Germany and Japan, March 8, 2017 --- Deutsches Forschungszentrum für Künstliche Intelligenz (German Research Center for Artificial Intelligence, 'DFKI') and Hitachi, Ltd. (Hitachi) today announced the joint development of AI (artificial intelligence) technology for human activity recongnition of workers using wearable devices. The AI technology performs real-time recognition of workers' activities by integrating technology in eye-tracking glasses*1to recognize gazed objects with technology in armband devices to recognize action. The recognition ability of each activity is achieved by having the AI understand the tools or parts used at the production site as well as anticipated actions through Deep Learning*2. DFKI and Hitachi will use this newly developed AI technology to assist operations and prevent human error, to contribute to enhancing quality and efficiency on the front line of manufacturing. In line with initiatives such as Industry 4.0*3in Germany and Society 5.0*4in Japan, the manufacturing industry is accelerating steps towards innovating production using AI and robotics, and the automation of menial tasks.

First they figured out how to play checkers and backgammon. Then they mastered chess, Go, "Jeopardy!" and even a few Atari video games. Now computers can challenge humans at the poker table -- and win. DeepStack, a software program developed at the University of Alberta's Computer Poker Research Group, took on 33 professional poker players in more than 44,000 hands of Texas hold'em. Overall, the program won by a significantly higher margin than if it had simply folded in each round, according to a new study in Science.

Metastasis detection is currently performed by pathologists reviewing large expanses of biological tissues… This process requires highly skilled pathologists and is fairly time-consuming and error-prone,

Want to know where all the wind and solar power supplies in the US are for some brilliant renewable-energy project? Or plot a round-the-world trip hitting every major soccer stadium along the way? It should be possible with a new tool that lets anyone scan the globe through AI "eyes" to instantly find satellite images of matching objects. Descartes Labs, a New Mexico startup that provides AI-driven analysis of satellite images to governments, academics and industry, on Tuesday released a public demo of its GeoVisual Search, a new type of search engine that combines satellite images of Earth with machine learning on a massive scale. The idea behind GeoVisual is pretty simple.

It works rather like the BB-8 robot from Star Wars, and could change the way we drive. Goodyear has revealed a radical new spherical tire powered by AI and linked to the car by magnetic force so it can rotate on any axis in any direction. The firm says it will be able to sense road conditions and adapt accordingly, turning itself into either a wet or dry weather configuration instantly. Working like human muscles, the smart tire can re-shape the individual sections of the tire's tread design, adding'dimples' for wet conditions (left) or smoothing the tread for dry conditions (right) Made of super-elastic polymer, the tire's bionic skin has a flexibility similar to that of human skin, allowing it to expand and contract. This outer layer covers a foam-like material that is strong enough to remain flexible despite the weight of a vehicle.

IBM Watson burst onto the world stage in 2011 when it participated in the trivia-based game show Jeopardy!. The supercomputer beat out two former champions to claim a victory for "artificial intelligence." Since then, Watson has embarked on a number of challenges across a variety of domains, from identifying the best cancer treatments to improving weather forecasting. Adding Watson's cognitive capabilities allows financial services companies to go beyond traditional rules-based policy and demographic views for a deeper understanding of customer profitability and preferences. In turn, this allows them to offer new, more personalized offerings and experiences.

Late last year, Google announced a breakthrough in translating. Dubbed Neural Machine Translation, it let Google's AI-powered engine tackle full sentences instead of just words, giving translations a more natural feel. Now Google is expanding it to a several more languages. Back when it launched, Google's new translator was available for English and just eight other languages, including French, German, Spanish, Portuguese, Chinese, Japanese, Korean, and Turkish. Now it is bringing it to Hindi, Russian, and Vietnamese, with more rolling out in the coming weeks.

Here's an interesting use of machine learning, using it to gauge the influence of a particular Twitter user.

LoopMe, a digital advertising firm that uses artificial intelligence (AI) to optimize mobile video advertising, has raised $10 million in a funding round led by Impulse VC and Harbert European Growth Capital, with participation from Holzbrinck Ventures and Open Ocean Capital. Founded out of London in 2012, LoopMe unifies all the popular mobile video ad formats, covering pre-roll, HTML5, and the VAST ad-serving standard. In a nutshell, the platform replaces humans with algorithms that determine the placement of ads in real time, based on metrics such as purchase intent or offline sales. The technology "learns" how viewers are reacting to the ads and changes them based on how a user is responding. The company's platform has been used by a host of well-known brands, including Microsoft, Disney, Airbnb, and Honda.

ChainerRL is a deep reinforcement learning library that implements various state-of-the-art deep reinforcement algorithms in Python using Chainer, a flexible deep learning framework. ChainerRL is tested with Python 2.7 and 3.5.1 . For other requirements, see requirements.txt. ChainerRL contains atari_py as dependencies, and windows users may face error while installing it. This problem is discussed in OpenAI gym issues, and one possible counter measure is to enable "Bash on Ubuntu on Windows" for Windows 10 users.