GENEVA – A new device has allowed two monkeys to regain use of their paralyzed legs by transmitting brain signals wirelessly, bypassing their spinal cord lesions, a study released Wednesday by the journal Nature said. The implantable device, called a neuroprosthetic interface, was developed by an international team led by researchers at the Federal Polytechnic School of Lausanne (EPFL) and may soon be tested as a remedy for paralysis in humans. "For the first time, I can imagine a completely paralyzed patient able to move their legs through this brain-spine interface," Jocelyne Bloch, a neurosurgeon at the Lausanne University Hospital, said in a press release from EPFL. The interface conceived at EPFL is a multicomponent brain-spine connector, which decodes signals from the part of the motor cortex responsible for leg movements. It then relays those signals in real time to the lumbar region of the spinal cord that activates leg muscles to walk.

It's fun to buy a drone from a store, but perhaps more satisfying to build one from scratch. Intel in December will start shipping a fully loaded drone kit to let you do just that, with all the parts including the rotors, software, 3D camera and flight controller. Intel's Aero Ready to Fly Drone kit will go on sale on the company's website. An Intel spokeperson couldn't immediately provide a price. But it won't be cheap -- likely more than $600.

BenevolentAI is a London start-up that specializes in artificial intelligence (AI); its BenevolentBio division, formerly Stratified Medical, applies AI to human health and biotech. Its baby is a technology that could speed up late-stage development of drugs and provide richer clinical data. Now, it will test it using clinical stage drug candidates licensed from Janssen. Although there are no details on the particulars of the agreement, BenevolentAI is confident that it can accelerate clinical development and begin Phase IIb trials in mid-2017. If everything works out well, the company will have exclusive rights to develop, manufacture and commercialize these candidates.

I first got speaking to Jason via Twitter and then we met at a few networking events. We quickly realised we shared an overtly cynical attitude to the vacuous tripe that emerges from Silicon Valley's startup culture, and want to resist the adoption of that culture in the Northern Ireland tech scene. When it comes to big data and machine learning, I know no one more qualified than Jason. He wrote a book about machine learning which has helped me immensely in coming to grips with the topic, even though I can't even begin to understand the mathematics behind it all. Like myself, Jason is not native to Northern Ireland, but he's been here so long he might as well be part of the furniture.

Artificial Intelligence (AI) is making progress in great strides, or at least it appears so! Almost no week passes by without some major announcements of new challenges solved by AI technology or new products powered by AI. Indeed many quantifiable factors attest an unprecedented level of activity: capital investments, number of academic papers, number of products involving AI technology, they all are on a steep rise in the past five years. Computers are already very capable at some specialized tasks that require reasoning and other abilities that we typically associate with intelligence. For example, computers can play a decent game of chess or can help us order our holiday photos. Despite this genuine progress, we are still a long way from human level intelligence because our best artificial intelligence systems are not general purpose. They cannot quickly adapt to novel tasks the way most humans can do.

In the previous blog post Using Keras and Deep Q-Network to Play FlappyBird we demonstrate using Deep Q-Network to play FlappyBird. However, a big limitation of Deep Q-Network is that the outputs/actions are discrete while the action like steering are continuous in car racing. An obvious approach to adapt DQN to continuous domains is to simply discretize the action space. However, we encounter the "curse of dimensionality" problem. For example, if you discretize the steering wheel from -90 to 90 degrees in 5 degrees each and acceleration from 0km to 300km in 5km each, your output combinations will be 36 steering states times 60 velocity states which equals to 2160 possible combinations. The situation will be worse when you want to build robots to perform something very specialized, such as brain surgery that requires fine control of actions and naive discretization will not able to achieve the required precision to do the operations.

Many predict artificial intelligence (AI) will someday cure cancer, clean up our environment, drastically improve our cities, and send us to Mars, among a host of other accomplishments. However, with the potential benefits that inspire oohs and aahs also comes risk. Before there was Siri, there was HAL. And in the epic science fiction movie "2001: A Space Odyssey," when the poor astronaut Dave Bowman asks the supercomputer HAL 9000 to let him back inside the spacecraft, HAL merely responds, "I'm sorry Dave, I'm afraid I can't do that." Granted, this was a movie--albeit a brilliant one--but there are still real life concerns about what exactly are artificial intelligence best practices and a need for guidelines.

Unless you've recently graduated from one of the new Data Science courses that have been popping up online and in various universities around the world, then becoming a Data Scientist was most likely slightly accidental and was more about the journey than the destination. I started out as a physicist and had a strong mathematical grounding, but I had a passion for medicine. After completing my bachelor's degree I took a master's degree in medical physics. This is where I gained an appreciation for the importance of image analysis and the role that data plays in medicine. I created a virtual model of a human torso by segmenting images from the Visible Human Project.

As one of the top tech universities in the world, there's no doubt that the Massachusetts Institute of Technology houses some pretty darn intelligent people -- and now it seems that its buildings are getting a whole lot smarter, too. That's thanks to MIT researchers who have developed a computational model that analyzes ambient vibrations from surrounding environmental factors -- such as passing trucks -- and uses these insights to monitor for building damage or mechanical stress. So far, the research has been tested on MIT's 21-story Green Building, a concrete tower designed by noted architect I.M. Pei in the 1960s that happens to be the tallest building in Cambridge, Massachusetts. In 2010, the building was equipped with 36 accelerometers to monitor vibrations on different floors. These sensors essentially act as a central nervous system for the building.

COULD hacking our reflexes allow paralysed people to walk again? Some animals have walking reflexes governed by nerves in their spine – it's why a chicken continues to run after its head has been cut off. Now these reflexes have let paralysed monkeys regain use of their legs after a week or two of practice. Previous methods have taken months. We have no reliable means to reconnect severed nerves in people with injured spinal cords. One way to overcome paralysis might be to detect a person's desire to move and use this to stimulate nerves or muscles.