SANAA, YEMEN – Yemeni security officials say a suspected U.S. drone has killed three alleged al-Qaida fighters in an airstrike in the central Shabwa province. The officials said Monday that the overnight attack hit the men's vehicle as they were traveling near the town of Haban. The officials also say that in the onetime al-Qaida stronghold of Mukalla, on Yemen's southern coast, Emirati and other troops from the Saudi-led coalition who are primarily fighting Yemen's anti-government Shiite rebels conducted raids on homes seeking al-Qaida operatives. They say some 150 were detained. Activists close to al-Qaida say the men were being tortured in prisons run by Emirati forces.

Although it tends look to the sky, Israel Aerospace Industries (IAI) came back down to Earth to develop RoBattle, an unmanned ground vehicle (UGV) that may soon be tasked with the type of risky missions typically assigned to foot soldiers. IAI's UGV is built to be maneuverable, dynamic, and tough. Six wheels with independent suspension enable RoBattle to scale obstacles, such as rubble and small walls, to access areas that would typically be out of reach for other robots. A modular robotic kit allows the machine to be modified and adapted with remote vehicle control, navigation, and real time mapping abilities, depending on its operational needs. RoBattle can operate independently or as support unit for convoy protection, decoy, ambush, attack, intelligence, surveillance, or armed reconnaissance, according to IAI.

With the appearance of robotic financial advisors, self-driving cars and personal digital assistants come many unresolved problems. We have already experienced market crashes caused by intelligent trading software, accidents caused by self-driving cars and hate speech from chat-bots that turned racist. Today's narrowly focused artificial intelligence (AI) systems are good only at specific assigned tasks. Their failures are just a warning: Once humans develop general AI capable of accomplishing a much wider range of tasks, expressions of prejudice will be the least of our concerns. It is not easy to make a machine that can perceive, learn and synthesize information to accomplish a set of tasks.

With the appearance of robotic financial advisors, self-driving cars and personal digital assistants come many unresolved problems. We have already experienced market crashes caused by intelligent trading software, accidents caused by self-driving cars and hate speech from chat-bots that turned racist. Today's narrowly focused artificial intelligence (AI) systems are good only at specific assigned tasks. Their failures are just a warning: Once humans develop general AI capable of accomplishing a much wider range of tasks, expressions of prejudice will be the least of our concerns. It is not easy to make a machine that can perceive, learn and synthesize information to accomplish a set of tasks. But making that machine safe as well as capable is much harder.

China's'Doctor Frankenstein' has revealed he is building a team for the world's first full body transplant on a living human being and will operate'when we are ready'. In an interview with the New York Times, Dr Xiaoping Ren spoke about the details for his plan, which involves removing two heads from two bodies and connecting the donor body to the recipient's head. A metal plate would be inserted to stabilise the new neck, while the spinal cord nerve endings would be saturated in a gluelike substance to help regrowth. Earlier this year, Dr Ren shocked the world when it was revealed his team had carried out a successful head transplant on a monkey – and that it lived for 20 hours. Dr Xiaoping Ren has revealed he is building a team for the world's first head transplant on a live human being Although compared to Dr Frankenstein by China's own state media, Dr Ren, who assisted in the first hand transplant in the US in 1999, remains unapologetic in his ambition.

An ounce of prevention is worth a pound of cure, as the old saying goes, and that's just as true in cybersecurity as it is in health. So believes Cylance, a startup that uses AI to detect and prevent cyberattacks. On Wednesday, Cylance announced that it just raised a whopping 100 million in Series D funding. It will use the new infusion to expand its sales, marketing, and engineering programs. Dubbed CylanceProtect, the company's flagship product promises A.I.-based endpoint security while using a fraction of the system resources required by the approaches used in most enterprises today.

Matt Krisiloff is in a small, glass-walled conference room off the lobby of Y Combinator's office in San Francisco's South of Market neighborhood, shouting distance from some of the country's wealthiest startups, many of which Y Combinator has nurtured and helped fund. Krisiloff, who manages the operations of the tech incubator's program for very early-stage companies, is explaining why it is committed to investing an amount said to be in the tens of millions of dollars in a venture that is guaranteed never to make a penny. It's the simplest business model conceivable: hand thousands of dollars over to individuals in return for nothing, no strings attached. Krisiloff insists he and his Y Combinator colleagues can't wait to get started giving away the money. "This could be really transformative," he says. "It may help change how humans, society, and technology all operate together in the future."

In July, we talked about whether the change in law should be characterized as "Disruption, Eruption or Interruption?" This week, we drill down into one likely source of change, IBM's Watson. Lawyers have been thinking for a while about whether artificial intelligence would ever start to displace or complement lawyers. Richard Susskind, the leading legal futurist/technologist, did his work in this area starting in the mid-1980s. In the August issue of the ABA Journal, one of the commenters to an article about LegalZoom feared: "Once we have fully artificial intelligence enhanced programs like LegalZoom, there will be no need for lawyers, aside from the highly specialized and expensive large-law-firm variety."

The NHS could be applying machine learning-style processing to its patient, doctor and hospital data in an effort to improve efficiency within five years if plans by Google/DeepMind to push into the healthcare sector are approved. According to New Scientist, which has obtained a Memorandum of Understanding drawn up between DeepMind and the Royal Free NHS Trust in London, the two organisations are attempting to form a "broad ranging, mutually beneficial partnership, engaging in high levels of collaborative activity and maximising the potential to work on genuinely innovative and transformative projects." Among the areas the project aims to touch on are making improvements in clinical outcomes and patient safety, and reducing costs throughout the organisation. The memo also sets out a long list of "areas of mutual interest" where the two organisations could work together over the next five years, including bed and demand management software, financial control products, private messaging and task management for junior doctors, and even real-time health prediction. In fact, health prediction has formed the basis of the first project between the two partners, with Google/DeepMind creating an app called Streams that aims to study healthcare data to try to identify patients at risk of deterioration, readmission or even death.

People have a weird obsession with games likes Chess and Go. Achievement in them has long been seen as a marker of human intellect, and yet they're among the least human test you could devise; putting players in simplified situations where everything is known, every possible course of action is laid out for them, and the test is one of concentration and logic. We pass far greater tests daily, when we recognise a face in a crowd, when we dynamically balance in motion, when we predict the response our words and expressions will have on another sentient being, or when we do all of the above, effortlessly, at the same time. We don't think of these as challenging because they're so innately human, while playing Chess or Go seems far more impressive precisely because they're more rigid and computational in nature. There's an irony in making a board game one of the'grand challenges' of AI, and it surprises me that more people don't see it.