IBM delivers a piece of its brain-inspired supercomputer to Livermore national lab

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IBM is about to deliver the foundation of a brain-inspired supercomputer to Lawrence Livermore National Laboratory, one of the federal government's top research institutions. The delivery is one small "blade" within a server rack with 16 chips, dubbed TrueNorth, and is modeled after the way the human brain functions. Silicon Valley is awash in optimism about artificial intelligence, largely based on the progress that deep learning neural networks are making in solving big problems. Companies from Google to Nvidia are hoping they'll provide the AI smarts for self-driving cars and other tough problems. It is within this environment that IBM has been pursuing solutions in brain-inspired supercomputers.


IBM delivers a piece of its brain-inspired supercomputer to Livermore national lab

#artificialintelligence

IBM is about to deliver the foundation of a brain-inspired supercomputer to Lawrence Livermore National Laboratory, one of the federal government's top research institutions. The delivery is one small "blade" within a server rack with 16 chips, dubbed TrueNorth, and is modeled after the way the human brain functions. Silicon Valley is awash in optimism about artificial intelligence, largely based on the progress that deep learning neural networks are making in solving big problems. Companies from Google to Nvidia are hoping they'll provide the AI smarts for self-driving cars and other tough problems. It is within this environment that IBM has been pursuing solutions in brain-inspired supercomputers.


AI Gold Seen in Healthcare Waste NVIDIA Blog

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A new report estimates the cost of waste in the U.S. healthcare system alone ranges as high as $935 billion a year, about 25 percent of total healthcare spending. A growing army of startups and established practitioners sees the inefficiencies as a trillion-dollar opportunity to apply AI. The U.S. spends about 18 percent of its gross domestic product on healthcare, more than any other country. A report published online by the Journal of the American Medical Association surveyed 54 studies to estimate annual waste figures in six broad categories, including failures from choosing ineffective treatments (up to $166 billion), failures from coordinating multiple treatments ($78 billion), fraud and abuse ($84 billion) and administrative complexity ($266 billion). "Implementation of effective measures to eliminate waste represents an opportunity to reduce the continued increases in U.S. health care expenditures," the report concluded.


Artificial Immune Systems May Be the Future of Cybersecurity

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From CIA director John Brennan's private email to Sony Inc, from the IRS to CVS, from Target to the notorious Ashley Madison, millions of people suffered from cybersecurity breakdowns across industries. According to the Ponemon Institute, the average cost of damages from data breaches in the US hit a staggering $6.5 million this year, up $600,000 from 2014. Untallied are the personal costs to the hacker's victims: the stress associated with leaked phone numbers, credit card information, social security numbers, tax information, and the time spent getting their lives back on track. The sophistication and scope of cyber threats are expected to further escalate, yet our defenses remain rudimentary, even medieval. Overwhelmingly, the current strategy is to define the threats, and then build strong defensive walls focused on keeping nefarious agents, viruses or programs out.


Facebook's AI Is Learning to Predict and Prevent Suicide

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For years, Facebook has been investing in artificial intelligence fields like machine learning and deep neural nets to build its core business--selling you things better than anyone else in the world. But earlier this month, the company began turning some of those AI tools to a more noble goal: stopping people from taking their own lives. But it's not just tech giants like Facebook, Instagram, and China's up-and-coming video platform Live.me who are devoting R&D to flagging self-harm. Doctors at research hospitals and even the US Department of Veterans Affairs are piloting new, AI-driven suicide-prevention platforms that capture more data than ever before. The goal: build predictive models to tailor interventions earlier.