Along with taking part in the social experiment, Gemma will front the factual programme and delve into the advances that have been made into artificial intelligence. She will look at technology - such as driverless cars - and speak to British A.I. researcher Demis Hassabis and his DeepMind project, which is working toward creating machines that can learn even more by themsleves than ever before. "This film pushes the boundaries of what is possible using the technology that is increasingly influential in our lives," said Tom Porter, Channel 4's acting Commissioning Editor, Science.

It can teach itself, The Next Web reported (17 Oct 2016): "In a significant step forward for artificial intelligence, Alphabet's hybrid system -- called a Differential Neural Computer (DNC) -- uses the existing data storage capacity of conventional computers while pairing it with smart AI and a neural net capable of quickly parsing it." The AI also knows how to optimise its memory to accelerate future searching-learning. The Next Web added: "Instead of having to learn every possible outcome to find a solution, DeepMind can derive an answer from prior experience, unearthing the answer from its internal memory rather than from outside conditioning and programming." In other AI news the British Socialist newspaper the Morning Star commented on the #Singularity and AI, regarding concern about powerful multinationals shaping AI (17 Oct 2016): "Technologies shaping our world and determining the sustainability of human civilisation are commissioned by wealthy corporations. So uploaded human intelligence, machine learning and systems designed without human agency -- and perhaps without human values -- are ideas we all need to understand and influence."

The Google logo is displayed on a sign outside of the Google headquarters in Mountain View, California. Google's artificial intelligence (AI) platform DeepMind revolutionizes the field, being now capable of learning based on information already possessed. DeepMind is able of learning, or better said of teaching itself, based on data it already possesses. According to The Next Web, this is a significant step forward for artificial intelligence, a real breakthrough that revolutionizes the field. DeepMind technology is based on Alphabet's hybrid system called Differential Neural Computer (DNC).

Google's DeepMind algorithm just got one step closer to behaving like a human. Human smart DeepMind has gotten scarily smart in recent months – and we're not just talking "computer smart," but more like "human smart."

OpenAI wants to build the technology that will finally create a computer that can converse in a way that is indistinguishable humans. The nonprofit, backed by Tesla CEO Elon Musk and his PayPal co-founder Peter Thiel, brought on NVIDIA's supercomputer DGX-1, which has 170 teraflops of computing power, to help hone machine learning systems to create algorithms that can comprehend language and teach robots to respond appropriately. That should solve one of the biggest hindrances to making AI systems that can learn complex interactions: the slowness of current computers. "The speed of our computers is in some sense the lifeblood of deep learning," OpenAI research director Ilya Sutskever in an NVIDIA video. The goal of this project is to allow a robot to become smart enough to not only recognize speech, but to also use the data it gathers to formulate appropriate responses on its own--and to do that, computers need to digest data more quickly than they are currently capable of. The DGX-1, which is optimized for an arm of machine learning called deep learning, can feed copious amounts of natural language data into OpenAI's network much quicker than ever before.

And – why we aren't ready for Superintelligence, DeepMind created an AI with memory, Facebook's ideas for VR and more! Last weekend we saw Cybathlon, the world's first "bionic Olympics", where disabled athletes assisted with exoskeletons, prosthetic robotic hands or brain-computer interfaces competed in a series of challenges. This article from BBC describes the games and lists all the winners. Some amputees want to have a prosthetic limb that can do a bit more or just looks better.Waterproof, dustproof, customized to client's skin color, matching to the owner's tattoos. And there are companies that are ready to help them for an appropriate price.

DeepMind, an artificial intelligence firm that was acquired by Google in 2014 and is now under the Alphabet umbrella, has developed a computer than can refer to its own memory to learn facts and use that knowledge to answer questions. That's huge, because it means that future AI could respond to queries from humans without being taught every possible correct answer. DeepMind says its new AI model, called a differentiable neural computer (DNC), can be fed with things like a family tree and a map of the London Underground network, and can answer complex questions about the relationships between items in those data structures. For example, you could get responses to questions like, "Starting at Bond street, and taking the Central line in a direction one stop, the Circle line in a direction for four stops, and the Jubilee line in a direction for two stops, at what stop do you wind up?" DeepMind says its DNC could also help you plan an efficient route from Moorgate to Piccadilly Circus. Similarly, it could understand and answer questions about the relationships between people from a large family, like, ""Who is Freya's maternal great uncle?" This discovery builds on the concept of neural networks, which mimic the way the human mind works.

An artificial intelligence algorithm has been developed by Google's DeepMind that is capable of working out the most efficient way of getting from one point to another on London's Tube network. The system, known as a differentiable neural computer (DNC), is able to combine basic reasoning with memory in a unique way to solve such problems. "Like a conventional computer, it can use its memory to represent and manipulate complex data structures, but, like a neural network, it can learn to do so from the data," states a paper that details the DNC in the journal Nature. "We show that it can learn tasks, such as finding the shortest path between specified points and inferring the missing links in randomly generated graphs, and then generalize these tasks to specific graphs, such as transport networks and family trees." Google's DeepMind gained international media attention earlier this year after it developed the first machine capable of beating a human world champion at the board game Go.

DeepMind, an AI research lab acquired by Google for 400 million in 2014, has provided an update on how its DeepMind Health unit is doing. The London-based company told Business Insider on Tuesday that it has doubled the size of its team from 20 to 40 since launching in February this year, hiring several big names in the AI world along the way. New hires include security and privacy expert Ben Laurie, who is the founding director of the Apache Software Foundation, a director at the Open Rights Group, and a veteran Google software engineer, and former CIO Tony Corkett, who helped the NHS to digitise X-rays. Former Google Maps team leader Andrew Eland has been brought in to head up DeepMind Health's engineering efforts, while Will Cavendish, a former civil servant that worked on NHS online booking and prescription services, has joined as strategy lead. Elsewhere, ex-GE Healthcare executive Cathy Harris has been appointed as DeepMind Health's product lead.