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What artificial intelligence will look like in 2030

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Over the next 15 years, AI technologies will continue to make inroads in nearly every area of our lives, from education to entertainment, health care to security. "Now is the time to consider the design, ethical, and policy challenges that AI technologies raise," said Grosz. The report investigates eight areas of human activity in which AI technologies are already affecting urban life and will be even more pervasive by 2030: transportation, home/service robots, health care, education, entertainment, low-resource communities, public safety and security, employment, and the workplace. Some of the biggest challenges in the next 15 years will be creating safe and reliable hardware for autonomous cars and health care robots; gaining public trust for AI systems, especially in low-resource communities; and overcoming fears that the technology will marginalize humans in the workplace.


Exploiting machine learning in cybersecurity

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MIT's Computer Science and Artificial Intelligence Lab (CSAIL) has led one of the most notable efforts in this regard, developing a system called AI2, an adaptive cybersecurity platform that uses machine learning and the assistance of expert analysts to adapt and improve over time. The system uses near-real-time analytics to identify known security threats, stored data analytics to compare samples against historical data and big data analytics to identify evolving threats through anonymized datasets gathered from a vast number of clients. Combining this capability with the data already being gathered by IBM's threat intelligence platform, X-Force Exchange, the company wants to address the shortage of talent in the industry by raising Watson's level of efficiency to that of an expert assistant and help reduce the rate of false positives. This technique gives the cybersecurity firm the unique ability to monitor billions of results on a daily basis, identify and alert about the publication of potentially brand-damaging information and proactively detect and prevent attacks and data loss before they happen.


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Machine learning and AI could be the key to protecting enterprise IT from advancing cybersecurity threats, Cylance CEO Stuart McClure said on Tuesday. McClure's company, which bills itself as "advanced threat protection for the endpoint," uses machine learning to analyze massive amounts of data in an organization and classifies that data automatically. Cylance, in offering breach protection, is often confused with legacy anti-virus software, McClure said. The US Office of Personnel Management (OPM) eventually brought Cylance in to help them work on the early days of what would eventually be determined to be a massive breach.


Business Case Drive Enhancements to Video Analytics

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The video analytics industry is typically split into two distinct camps: (1) systems designed around rules and user-specified rules or models and (2) autonomous systems designed around machine learning. Supervised learning systems require heavy training and feedback to achieve the desired output, where unsupervised learning systems train themselves from the input data and require minimal human input. The video analytic solutions we saw in the market a decade ago seem rudimentary compared to today's offerings; partly due to the technology catching up with early promises and partly due to the industry's understanding and level-setting of expectations from the initial splash of analytics hyped as a panacea and the future of security. However, some of the extreme claims such as its ability to replace trained human operators, eliminate the need for well-designed camera placement, completely eliminate false positives, and determine a person's intent ahead of an action have proven to be more hype than reality for many end users.


A strategy for "convergence" research to transform biomedicine

MIT News

The report, "Convergence: The Future of Health," was co-chaired by Tyler Jacks, the David H. Koch Professor of Biology and director of MIT's Koch Institute for Integrative Cancer Research; Susan Hockfield, noted neuroscientist and president emerita of MIT; and Phillip Sharp, Institute Professor at MIT and Nobel laureate, and will be presented at the National Academies of Sciences, Engineering, and Medicine in Washington on June 24. Accordingly, the report's authors call for increasing NIH funding for convergence research to at least 20 percent of the agency's budget. And the National Cancer Moonshot Initiative, launched earlier this year to accelerate research to develop cancer vaccines and early detection methods and genomic tumor analysis, will also operate largely using convergence tools and approaches. As a concrete next step, the report's authors recommend establishing an interagency working group on convergence with participation from NIH, the National Science Foundation, and other federal agencies involved in funding scientific research, such as the Food and Drug Administration and the Department of Energy.


FAA completes landmark rules for commercial drones

USATODAY

WASHINGTON – New drone rules from the Federal Aviation Administration limit most small commercial drone operations to daylight hours and require operators to get certified every two years. "It is essential that all rules developed to promote the safe operation of unmanned aircraft systems must be consistent with and compatible with those for all other airspace users," the group said in a statement. Another 10,054 people registered one drone apiece for special permission for non-hobbyist operations such as for police and fire departments. At least 31 states have adopted laws governing drones, with 18 requiring search warrants for police to use drones for surveillance, 13 adopting criminal penalties for misusing drones and 12 creating privacy protections, according to the National Conference of State Legislatures.


Artificial Intelligence in Defence and Security Industry – AI.Business

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In the last few decades, one of the largest sources of funding for AI research came from the Defense Advanced Research Project Agency (DARPA), which is agency of the Department of Defense of the United States of America responsible for the development of new technologies for use by the military. Using machine learning techniques inspired by the self-learning intelligence of the human immune system, UK-based startup Darktrace tackles the challenge of detecting previously unidentifiable cyber threats in real time, and allows them to be eradicated more quickly than traditional approaches. It includes a big data platform designed for large data volumes and real time response, an ensemble of algorithms designed to detect rare behaviors with the goal of identifying new attacks, an active learning feedback loop that continuously improves detection rates over time and a repository of threat intelligence that can be shared among enterprises. The future of cyber-security looks part human and part machine, according to MIT's Computer Science and Artificial Intelligence Laboratory.


Stanford and White House host experts to discuss future social benefits of artificial intelligence Stanford News

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Stanford's Russ Altman, left, and Fei-Fei Li will host a June 23 panel on artificial intelligence. In the face of this revolution, Stanford and the White House Office of Science and Technology Policy will host a panel of AI visionaries from academia, government and industry to discuss how to responsibly integrate the ever-evolving technology into the real world. The conversation will be co-hosted by Russ Altman, professor of bioengineering, of genetics, of medicine and, by courtesy, of computer science, and the faculty director of the One Hundred Year Study on Artificial Intelligence; and Fei-Fei Li, associate professor of computer science and, by courtesy, of psychology, and director of the Stanford Artificial Intelligence Lab. Li: One big challenge is the lack of understanding of AI in our society at large, including industrial leaders, lawmakers, public officers and the general public.


Self-driving cars could dramatically change the auto-insurance industry

Los Angeles Times

The auto insurance industry faces upheaval in the next 25 years as the migration to autonomous safety features -- and ultimately a self-driving car -- shifts more of a car's accident risk from the driver to the vehicle, analysts said. The U.S. market for personal auto insurance policies, which currently generates 200 billion in premiums a year, could shrink substantially, some experts predict. And don't expect a price cut in auto insurance anytime soon. " Adrian Flux General Manager Gerry Bucke said in a statement.


In Radiology, Man Versus Machine

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The Case for AI In effect, AI is the next generation of clinical decision support – technology designed to enhance a radiologist's ability to identify and correctly diagnose any problems caught on diagnostic images. Its use has since expanded into clinical analytics, mining imaging data to improve medical treatment. AI can also take breast cancer diagnosis a step further, incorporating real-world, pre-existing images, said Igor Barani, MD, chief medical officer of deep learning healthcare company Enlitic. According to Jenny Chen, MD, chief executive officer and founder of 3D healthcare printing company 3DHeals, AI use presents problems, while reducing the amount of time radiologists spend reading images.