable sectors in 2015. "But that does not mean that we can stand still. And just keeping up should not be the limit of our ambitions. The UK must lead the world. Meanwhile, none of our citizens should be left behind," Bradley explains.

Dr. Stephen Parker, VP of professional graphics, took the stage to give an overview of the use of artificial intelligence in graphics applications. While the first working algorithm using deep feedforward perceptrons was published around 52 years ago in 1965 by Alexey Ivakhnenko and Valentin Lapa, deep learning in graphics applications has reached a combinatorial explosion thanks to some great work that has been recently accomplished by a group of researchers at the University of Toronto. In 2012, professor Geoffrey E Hinton and two students, Alex Krizhevsky and Ilya Sutskever, entered an image recognition content to build computer vision algorithms that learned to identify millions of objects in millions of pictures. Using the most efficient algorithms at the time, the team was able to take the error rate of an average human and cut it in half. They later created a company called DNNresearch, which Google bought the following year.

Here's a quick story you've probably heard before, followed by one you probably haven't. In 1979 a young Steve Jobs paid a visit to Xerox PARC, the legendary R&D lab in Palo Alto, California, and witnessed a demonstration of something now called the graphical user interface. An engineer from PARC used a prototype mouse to navigate a computer screen studded with icons, drop-down menus, and "windows" that overlapped each other like sheets of paper on a desktop. It was unlike anything Jobs had seen before, and he was beside himself. "Within 10 minutes," he would later say, "it was so obvious that every computer would work this way someday." As legend has it, Jobs raced back to Apple and commanded a team to set about replicating and improving on what he had just seen at PARC. And with that, personal computing sprinted off in the direction it has been traveling for the past 40 years, from the first Macintosh all the way up to the iPhone.

It's been a rocky week, at home and abroad. Bomb threats were made against Jewish community centers and schools. More controversy over Russia's role in the 2016 elections engulfed Congress and the White House. Russia and China vetoed new sanctions on Syria. Deadly tornadoes ripped across the Midwest.