Tesla defended its Autopilot feature, saying that while it doesn't prevent all accidents, it makes them less likely to occur than vehicles without it. The Tesla vehicle involved in a fatal crash last month in Northern California was operating on Autopilot, the automaker has confirmed. But Tesla contends that the victim and a damaged freeway barrier share in the blame. The Model X SUV crashed in Mountain View, in California's Silicon Valley, on March 23, killing its driver, Apple engineer Walter Huang, 38. The electric car maker said in a company blog post that the driver did not have his hands on the steering wheel for six seconds before the crash, despite several warnings from the vehicle.

Today artificial neural networks are making art, writing speeches, identifying faces and even driving cars. It feels as if we're riding the wave of a novel technological era, but the current rise in neural networks is actually a renaissance of sorts. It may be hard to believe, but artificial intelligence researchers were already beginning to see the promise in neural networks during World War II in their mathematical models. But by the 1970s, the field was ready to give up on them entirely. "[T]here were no impressive results until computers grew up, that is until the past 10 years," Patrick Henry Winston, a professor at MIT who specializes in artificial intelligence, says. "It remains the most important enabler of deep learning."

Palestinian health officials said 15 Palestinians were killed by Israeli fire and more than 750 hit by live rounds Friday, making it the bloodiest day in Gaza since the 2014 cross-border war between Israel and Hamas. In Friday's confrontations, large crowds gathered near the fence, with smaller groups of protesters rushing forward, throwing stones and burning tires. Israeli troops responded with live fire and rubber-coated steel pellets, while drones dropped tear gas from above. Gen. Ronen Manelis, said that while thousands of Palestinians approached the border Friday, those engaged in stone-throwing were in the hundreds. General Manelis denied soldiers used excessive force, saying those killed by Israeli troops were men between the ages of 18 and 30 who were involved in violence and belonged to militant factions.

In a proactive move to "eliminate a future conflict," Elon Musk recently stepped down as chairman of OpenAI, a nonprofit research company he cofounded two years ago aimed at building safe artificial intelligence (AI) with wide benefits for all. In 2014, Musk suggested AI could be "more dangerous than nuclear weapons," a statement he reiterated at a recent SXSW event in Austin, TX. Bill Gates also went on record several years ago about his concerns regarding machine superintelligence. "It is important to research how to reap [AI] benefits while avoiding potential pitfalls." The open letter was accompanied by a research priorities proposal, highlighting work that can be done to make AI "robust and beneficial." Perhaps the most pressing question today is whether we can use current technologies -- such as historical and preventative tracking -- to build AI safeguards that not only figure out why an AI algorithm made a poor decision but also preclude other AI algorithms from making the same poor decision?

The software connects a robot's arms and grippers as well as its onboard cameras and sensors to off-the-shelf virtual reality hardware via the internet. Using handheld controllers, users can control the position of the robot's arms to perform intricate manipulation tasks just by moving their own arms. Users can step into the robot's metal skin and get a first-person view of the environment, or can walk around the robot to survey the scene in the third person -- whichever is easier for accomplishing the task at hand. The data transferred between the robot and the virtual reality unit is compact enough to be sent over the internet with minimal lag, making it possible for users to guide robots from great distances. "We think this could be useful in any situation where we need some deft manipulation to be done, but where people shouldn't be," said David Whitney, a graduate student at Brown who co-led the development of the system.

Tesla Inc. TSLA 3.24% late Friday acknowledged its semiautonomous Autopilot system was engaged by the driver in the seconds before a fatal crash last week, raising more questions about the safety of self-driving technology on public roads. Federal investigators this week began examining the March 23 crash of a Model X sport-utility vehicle that was traveling south on Highway 101, near Mountain View, Calif., before it struck a barrier, then was hit by two other vehicles and caught fire. The driver of the Model X was killed. Tesla said its vehicle logs show the driver's hands weren't detected on the wheel for six seconds before the collision, and he took no action despite having five seconds and about 500 feet of unobstructed view of a concrete highway divider. On Tuesday, the National Transportation Safety Board dispatched investigators to the scene, the second Tesla crash to attract the agency's attention this year.

Artificial intelligence (AI) could help increase the UAE's gross domestic product by 35 percent by 2031, according to a new report. The Ministry of Economy said that the economic impact of the country's investment in the technologies of the Fourth Generation of the Industrial Revolution, most notably AI, will not be restricted by cost, consumption, production and productivity, adding that the UAE aims to become the global centre of AI by 2030. The ministry added in a report cited by news agency WAM that AI will reduce the government's annual spending by 50 percent, through reducing the number of paper-based transactions. The report also predicts that the UAE's AI strategy will generate an annual economic return, in many sectors, of around AED22 billion. It said this will be achieved by raising individual productivity by 13 percent, saving 396 million hours annually from commuting, reducing transportation costs by 44 percent, limiting carbon emissions and environmental pollution by 12 percent, limiting traffic accidents and their resulting losses by 12 percent, reducing the need for parking spaces by 20 percent by 2030.

Although Mr Macron promotes the use of digital algorithms to make public and private services more efficient, he said in an interview with Wired magazine, that the technology should be open to public scrutiny to ensure public trust. He said: "My role is not to block this change, but to be able to train or retrain people for them to get opportunities in this new world." While AI could revolutionise major industries in the fields of medicine, energy, transport, defence and finance, Mr Macron warned that unless the technology can be trusted, "people will eventually reject this innovation". He guaranteed that all the AI algorithms created by his government will be transparent to reduce the threat to democracy which AI poses.

Visual Domain Adaptation is a problem of immense importance in computer vision. Previous approaches showcase the inability of even deep neural networks to learn informative representations across domain shift. This problem is more severe for tasks where acquiring hand labeled data is extremely hard and tedious. In this work, we focus on adapting the representations learned by segmentation networks across synthetic and real domains. Contrary to previous approaches that use a simple adversarial objective or superpixel information to aid the process, we propose an approach based on Generative Adversarial Networks (GANs) that brings the embeddings closer in the learned feature space. To showcase the generality and scalability of our approach, we show that we can achieve state of the art results on two challenging scenarios of synthetic to real domain adaptation. Additional exploratory experiments show that our approach: (1) generalizes to unseen domains and (2) results in improved alignment of source and target distributions.

From eastern Europe to southern Iraq, the U.S. military faces a difficult problem: Adversaries pretending to be something they're not -- think Russia's "little green men" in Ukraine. But a new program from the Defense Advanced Research Projects Agency seeks to apply artificial intelligence to detect and understand how adversaries are using sneaky tactics to create chaos, undermine governments, spread foreign influence and sow discord. This activity, hostile action that falls short of -- but often precedes -- violence, is sometimes referred to as gray zone warfare, the'zone' being a sort of liminal state in between peace and war. The actors that work in it are difficult to identify and their aims hard to predict, by design. "We're looking at the problem from two perspectives: Trying to determine what the adversary is trying to do, his intent; and once we understand that or have a better understanding of it, then identify how he's going to carry out his plans -- what the timing will be, and what actors will be used," said DARPA program manager Fotis Barlos.