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LendingRobot launches hedge fund that uses blockchain and machine learning -- with no human intervention

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LendingRobot, an automated online investment-management service that calls itself a "robo-advisor," is launching a hedge fund that the company says is administered without human intervention, making use of Amazon Web Services' machine learning, compute servers and blockchain technology. Until now, the business of Seattle-based LendingRobot has been focused on helping manage investments in so-called peer-to-peer loans. In such loans, would-be borrowers too risky for banks seek loans from individuals. Companies including Lending Club and Prosper grade loan applications by risk and make them available to individual investors, most of whom spread their risk by investing small amounts in many individual loans. The investment is attractive, as it can yield 8-10 percent interest paid monthly.


How Silicon Valley is teaching language to machines

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The dream of building computers or robots that communicate like humans has been with us for many decades now. And if market trends and investment levels are any guide, it's something we would really like to have. MarketsandMarkets says the natural language processing (NLP) industry will be worth $16.07 billion by 2021, growing at a rate of 16.1 percent, and deep learning is estimated to reach $1.7 billion by 2022, growing at a CAGR of 65.3 percent between 2016 and 2022. Of course, if you've played with any chatbots, you will know that it's a promise that is yet to be fulfilled. There's an "uncanny valley" where, at one end, we sense we're not talking to a real person and, at the other end, the machine just doesn't "get" what we mean.


Elon Musk Sees Brain-Computer Systems in Humans' Future

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Is human intelligence heading toward a cyborg-dominated future? In a recent tweet, the Tesla and SpaceX CEO teased that a brain-computer system that links human brains to a computer interface -- a "neural lace" -- may be announced early this year, reported TechCrunch. Musk first mentioned the neural lace concept (the addition of a digital layer of intelligence to the human brain) at Recode's Code Conference last year. The brain-computer system would create a"symbiosis with machines," Musk said, according to TechCrunch. "We're already a cyborg -- I mean, you have a digital or partial version of yourself in the form of your emails and your social media and all the things that you do, and you have basically superpowers with your computer and your phone and the applications that are there," Musk said at the conference.


Open Data Spotlight: The Global Terrorism Database

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Publishing data on Kaggle is a way organizations can reach a diverse audience of data scientists with an enthusiasm for learning, knowledge, and collaboration. For Dr. Erin Miller of START, the National Consortium for the Study of Terrorism and Responses to Terrorism, making her organization's Global Terrorism Database available for analysis by Kaggle users has brought new awareness to their cause. In this Open Data Spotlight, Erin discusses how setting aside agendas and focusing on understanding this unparalleled dataset of over 150,000 attack events allows users to undertake constructive analyses that may defy common conceptions about terrorism. Read on to learn more about the Global Terrorism Database project and the ways users of open data can make valuable contributions to the organizations that make them possible. My role started out (more than 12 years ago) as a graduate assistant cleaning raw data, and now I manage the project team, workflow, resources, and interaction with end users and related research projects.


The Lumiata AI prescribing healthcare interventions

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The hysteria surrounding both machine learning and artificial intelligence is substantiating mathematician Alan Turing's assertion that eventually "no one will be able to speak of machines thinking without expecting to be contradicted". Indeed now, the concept of the'rise of robots' is no longer merely a plot in a Hollywood sci-fi blockbuster, but an area being explored by academics, researchers and technologists across the world. Silicon Valley start-up Lumiata, for example, uses AI to map out current and future health trajectories of individuals and provide detailed reasons behind every prediction. Ash Damle, founder and CEO of the company, told BusinessCloud that AI solves an issue of scale. "If we gave physicians enough time to go through all of the data and look for patterns and individuals, they could get some wonderful insight, but the reality is that people are constrained," he said.


Artificial Intelligence to Challenge Poker Players Again

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New AI vs. humans poker challenge is set to kick off on Wednesday. The poker-playing algorithm humans will be facing this time around was named Libratus. After successfully solving games like chess and even Go, scientists seem bent to crack poker next. The research into an artificial intelligence that could stand up to top-tier poker players has been going on for some time now. The results so far haven't been very encouraging for these scientists, but they aren't giving up.


The Future of AI in Digital Advertising

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Marketers are beginning to realize AI’s potential as a tool for improving the effectiveness of campaigns, but understanding of its capacity remains limited. "Smith & Tinker's Patent Double-Action, Extra-Responsive, Thought-Creating, Perfect-Talking Mechanical Man [โ€ฆ] Thinks, Speaks, Acts, and Does Everything but Live." - Ozma of Oz, L. Frank Baum, 1907 Written almost 110 years ago, L. Frank Baum's product description of a mechanical man powered by artificial intelligence (AI) was a humorous oddity in a fantasy world. While we may not have Tik-Tok -- except on screen in the Return to OZ -- we do now have smart technology. The powerful urge to streamline our existence has spawned a host of consumer-level AI applications that promise to do nearly everything. AI-driven tools like image and voice recognition on smartphones, algorithm-based viewing suggestions for Netflix, and Google’s real language analysis in search, are now integral to everyday life.


Study Develops Artificial Intelligence To Discover Drugs Faster And Systematically

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A cure for cancer and other critical medical conditions could already be in existence as a recent study by Professors of Pharmaceutical Chemistry, Steven Atschuler and his wife, Lani Wu has developed a new method that uses artificial intelligence for faster and systematic drug discovery. The new technique reduces the time and cost previously used to search for possible new drugs to treat illnesses and diseases. The husband and wife research team at University Of California-San Francisco (UCSF) designed a new method to make drug discovery faster and at a cheaper cost than that of the traditional method. Atschuler and his wife have worked together since they met as students almost 30 years ago. Their study is informed not only by their extant collaboration but by other previously shared careers in other fields, according to Phys.


4 Predictions for cloud computing and machine learning in 2017 Content and Data, Integration and Distribution Bloomberg for Enterprise

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Frustrated with the impact of technology advances on infrastructure upgrades and IT budgets, a growing number of organizations are opting for cloud computing investments instead. That is the view of Bluelock Chief Technology Officer Pat O'Day, who shared his predictions for cloud computing and machine learning with Information Management. O'Day sees four key trends driving cloud computing in 2017. "There's a lot of churn in the hardware space because of virtualization," O'Day explains. "Companies are growing tired of having to refresh their IT systems with new hardware every five years. People want to be more mobile, and the cloud is a way to get there. Plus, rapid technology innovation has driven increased competition (think about the rise in artificial intelligence, for example)."


Google Translate is about to get a lot better, thanks to machine learning push

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Google CEO Sundar Pichai is offering a big new update that should affect anyone who's ever used Google's translation services. The new version will be rolling out in 2017 via Google Cloud, Pichai said. "We have improved our translation ability more in one single year than all our improvements over the last 10 years combined," Pichai told investors in a quarterly call, after parent company Alphabet reported mixed results. Like Alphabet, a lot of technology companies -- from IBM to to Amazon -- are talking about how machine learning and artificial intelligence algorithms are making their offerings more efficient. Until very recently, users have not always see those algorithms in action.