Alphabet's Google unit, Ford, the ride-sharing service Uber, and two other companies said on Tuesday they are forming a coalition to push for federal action to help speed self-driving cars to market. Sweden-based Volvo Cars, which is owned by China's Zhejiang Geely Holding Group Co, and Uber rival Lyft also are part of the Self-Driving Coalition for Safer Streets. The group said in a statement it will "work with lawmakers, regulators and the public to realize the safety and societal benefits of self-driving vehicles." The coalition said David Strickland, the former top official of the U.S. National Highway Traffic Safety Administration (NHTSA), the top U.S. auto safety agency that is writing new guidance on self-driving cars, will be the coalition's counsel and spokesman. "The best path for this innovation is to have one clear set of federal standards and the coalition will work with policymakers to find the right solutions that will facilitate the deployment of self-driving vehicles," Strickland said in the statement.

Mike Stute recently wrote in Datanami, "Fraud detection. These use cases–and so many more–all owe a debt to machine learning. By automatically discovering patterns that lead to insights and creating predictive models that drive actions, the technology has proven its value many times, and to many industries. More recently, machine learning has begun to make a name for itself in the field of cybersecurity. As part of a larger cybersecurity solution, machine learning can help human security analysts when it comes to detecting real threats more quickly, so that an enterprise can act on them more swiftly. The technology can plumb the depths of historical security data to learn what attacks look like based on hidden variables and their relationships to each other, all in preparation for'seeing' the next attack when it hits."

Alphabet Inc.'s Google unit, Ford Motor Co., the ride-sharing service Uber and two other companies said on Tuesday they are forming a coalition to push for federal action to help speed self-driving cars to market. Sweden-based Volvo Cars, which is owned by China's Zhejiang Geely Holding Group Co., and Uber rival Lyft also are part of the Self-Driving Coalition for Safer Streets. The group said in a statement it will "work with lawmakers, regulators and the public to realize the safety and societal benefits of self-driving vehicles." The coalition said David Strickland, the former top official of the U.S. National Highway Traffic Safety Administration (NHTSA), the top U.S. auto safety agency that is writing new guidance on self-driving cars, will be the coalition's counsel and spokesman. "The best path for this innovation is to have one clear set of federal standards and the coalition will work with policymakers to find the right solutions that will facilitate the deployment of self-driving vehicles," Strickland said in the statement.

WASHINGTON (Reuters) - Alphabet Inc's Google unit GOOGL.O, Ford Motor Co F.N, the ride-sharing service Uber [UBER.UL] and two other companies said on Tuesday they are forming a coalition to push for federal action to help speed self-driving cars to market. Sweden-based Volvo Cars, which is owned by China's Zhejiang Geely Holding Group Co GEELY.UL, and Uber rival Lyft also are part of the Self-Driving Coalition for Safer Streets. The group said in a statement it will "work with lawmakers, regulators and the public to realize the safety and societal benefits of self-driving vehicles." The coalition said David Strickland, the former top official of the U.S. National Highway Traffic Safety Administration (NHTSA), the top U.S. auto safety agency that is writing new guidance on self-driving cars, will be the coalition's counsel and spokesman. "The best path for this innovation is to have one clear set of federal standards and the coalition will work with policymakers to find the right solutions that will facilitate the deployment of self-driving vehicles," Strickland said in the statement.

Computer scientists from MIT and a machine learning startup, PatternEx, have reportedly developed a new system that can correctly detect 85% of cyberattacks using artificial intelligence merged with input from human experts. At the moment, security systems are closely monitored by humans and programmed to pick up on cyberattacks that only follow very specific rules, as such missing any attacks that do not follow those rules. But, there are also systems autonomously run by computers that practice anomaly detection – i.e. the identification of items, events or observations – that do not conform to an expected pattern or other items in a dataset. This method often leads to false positives, meaning that humans doubt the reliability of the system and are forced to go back and check all the results anyway. To improve this, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), in collaboration with PatternEx, have developed the AI2 artificial intelligent platform, which merges three different machine learning methods that enable computers to learn unsupervised.

Tesla Motors Inc (NASDAQ:TSLA) is riding on a free wave of notoriety since the start of this year. The firm continues to lead an industry in transition away from internal combustion engines and toward all electric power. Most of the media attention lately comes from the introduction of the "affordable" Tesla Model 3. That car won't even begin delivery until late next year but over 400k people have paid 1000 each just to get in line to buy one. One of the features that will be available on the Model 3 is Autopilot. Tesla gets a lot of attention for its Autopilot feature that provides properly equipped Model S and Model X SUVs with self-driving abilities on highways.

Tesla Motors Inc (NASDAQ:TSLA) is riding on a tidal wave of notoriety since the start of 2016. The firm is continuing to lead an industry in a transition away from internal combustion engines and toward all electric power. Most of the media attention lately comes from the introduction of the "affordable" Tesla Model 3. That car won't even begin delivery until late next year but over 400k people have paid 1000 each just to get in line to buy one. One of the features that will be available on the Model 3 is Autopilot. Tesla gets a lot of attention for its Autopilot feature that provides properly equipped Model S and Model X SUVs with self-driving abilities on highways.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

Dr Ben Azvine is responsible for BT's security innovation strategy and helped to lay the groundwork for BT's award winning new capability, BT Assure Analytics. In this interview, Ben explains how the cyber threat landscape is evolving and how new developments in technology – especially Artificial Intelligence – will help us address the threats of tomorrow. Tell us a little about your background and current role at BT. Ben Azvine: As Global Head of Security Innovation at BT my role is to look 2-5 years into the future and prepare for the coming challenges. I think it is the best time in the history of technology to be involved in security because it is such a dynamic area. Security is not just a technology issue; it is also a business and board-level issue. I would say that cyber security is currently one of the top 3 priorities for business and hence we receive a lot of support from top management to accelerate technology in this field.

At the IEEE International Conference on Big Data Security in New York City this month, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and the machine learning start-up PatternEx, presented a paper about their new security system that combines machine learning approaches and input from human security experts. This system, called AI2 (named by merging "artificial intelligence" and "analyst intuition"), has an 85 percent success rate in identifying threats and a false positive rate of 4.4 percent over a raw data set of 3.6 billion log lines. According to the paper, the three major challenges faced by the security industry are a lack of labelled examples to model learning models on, constant evolution of attacker's methods, and limited reliance on security analysts to determine each threat's risk factor. In fact, stand-alone analyst-driven approaches are limited in their effectiveness because of the fact that attackers learn the behavior used by such systems to predict possible threats, and then work their way around that learned behavior in order to bypass security systems. Furthermore, only machine learning-based approaches can be inefficient based on the fact that they raise a need for human investigation every time they come across an anomaly.