You Should Have the Right to Inspect Google's Robo-Car Tests


Driverless cars are set to improve, disrupt, and challenge the way we travel--someday. As of now, self-driving cars aren't available for widespread use, as they aren't sufficiently developed or safe to be commercially sold. It may take decades before they are able to infiltrate the market or gain enough public acceptance to be successful. Seth Birnbaum is CEO of EverQuote, the largest online auto insurance marketplace in the US. Even though autonomous vehicles haven't gone mainstream, US government regulators published their automated vehicle policy in September, and many states are working to develop regulations for autonomous cars.

US Air Force experiments create 'supersoldiers' with enhanced mental skills by boosting brains with electric shocks

Daily Mail

Military scientists in the US have revealed a series of experiments designs to create'supersoldiers' with enhanced mental capabilities. The successful tests used electrical brain stimulators to enhance the mental skills of soldiers. It is hoped the research could lead to treatments for drone operators, air crews and others in demanding roles. The successful tests at Wright-Patterson Air Force Base in Ohio used electrical brain stimulators to enhance the mental skills of soldiers. It is hoped the research could lead to treatments for drone operators, air crews and others in demanding roles.

Former NASA chief's startup exits stealth with a 256-core machine learning chip


Daniel Goldin has an impressive resume. The 75-year-old spent over a quarter century in the aerospace industry during the first leg of his career, went on to become the director of NASA and is now returning to the fold as the head of a newly launched startup. KnuEdge Inc., as the outfit is called, hit the scene today with a homegrown processor specifically designed to run machine learning algorithms. Dubbed KNUPATH, the chip sports 256 cores and 16 bidirectional I/O paths that provide 320 Gbs of throughput. It's also well-equipped to run in large environments, with the startup claiming that a single deployment can scale to over half a million nodes while keeping inter-rack latency at around 400 milliseconds.

KnuEdge Accelerates Neural Computing With Introduction of KNUPATH LambdaFabric Processor Technology


SAN DIEGO, CA--(Marketwired - Jun 6, 2016) - KnuEdge Inc., a neural technology innovation company that launched today, introduced its KNUPATH LambdaFabric processor technology enabling ground-breaking scalability, latency and workload performance in next-generation data centers. With a fundamentally different architecture than legacy products, KNUPATH can operate alone or be integrated with other devices, and it is available now to both end customers and technology vendors seeking to create data center neural computing capabilities to support advancements in machine learning, IoT and signal processing. "Many of today's CPUs, GPUs and FPGAs force system designers to either create workarounds with last-generation chip sets or reduce their requirements for advanced-compute projects," said Dan Goldin, Founder and CEO of KnuEdge. "After ten years of stealth development and rigorous testing, LambdaFabric enters the market as mature technology which enables system designers to meet the most demanding requirements now, and also helps them rethink what is possible with neural computing in the future." As evidenced by recent announcements such as Google's Tensor Processing Unit, there is increasing industry interest in targeted processor acceleration for machine learning and other growing workloads.

An ex-Nasa chief has revealed a stealth startup that beats Apple's Siri


A startup founded by a former top boss at Nasa has emerged from so-called stealth mode with technology that claims to beat Apple, Google and Microsoft's voice recognition technology. Dan Goldin, who spent nearly all of the 1990s leading Nasa, has revealed KnuEdge, a machine learning company that already boasts Fortune 500 clients and 100m in private funding despite its under the radar nature for the last decade. "We are not about incremental technology. Our mission is fundamental transformation," said Goldin "We were swinging for the fences from the very beginning, with intent to create next-generation technologies that will in essence alter how humans interact with machines, and enable next-generation computing capabilities ranging from signal processing to machine learning." The US-based firm has revealed its first product, KnuVerse, which it claims is a military-grade voice recognition and authentication technology, and believes it is more powerful than the most advanced but early stage voice recognition used in services such as Apple's Siri and Google's Home and Alexa.

New DARPA Project, Fun LoL, Seeks to Find the Limits of Machine Learning - DATAVERSITY


Cooney goes on, "With Fun LoL DARPA is looking for information about mathematical frameworks, architectures, and methods that would help answer questions such as: What are the number of examples necessary for training to achieve a given accuracy performance? What are important trade-offs and their implications? How close is the expected achievable performance of a learning algorithm compared to what can be achieved at the limit? What are the effects of noise and error in the training data? What are the potential gains possible due to the statistical structure of the model generating the data?"

IBM Research Lead Charts Scope of Watson AI Effort


Watson represents a larger focus at IBM that integrates machine learning and data analytics technologies to bring cognitive computing capabilities to its customers. He is an IBM Fellow, Vice President Europe and Director IBM Research – Zurich Research Laboratory, Switzerland. In January 2014, IBM launched the IBM Watson business unit, investing 1B dedicated to developing and commercializing cloud-delivered cognitive computing technologies. In addition to the Watson business unit, in September 2015 we announced Watson Health, dedicated to improving the ability of doctors, researchers and insurers to surface new insights from the massive amount of personal health data being created and provide turnkey solutions to deliver personalized healthcare.

How artificial intelligence could radically transform education


Artificial intelligence should be used to provide children with one-to-one tutoring to improve their learning and monitor their well-being, academics have argued. However, in a paper, academics from University College London's Knowledge Lab argue that AI systems could simulate human one-to-one tutoring by delivering learning activities tailored to a student's needs and providing targeted and timely feedback, all without an individual teacher present. It adds: "The increasing use of AIEd systems will enable the collection of mass data about which teaching and learning practices work best. "AIEd systems can provide tailored support to parents in the same way that they can for teachers and students, improving education and outcomes for both parents and their children.

10 Machine Learning Algorithms Explained to an 'Army Soldier'


It include algorithms such as Linear Regression, Logistic Regression, Decision Tree, Random Forest etc. This includes Decision Trees, Random Forest. In this article, I've explained machine learning algorithms to a soldier in terms of war, battle, and strategy. Do you find watching battle, wars interesting?

ACM Moral Imperatives vs. Lethal Autonomous Weapons

Communications of the ACM

It described as "fundamentally vague" Stephen Goose's ethical line in his Point side of the Point/Counterpoint debate "The Case for Banning Killer Robots" in the same issue. I encourage all ACM members to read or re-read them and consider if they themselves should be working on lethal autonomous weapons or even on any kind of weapon. Ronald Arkin's Counterpoint was optimistic regarding robots' ability to "... exceed human moral performance ...," writing that a ban on autonomous weapons "... ignores the moral imperative to use technology to reduce the atrocities and mistakes that human warfighters make." This analysis involved two main problems. First, Arkin tacitly assumed autonomous weapons will be used only by benevolent forces, and the "moral performance" of such weapons is incorruptible by those deploying them.