Last week scientists at the Children's National Medical Center in Washington, DC, announced a pretty important breakthrough – they've developed a robot that can operate by itself on soft tissue. The robot is called the Smart Tissue Autonomous Robot. Not just because it's another step towards even more precise and safe surgery, which is good for everyone, but because the robot can do this with a level of independence not previously seen. In 1985, doctors used the Puma 560 to assist them in delicate operations, and that's how robotic surgery has developed – as a way of assisting human doctors. It's not hard to see why: a robot may be able to make more precise movements than a person, and it won't get tired or feel the strain of a long operation in the way a surgeon might.

With all this talk about chatbots from Facebook and Microsoft, teaching artificial intelligence to be smarter has become a central topic of the tech world. But what about what AI can teach us? Ashok Goel, a computer science professor at Georgia Tech, put that question to the test when he added "Jill Watson" – a chatbot powered by IBM's Watson technology – to his list of of teaching assistants for an online course. The chatbot was so good at answering questions that students did not notice their TA was made of silicon until after they'd turned in their finals. Some of the biggest names in tech are coming to TNW Conference in Amsterdam this May.

If you want to tackle competition and be a leader in your own right you need inevitably to gain competitive advantages. Otherwise, you are bound to be just one more in the bunch of those left behind. So the question is: how to become a leader and, if possible, an awesome leader? By this, I mean the kind of front-runner that sees what the others don't; the kind of strategist that anticipates his competitor's actions; the resilient believer that doesn't hesitate and goes staunchly the extra mile before the others. Altogether, the driving force that irradiates a huge resolve that convinces the others around that there is an upcoming light at the end of the tunnel.

How to Build a Mind Artificial Intelligence Reloaded A foray into the present, future and ideas of Artificial Intelligence. Are we going to build (beyond) human-level artificial intelligence one day? Nobody knows, because the specs are not fully done yet. But let me give you some of those we already know, just to get you started. While large factions within the philosophy of mind still seem to struggle over the relationship between mind, world, meaning, intentionality, subjectivity, phenomenal experience, personhood and autonomy, Artificial Intelligence (AI) offers a clear and concise set of answers to these basic questions, as well as avenues of pursuing their eventual understanding.

Collaboration With STFC Hartree Centre Taps into IBM Watson to Improve Patient Experience. Alder Hey Children's NHS Foundation Trust today announced a ground-breaking multi-year collaborative programme with the Science and Technology Facilities Council's (STFC) Hartree Centre, supported by IBM (NYSE: IBM), to create the United Kingdom's first'cognitive' hospital by harnessing'big data' and the power of IBM's Watson technology platform. This is the first time that Watson technology will be applied to improve patient experience in the United Kingdom. Alder Hey and the Hartree Centre believe that by applying Watson -- an innovation in computing technology -- it will enhance patient care and potentially generate savings for both the hospital and the NHS (National Health Service) as a whole. Using Watson to analyse any feedback that is voluntarily and securely provided by the patients, with appropriate consent as needed, it is anticipated that Alder Hey will be able to greatly enhance patient experience by; identifying patient anxieties and providing information and reassurance on-demand; reminding young patients and their parents about appointments and about aftercare; and providing insightful feedback to clinicians based on the tone and sentiment of these interactions.

Conversations about basic income, a government-funded salary given to every citizen, used to take place in the dingy offices of extremist left-wing politicians, or in the campus dorm rooms of idealistic students determined to fix the problems of the previous generation. The conversation was about social responsibility. It wasn't an economic case, it was a moral one. A sharp uptake in technology designed to automate jobs and replace human workers is bringing new voices to this old debate. Today's society could be disastrously affected by artificial intelligence and growing automation, and scientists and technologists are looking for ways to stop that damage before it happens.

The pathway in the brain responsible for vision operates in several layers, each of which is thought to extract progressively more information from an image, such as movement, shape, color, and so on. Each layer consists of huge numbers of neurons connected into a vast network. Deep convolution neural networks have a similar structure. They too are made up of layers, and each of these is a network of circuits designed to mimic the behavior of neurons, hence the term neural network. Through much trial and error, computer scientists have found that these layers perform best when each extracts progressively more information about an image. And when they look at the behavior of layers individually, they find remarkable similarities to the function of specific layers in the brain.

Computers are becoming rather versatile copycats, thanks to deep-learning algorithms. Just last year, researchers "trained" machines to transfer the brushstrokes of iconic artists onto any still image. Now, Manuel Ruder and a team of computer scientists from the University of Freiburg in Germany have taken the technology a step further: They're altering videos. The team's style transfer algorithm makes clips from Ice Age or the television show Miss Marple appear as living paintings crafted by the likes of Van Gogh, Picasso or any other artist. And the results speak for themselves.

Are deep neural networks creative? It seems like a reasonable question. Google's "Inceptionism" technique transforms images, iteratively modifying them to enhance the activation of specific neurons in a deep net. The images appear trippy, transforming rocks into buildings or leaves into insects. Another neural generative model, introduced by Leon Gatys of the University of Tubingen in Germany, can extract the style from one image (say a painting by Van Gogh), and apply it to the content of another image (say a photograph). Generative adversarial networks (GANs), introduced by Ian Goodfellow, are capable of synthesizing novel images by modeling the distribution of seen images.

Deep neural networks have progressed immensely in recent years. Far from being moonshots, they are now at a point where they are better than humans at several tasks. They are capable of understanding text without previously encountering the words, of translating different languages, they can even cut transcription errors by half. And now, it seems they can recognize and replicate art (and a number of art styles). A team from the University of Freiburg in Germany have used deep neural networks to copy the artistic style of famous painters and paste them into video clips from movies and TV shows.