Samsung Electronics Co. is making a drive for control of the car. The South Korean smartphone maker said Monday that it would buy U.S. auto-parts supplier Harman International Industries Inc., based in Stamford, Conn., for $8 billion in an all-cash deal that instantly makes Samsung a major player in the world of automotive technology. The deal -- Samsung's biggest acquisition in its history -- reshapes the pecking order in the global automotive supply chain, reflecting a quickening pace of innovation and an increased role for companies with deep pockets and a keen understanding of mobile services. Harman, an audio pioneer that dates back to 1953, has in recent years pushed aggressively into the automotive world under CEO Dinesh Paliwal, and has secured billions in new business, including big contracts with General Motors Co. and Fiat Chrysler Automobiles NV. It has projected an order backlog of $24 billion, more than three times annual revenue, and about two-thirds of its current sales come from auto makers.

Silicon Valley is synonymous with innovation and high-tech, and Mineta San Jose International Airport wants to make sure travelers know it. The Silicon Valley travel hub is the first airport in the U.S. to introduce customer service robots. The three robotic gals (stationed in front of gates 11, 21, and 25) provide travelers with entertainment, as well as directions to dining and shopping destinations. "It's very important for Silicon Valley's airport to offer services for our travelers that are iconic to our region...we want to create a sense of place," said Rosemary Barnes, a public information manager at San Jose airport. The bots are not only iconic to the region.

Electronics giant Samsung on Monday said it will buy U.S. car and audio systems supplier Harman International for $8 billion. South Korean electronics giant Samsung looks to very quickly get up to speed in the highly-competitive smart car business with its $8 billion acquisition of U.S. car and audio systems supplier Harman International The all-cash deal will see Samsung buy the Stamford, Conn.-headquartered firm for $112.00 per share. It is the biggest acquisition in Samsung's history, the company said. Automotive electronics is expected to grow to more than $100 billion by 2025, estimates Samsung, which has made the segment a strategic priority. But the electronics titan -- hit in recent weeks by the recalls of its Galaxy Note 7 smartphone and some washing machines with tops that could detach -- is playing catchup in smart cars to competitors such as Apple, which has a CarPlay feature available in a growing number of vehicles, and Google and its Android Auto in-car platform.

Google Play Music is getting a much-needed overhaul starting this week, both inside and out. Google is revamping its Play Music streaming app for Android, iOS and Web to focus heavily on context and personalization. Using machine learning to figure out what music you want to listen to, the app will suggest songs and playlists depending on what time and day it is, where you are, what the local weather is, and other factors that could possibly affect your mood and musical preferences. The update will see a gradual global roll-out, starting this week on Android, iOS and the web version of Google Play Music. "When you opt in, we'll deliver personalized music based on where you are and why you are listening -- relaxing at home, powering through at work, commuting, flying, exploring new cities, heading out on the town, and everything in between," Google says in a blog post.

I find myself being summoned from various directions, as if I've just stepped into a party with my closest friends. Many pins I see are interesting to me -- it's a pleasant feeling. A house with a window lined with dark brown wooden shutters. A shelf made from the back of an iMac. A media console on wheels with iron legs and wooden slats.

Anthony Ledford and his colleagues at Man AHL investment fund spent three painstaking years building a machine-learning model to do something mere mortals often can't: find fresh ideas in an avalanche of data. But even Ledford, chief scientist at the $19 billion Man AHL in London, rolls his eyes when he hears people say that machine learning, a type of artificial intelligence, is going to transform hedge funds tomorrow. To Ledford, a lot of the buzz smacks of hype. The technology is more robust than its predecessors but hardly revolutionary. "There is some real science here, but it's not the way it's been portrayed," said Ledford, who holds a doctorate in mathematics.

Machine learning is on a steep adoption curve and making its inroads in our daily lives and work. The application of the technology won't be an issue at all. There's an abundance of meaningful value propositions for many functional areas, business processes and roles across multiple industries. Software vendors of enterprise business solutions are focusing their product development on machine learning and other related artificial intelligence technologies. CEO Bill McDermott of SAP said that intelligent applications will fundamentally change the way you do work in the enterprise in the next decade.

Dutch airline KLM has partnered with DigitalGenius to help incorporate machine learning into its customer service, but humans are in no way getting replaced. Robots remain a common theme in the'who will take your job?' discussions accompanying much of the debate about the future of work. However, very few have looked at the complementary rather than the industrial, revolutionary side of things. Monotonous, mundane tasks have forever come under attack from technology, with machines now operating across most manufacturing lines – though that doesn't mean we should all fear change. Take customer care, for example: it's something that seems menial, but would struggle to fully work on automation.

This is the code for Genetic Algorithms by @Sirajology on Youtube. In this demo code we use the MAGIC Gamma Telescope dataset to build a classifer. The classifier will train on the dataset and then be able to classify whether or not some energy is either Gamma Radiation or Hadron Radiation. Instead of guessing and checking the best ML model and hyperparameters to use, we use a genetic programming library called tpot to do that for us by trying out a bunch of them. See this link for an IPython notebook version of this code.

And could software design book covers that could be judged--correctly--by humans? Research in Japan says maybe. 'Designed To Be Judged' At At MIT Technology Review, an article from looks at work being done by Brian Kenji Iwana and Seiichi Uchida at Kyushu University in Japan. According to the report, they've trained a deep neural network to study book covers--to see if the network can identify genre. "Book covers are designed to give readers an idea of the content," after all, the report points out. "Good book covers are designed to be judged.