Now I suppose it is possible that once an agent reaches a sufficient level of intellectual ability it derives some universal morality from the ether and there really is nothing to worry about, but I hope you agree that this is, at the very least, not a conservative assumption. For the purposes of this article I will take the orthogonality thesis as a given. So a smarter than human artificial intelligence can have any goal.

Everyone is talking about driverless cars ... After reading this book, you will be knowledgeable enough to make your own informed opinion. Driverless vehicles are poised to usher in a massive disruption of our transportation system, our urban landscapes, our economy -- and quite possibly the very fabric of society. Anyone who wants to understand what's coming must read this fascinating book. Driverless is a great read for anybody interested in technological, societal, and ethical implications of self-driving cars. The book reaches across fields and issues thoughtfully, and presents a comprehensive view of the state of the art.

In 2014, Tesla and SpaceX founder Elon Musk said in an interview that he believed that AI posed the biggest threat to human existence. That didn't stop him from co-chairing a billion-dollar AI research nonprofit, but it did make people think about whether artificial intelligence could get out of hand. Now, five tech giants including Google and its DeepMind subsidiary, Facebook, Microsoft, Amazon and IBM have come together to form Partnership on AI, a coalition dedicated to highlighting the best practices and ethical research in the field of artificial intelligence. Momentum by TNW is our New York technology event for anyone interested in helping their company grow. The group notes that it "foresees great societal benefits and opportunities ahead, but we also understand that as with every new technology there will be concerns and confusion associated with new applications and competencies, and we look forward to working together on these important issues. We intend to come together to address these important issues, including ethics, safety, transparency, privacy, biases, and fairness."

Virtual reality is on the cusp of becoming mainstream, but one startup in Japan is betting the technology won't really succeed unless it cracks a critical piece of the puzzle: human eyeballs. Fove Inc. is introducing the world's first commercially available VR goggles equipped with tiny infrared cameras to follow eye movements. By tracking human irises, the gadget aims to reduce motion sickness, improve graphics performance and enhance social experiences by making virtual eye-contact possible, says Yuka Kojima, Fove's founder and chief executive officer. "We want to be the company that figures out VR's unsolved problems," Kojima said. "The immediate goal for now is to get as many headsets into the hands of developers as possible."

As it wraps up its annual user conference here this week, San Francisco-based Splunk has one main message for the market. It's going big -- or, given that this is football season -- long with machine learning. In other words, it has expanded in a significant way the early version of machine learning in its platform to deliver new services and capabilities. It has added machine learning to the core of its platform with a machine learning toolkit that can be installed as a free app on top of the Splunk Enterprise platform, Manish Sainani, principal product manager of Machine Learning at Splunk told CMSWire. This toolkit provides 300 algorithms for machine learning, 27 of which are pre-packaged out of the box, spanning all of the major categories, he said.

Five tech giants announced on Wednesday that they are launching a nonprofit to "advance public understanding" of artificial intelligence and to formulate "best practices on the challenges and opportunities within the field." The Partnership on Artificial Intelligence to Benefit People and Society is being formed byAmazon, Facebook, Google, IBM, and Microsoft, each of which will have a representative on the group's 10-member board. The partnership will conduct research and recommend best practices relating to "ethics, fairness and inclusivity; transparency, privacy, and interoperability; collaboration between people and AI systems; and the trustworthiness, reliability and robustness of the technology," according to the announcement. "It does not intend to lobby government or other policymaking bodies." "We're in a golden age of machine learning and AI," said Ralf Herbrich, the director of machine learning at Amazon, in a prepared statement.

Facebook (FB, Tech30), Amazon (AMZN, Tech30), Google (GOOGL, Tech30), Microsoft (MSFT, Tech30) and IBM (IBM, Tech30) have formed a new nonprofit to establish best practices for the development of AI technology in partnership with academics and ethics experts. The group, unveiled on Wednesday, goes by the heartwarming name Partnership on Artificial Intelligence to Benefit People and Society. "This partnership will ensure we're including the best and the brightest in this space in the conversation to improve customer trust and benefit society," Ralf Herbrich, director of machine learning science and core machine learning at Amazon, said in a statement. Each of the corporate members is expected to make financial and research contributions to the group. The nonprofit is also looking to engage with the scientific community and bring academics onto its board.

Many of the biggest tech companies are joining forces to ease fears around artificial intelligence. Facebook (FB, Tech30), Amazon (AMZN, Tech30), Google (GOOGL, Tech30), Microsoft (MSFT, Tech30) and IBM (IBM, Tech30) have formed a new nonprofit to establish best practices for the development of AI technology in partnership with academics and ethics experts. The group, unveiled on Wednesday, goes by the heartwarming name Partnership on Artificial Intelligence to Benefit People and Society. "This partnership will ensure we're including the best and the brightest in this space in the conversation to improve customer trust and benefit society," Ralf Herbrich, director of machine learning science and core machine learning at Amazon, said in a statement. Each of the corporate members is expected to make financial and research contributions to the group.

Summary: At the core of modern AI, particularly robotics, and sequential tasks is Reinforcement Learning. Although RL has been around for many years it has become the third leg of the Machine Learning stool and increasingly important for Data Scientist to know when and how to implement. If you poled a group of data scientist just a few years back about how many machine learning problem types there are you would almost certainly have gotten a binary response: problem types were clearly divided into supervised and unsupervised. While Reinforcement Learning (RL) has been around since at least the 80's and before that in the behavioral sciences, its introduction as a major player in machine learning reflects it rising importance in AI. What problems fit this description?

Machine Learning, driven by the rise of big data and evolving technologies, is emerging as a powerful quantitative investment tool, with financial advisers increasingly recognising the benefits it can bring to investors, according to Man AHL. A recent survey of financial advisers, who attended a series of adviser events held by Man AHL across Australia earlier this month, found that nearly three quarters of advisers (74%) believe Machine Learning, a branch of artificial intelligence, has the potential to change the way we invest in the future. Speaking at the adviser events, Man AHL's Oxford-based Chief Scientist Dr. Anthony Ledford said that Machine Learning has become increasingly important to the alternative investment management industry as it deals with larger and more complex data-sets. "The rise of Machine Learning in quantitative investing is powered by three separate revolutions: the growth in computing power, the explosion of data generation and the maturing of methodologies from statistics, computer science, mathematics and engineering, amongst other disciplines." "As more data become available, sophisticated Machine Learning models enable new patterns to be detected that humans can't easily spot. The technology is a significant area of research focus for Man AHL and we believe our enhanced focus on Machine Learning will be strongly supportive of the evolution of our quantitative investment strategies," Dr. Ledford said.