It's easy to think of AI as cold, unbiased, objective. Not quite, suggests Narrative Science Chief Scientist Kris Hammond explains, because we never know when AI will repeat our biases back to us. "Just as our biases creep into how we talk to, we train, we teach our children, they creep into the way we talk to, train, and teach our AI systems," says Hammond, also a professor of Computer Science at Northwestern University and founder of the University of Chicago's Artificial Intelligence Laboratory. Narrative Science uses machine learning to turn data into stories that help people better understand the world around them. Its natural language generation platform, Quill, has generated headlines by literally generating headlines: automating the production of earnings reports and sports stories, among other tasks.

WorkFusion, the leading provider of intelligent automation, has closed a $35 million Series D financing round led by Georgian Partners with participation from existing investors Mohr Davidow Ventures, iNovia, Nokia Growth Partners (NGP), Greycroft and RTP Ventures, bringing total funds raised to $71 million. The funding will accelerate customer adoption of AI-powered automation as they realize the immense productivity gains from digitizing business processes. "We invested in WorkFusion not only because it aligns with our thesis that AI will transform business, but most importantly because the company has made machine learning practical and powerful for enterprise operations," said Justin LaFayette, Managing Partner at Georgian Partners. "WorkFusion has category leading products and a strong leadership aligned by a powerful vision of helping businesses drive rapid productivity improvements with AI." WorkFusion transforms operations through self-learning, process-level automation that eliminates up to 90% of manual back-office work and AI-powered chat bots that increase front office service center capacity by 5x. "IDC estimates the AI and cognitive systems market will grow from $8 billion in 2016 to over $47 billion in 2020 and businesses are looking to invest in the most innovative and comprehensive automation technologies on the market," said Max Yankelevich, WorkFusion CEO.

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.

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.

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.

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 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.

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.

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 […] 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.

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.