To ramp up its contribution to global fights against money laundering and terrorism financing, South Korea will introduce an artificial intelligence-based system to better filter out financial crimes, said the country's financial intelligence chief. Yoo Kwang-yeol, commissioner of the Korea Financial Intelligence Unit, said his agency is currently working to upgrade the main system that stores and analyzes information regarding hundreds of millions of financial transactions in order to increase accuracy of capturing suspicious transactions out of normal ones. Yoo Kwang-yeol, commissioner of Korea Financial Intelligence Unit speaks during an interview at his office in Gwanghwamun, central Seoul, Dec. 6. For this, a group of KOFIU experts paid a trip to Australia earlier this month to learn from the Australian financial intelligence system. "AI can help improve efficiency of sorting out suspicious financial transactions and accuracy of analyzing related account information," Yoo said.

The Canadian firm is set to invest C$100 million ($75 million) in a new autonomous vehicle-testing hub over several years, the company's chief executive said on Monday, marking a change of direction for the smartphone pioneer. Apple is said to have taken the unusual step of working on its car software far away from its California HQ. QNX, which was bought out by Blackberry in 2010, is known for producing car software. What is REALLY going on in North Korea? 'Explosion' thought... From reacting to a bad gift to buying the perfect present:... Facebook Messenger FINALLY unveils group video calls that... Look up! FOUR asteroids are set to make a'close approach'... What is REALLY going on in North Korea?

What is the Central Limit Theorem and why is it important? How many sampling methods do you know? What is the difference between Type I vs Type II error? What do the terms P-value, coefficient, R-Squared value mean? What is the significance of each of these components? What are the assumptions required for linear regression? There are four major assumptions: 1. There is a linear relationship between the variables, meaning the model you are creating actually fits the data, 2. The errors or residuals of the data are normally distributed and independent from each other, 3. There is minimal multicollinearity between explanatory variables, and 4. Homoscedasticity. This means the variance around the regression line is the same for all values of the predictor variable. What is an example of a dataset with a non-Gaussian distribution?

Amazon Go stopped the world in its tracks. The Dec. 5 introduction of Amazon's revolutionary convenience store looms among the most surprising and compelling retail announcements in recent memory: The Seattle pilot location -- which Amazon describes as "roughly 1,800 square feet of retail space that is conveniently compact, so busy customers can get in and out fast" -- advances far beyond existing self-checkout systems by eliminating the checkout process entirely. Amazon Go offers c-store staples like milk and bread, along with meals and snacks made by on-site chefs and local suppliers, as well as Amazon Meal Kits. Shoppers (a segment currently comprised exclusively of Amazon employees) scan a QR-code based mobile application upon entering the store. The e-commerce giant's Just Walk Out technology then detects when items are removed from or returned to store shelves, tracking purchases in a virtual cart, and totals the final cost when customers exit the premises.

Master everything you need to transform data into action with our Learning Path: Machine Learning, a curated collection of lessons to take you from the basics to coding your own machine learning algorithms. Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this special two-segment episode of the Data Show, I spoke with Dafna Shahaf, assistant professor at the School of Computer Science and Engineering at the Hebrew University of Jerusalem. Her area of research is focused on tools and techniques for overcoming information overload, an area of increasing importance in an attention economy.

Artificial Intelligence (AI) is an important and evolving concept that is having significant impact within the Customer Experience industry -- and it's a topic that is being talked about on a seemingly daily basis at this point. But is AI really ready for primetime in customer care? I spoke with Michael Johnston, Lead Inventive Scientist at Interactions, about frequently asked questions about AI and Machine Learning as they apply to customer care. How do you define Artificial Intelligence and Machine Learning? Artificial Intelligence refers to the capability of a machine to imitate intelligent human behavior.

A number of the notable science stories of the past year are, quite literally, out of this world. For me, the story of the year has to be the August discovery of an Earth-like planet orbiting the closest star to our own. The star, Proxima Centauri, is just 4.2 light-years from Earth. The planet circling that star has been named Proxima Centauri b. Proxima Centauri b was discovered by astronomers working on a project called Pale Red Dot, who reported that the planet lies in the star's habitable zone, meaning that it could possess water and, maybe, life.

Episode Summary: Accenture is a leading global professional services company in the tech space, providing services to many of the Fortune 500 and their global equivalents. The company recently conducted a study, combined with expertise from economists and AI researchers, about the longer-term economic impact of artificial intelligence around the world. In this episode, I spoke with Chief Technology Officer Paul Daugherty, who has been with Accenture since 1986, and who was joined by Global Technology R&D Lead Marc Carrel-Billiard. We met up at a coffee shop after an AI Summit in San Francisco, and I asked Paul and Marc about what they had learned from this newly-published study and what they consider to be the significant impacts of *AI and automation on the future job market. Brief Recognition: Paul Daugherty is Accenture's CTO and leads the company's Technology Innovation & Ecosystem group.

Jerry Kaplan is widely known as an Artificial Intelligence expert, technical innovator, serial entrepreneur, and bestselling author. He is currently a Fellow at The Center for Legal Informatics at Stanford University and a visiting lecturer in the computer science department, where he teaches social and economic impact of Artificial Intelligence. Kaplan founded several technology companies over his 35-year career, two of which became public companies. As an inventor and entrepreneur, he was a key contributor to the creation of numerous familiar technologies including tablet computers, smart phones, online auctions, and social computer games. Kaplan is the author of three books: the best-selling classic Startup: A Silicon Valley Adventure; Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence (2015); and Artificial Intelligence: What Everyone Needs to Know (2016). In 1998, Kaplan received the Ernst & Young Emerging Entrepreneur of the Year Award, Northern California. He has been profiled in The New York Times, The Wall Street Journal and Forbes, among others. He received a BA degree from the University of Chicago and a PhD in Computer and Information Science from the University of Pennsylvania. Jerry will be speaking at the Gigaom AI Now in San Francisco, February 15-16th.

Here are some story lines I don't want you to miss today. Donald Trump has chosen one of the most consistently conservative presidential cabinets in recent history -- one whose presumed members' views don't always align with what Trump promised on the campaign trail. In Washington circles, the biggest guessing game is how it will all play out. Somehow, you have to think tweeting is involved. We don't want to jinx it, but … all of California should be in for some rain today.