StarCraft players are safe – but not for long. The machines that made short work of chess, Scrabble and Go are beginning to set their sights on the venerable video game. And while the inherent complexity of most video games makes them a much harder target for AI than board games, two new projects aim to show they are far from invulnerable. One is a training ground for artificial intelligences targeting StarCraft, opened today by the game's creator, Blizzard Entertainment, in collaboration with Google's AI company DeepMind. The other is an AI being developed by researchers in Denmark whose approach stands the first good chance of beating a human at the game.

Tic tac toe, checkers, chess, go, poker. Artificial intelligence rolled over each of these games like a relentless tide. No one expects the robot to win anytime soon. But when it does, it will be a far greater achievement than DeepMind's conquest of Go--and not just because StarCraft is a professional e-sport watched by fans for millions of hours each month. DeepMind and Blizzard Entertainment, the company behind StarCraft, just released the tools to let AI researchers create bots capable of competing in a galactic war against humans.

We consider the problem of provably optimal exploration in reinforcement learning for finite horizon MDPs. We show that an optimistic modification to value iteration achieves a regret bound of order (HSAT)1/2 (up to a logarithmic factor) where H is the time horizon, S the number of states, A the number of actions and T the number of time-steps. This result improves over the best previous known bound HS(AT)1/2 achieved by the UCRL2 algorithm of [Jaksch, Ortner, Auer, 2010]. The key significance of our new results is that for large T, the sample complexity of our algorithm matches the optimal lower bound of Ω(HSAT)1/2. Our analysis contains two key insights.

Alphabet-owned Artificial Intelligence laboratory DeepMind is bankrolling NHS research, Business Insider has revealed. The London-based company has provided Moorfields Eye Hospital's trust with £110,000 in funding since July 2016-- when the two organisations kick-started a partnership to test DeepMind's new technology to diagnose eye diseases. The collaboration had already sparked controversy, as over one million patient data were processed by DeepMind's algorithm: this raised questions on patients' consent to data treatment and the opportunity of sharing clinical data with a private technology corporation. Business Insider, which obtained the information under an FOI request, says that DeepMind's payment went to cover "the costs incurred by the [Moorfields Eye Hospital's] Trust", rather than being a fee to access patient data. The hospital did not pay any money to DeepMind.

At DeepMind, we argue that despite rapid progress in both fields, researchers should not lose sight of this vision. We urge researchers in neuroscience and AI to find a common language, allowing a free flow of knowledge that will allow continued progress on both fronts. We believe that drawing inspiration from neuroscience in AI research is important for two reasons. First, neuroscience can help validate AI techniques that already exist. Put simply, if we discover one of our artificial algorithms mimics a function within the brain, it suggests our approach may be on the right track.

FILE - This Monday, Jan. 4, 2016, file photo, shows a pair of Under Armour SpeedForm Gemini 2 Record Equipped running shoes, containing an embedded chip to track exercise, on display, in New York. On Tuesday, Aug. 1, 2017, Under Armour announced it is cutting approximately 280 jobs from its global workforce and lowering its full-year revenue outlook, overshadowing a second-quarter performance that topped most expectations.

We have discussed several times about the impact of Artificial Intelligence (AI) on threat landscape, from a defensive perspective new instruments will allow the early detections of malicious patterns associated with threats, from the offensive point of view machine learning tools can be exploited to create custom malware that defeats current anti-virus software. At the recent DEF CON hacking conference, Hyrum Anderson, technical director of data science at security shop Endgame, demonstrated how to abuse a machine learning system to create malicious code that can avoid detections of security solutions. Anderson adapted the Elon Musk's OpenAI framework to create malware, the principle is quite simple because the system he created just makes a few changes to legitimate-looking code and convert them into malicious code. A few modifications can deceive AV engines, the system created by the experts was named OpenAI Gym. "All machine learning models have blind spots," he said.

You might think, based on the type of research they're doing, that the OpenAI office would be full of gadgets, full of wonder, full of weird experiments. There are no Faraday cages. Well, okay, there is a robot. And it's tucked away in a side room. It's surrounded by cobbled-together protective material so that it doesn't smash into itself if it starts flailing about due to a programming error.

Google-owned DeepMind is working on artificial intelligence (AI) that can imagine like humans and handle the unpredictable scenarios in real world. According to a report in Wired on Thursday, DeepMind, that was acquired by Google in 2014, is developing an AI capable of'imagination', enabling machines to see the consequences of their actions before they make them. "Its attempt to create algorithms that simulate the distinctly human ability to construct a plan could eventually help to produce software and hardware capable of solving complex tasks more efficiently," the report noted. DeepMind was successful in AI when it developed'AlphaGo' that recently beat a series of human champions at the tricky board game'Go'. But in case of'AlphaGo', there are a set of defined rules and predictable outcomes.

Computers are excellent problem solvers that can perform calculations at rates far in excess of the human brain. However, humans retain the upper hand in creativity and imagination. We can reason with ourselves, develop plans and think of abstract concepts that can't be defined. In a blog post this week, DeepMind said it has been able to develop an AI that can "imagine" and "reason about" the future. The company added it has seen "tremendous results" with the system by giving AI agents the ability to interpret their internal simulations. Handing the agent introspection abilities gives it the ability of questioning its own actions, in the same way humans do.