ACKTR can learn continuous control tasks, like moving a robotic arm to a target location, purely from low-resolution pixel inputs (left). ACKTR (pronounced "actor") -- Actor Critic using Kronecker-factored Trust Region -- was developed by researchers at the University of Toronto and New York University, and we at OpenAI have collaborated with them to release a Baselines implementation. The authors use ACKTR to learn control policies for simulated robots (with pixels as input, and continuous action spaces) and Atari agents (with pixels as input and discrete action spaces). ACKTR combines three distinct techniques: actor-critic methods, trust region optimization for more consistent improvement, and distributed Kronecker factorization to improve sample efficiency and scalability. For machine learning algorithms, two costs are important to consider: sample complexity and computational complexity.

I research intelligence to understand what we are, and to harness it wisely.

Tesla CEO Elon Musk fired off a new and ominous warning on Friday about artificial intelligence, suggesting the emerging technology poses an even greater risk to the world than a nuclear conflagration with North Korea. Musk--a fierce and long time critic of A.I. who once likened it to "summoning the demon" in a horror movie--said in a Twitter post that people should be concerned about the rise of the machines than they are. Reacting to the news that autonomous tech had bested competitive players in an electronic sports competition, Musk posted what appeared to be a photo of a poster bearing the chilling words "In the end, the machines will win." Musk, who is spearheading commercial space travel with his venture SpaceX, is also the founder of OpenAI, a nonprofit that promotes the "safe" development of AI. His stance puts him at odds with much of the tech industry, but echoes remarks of prominent voices like Stephen Hawking--who has also issued dire warnings about machine learning.

We're excited to announce a new research partnership with the Radiotherapy Department at University College London Hospitals NHS Foundation Trust, which provides world-leading cancer treatment. Head and neck cancer in general affects over 11,000 patients in the UK alone each year. Advances in treatment such as radiotherapy have improved survival rates, but because of the high number of delicate structures concentrated in this area of the body, clinicians have to plan treatment extremely carefully to ensure none of the vital nerves or organs are damaged. That makes a cancer at the back of the mouth or in the sinuses, for example, particularly hard to treat with radiotherapy. So with clinicians in UCLH's world-leading radiotherapy team we are exploring whether machine learning methods could reduce the amount of time it takes to plan radiotherapy treatment for such cancers.

DeepMind Alberta will turbo-charge the research ecosystem, mirroring the partnerships DeepMind has nurtured with the top academic institutions in the UK,

The bot by OpenAI demonstrated its skills at the annual live tournament "The International" this past weekend. It was up against a crowd favorite, the pro player "Dendi" who is one of the best in the world when it comes to Dota 2. He was defeated by the bot twice, before forfeiting any more future matches. After the game, Dendi stated that the bot "feels a little like [a] human, but a little like something else." - many of its moves looked familiar and human. He was surprised that it was possible for the AI machine to beat a human player - and therefore human intelligence. 'Bot is really fun and challenging to play against.

By Cade Metz SAN FRANCISCO: At OpenAI, the artificial intelligence lab founded by Tesla's chief executive, Elon Musk, machines are teaching themselves to behave like humans. But sometimes, this goes wrong. Sitting inside OpenAI's San Francisco offices on a recent afternoon, the researcher Dario Amodei showed off an autonomous system that taught itself to play Coast Runners, an old boat-racing video game. The winner is the boat with the most points that also crosses the finish line. The result was surprising: The boat was far too interested in the little green widgets that popped up on the screen.

DeepMind, a British artificial intelligence firm acquired by Google in 2014, is building an AI capable of "imagination" and understanding the consequences of previous actions. In two research papers submitted last week, DeepMind describes how the AI would be able to "construct a plan" and remember information that may be important in the future. "What differentiates these agents is that they learn a model of the world from noisy sensory data, rather than rely on privileged information such as a pre-specified, accurate simulator," said the DeepMind research team to Wired. "Imagination-based approaches are particularly helpful in situations where the agent is in a new situation and has little direct experience to rely on, or when its actions have irreversible consequences and thinking carefully is desirable over spontaneous action." Like most of DeepMind's research, it used video games to test the AI's proficiency.

Blizzard's partnership with DeepMind, a firm that specializes in machine learning, has culminated in the release of the StarCraft II API, which is available now. This mechanism for enabling outside creators into integrate their apps into StarCraft II is going to open up the competitive sci-fi strategy game to researchers working in the field of A.I. At the 2016 BlizzCon fan gathering in Anaheim, Blizzard revealed that it was working with DeepMind to test the same sort of learning algorithms that helped the company's AlphaGo A.I. beat some of the top players of the complicated board game, Go. "On behalf of Blizzard Entertainment, the StarCraft II development team is very pleased to announce the release of the StarCraft II API," reads a Blizzard blog post. "We recognize the efforts made by researchers over the years to advance AI using the original StarCraft. With the StarCraft II API, we're providing powerful tools for researchers, gamers, and hobbyists to utilize the game as a platform to further advance the state of AI research."

DeepMind, a British artificial intelligence firm acquired by Google in 2014, is building an AI capable of "imagination" and understanding the consequences of previous actions. In two research papers submitted last week, DeepMind describes how the AI would be able to "construct a plan" and remember information that may be important in the future. "What differentiates these agents is that they learn a model of the world from noisy sensory data, rather than rely on privileged information such as a pre-specified, accurate simulator," said the DeepMind research team to Wired. "Imagination-based approaches are particularly helpful in situations where the agent is in a new situation and has little direct experience to rely on, or when its actions have irreversible consequences and thinking carefully is desirable over spontaneous action." Like most of DeepMind's research, it used video games to test the AI's proficiency.