A product from Japan created quite the stir at Consumer Electronics Show in Las Vegas and CEATEC JAPAN in Tokyo this year. The "harmony" of clothing analysis, artificial intelligence (AI), and robotics blend together to produce a "fully automatic clothes folding machine." Japan technological alliance "seven dreamers laboratories' is the developer. The product details have been released in various places, so I won't get into that, but as the name says, "It's a robot that folds clothes. No further explanation is needed." The company announced a partnership with Panasonic (TSE:6752) and Daiwa House (TSE:1925) last year, and together established the joint venture Seven Dreamers Laundroid with plans to begin sales by reservation for their first machine "Laundroid 1" in March of 2017. The developer, Seven Dreamers, announced on November 14th the securement of 6 billion yen (around $60 million US) in funds from SBI Investment, in addition to Panasonic and Daiwa House. The shareholding ratios and payment date remain undisclosed. The concept began in 2005, and with the realization of "folding" from 2013, Laundroid was born. I heard from Seven Dreamers CEO Shin Sakane about the road it took to get here. I came today with the idea of asking straight out, "What happened to make robots fold the laundry?" Well, to be straight, "It's now possible to recognize clothes using artificial intelligence," is maybe the simplest answer I can give. Let's go through the process. How did the idea first come to you? Before that, first permit me to talk a little about what criteria the Seven Dreamers esteem. For us, there are three criterion for "Things that have not been realized yet but could change our lives, and also enrich them." The technological hurdles are high and our policy is to clear them. You've made something that sets high hurdles. Since first coming up with the idea, I was thinking about different markets to satisfy all the criteria. Looking around we see many products targeted at men. Starting now and into the future, 'women', 'the elderly', and'children' are the keywords that will become important. After thinking, the idea that maybe the answer lies within the home came to me and, while I don't usually talk with my wife about work, I casually mentioned it to her. What do you wish you had? She came back just as fast, "Of course, it has to be a machine that folds the laundry.

Information extraction involves classifying data items that are stored in plain text, and is a major area of research for machine learning scientists. Last week, a research team from MIT introduced a new approach to information extraction for machine learning systems at the Association for Computational Linguistics' Conference on Empirical Methods on Natural Language Processing, and won a best-paper award. Instead of feeding their system as much data as possible, the team's winning approach takes a different route and focuses on a much smaller data set, a similar process used by human beings – if you're reading a paper that you don't understand, you're likely to do a search on the web and find articles that you are able to understand. This new system approach does something similar; if the system's confidence score is low in assessing a particular text, it will query for more information, pulling up a handful of new articles from the web that correlate with a specific set of terms. In future, this model could be applied to sparse data and save much time in reviewing databases.

Few technologies have the transformative potential to reshape how we live, move, and work. Electricity and the Internet were two technologies that fundamentally transformed life in the 20th century. Artificial intelligence (AI) is the 21st century equivalent of electricity and the Internet. According to a new white paper from Tractica, AI is expected to bring massive shifts in how people perceive and interact with technology, with machines performing a wider range of tasks, in many cases doing a better job than humans. Tractica's white paper analyzes 10 key trends that are influencing the development of the global artificial intelligence market, and is available for free download on the firm's website.

As Hyperloop One continues its attempt at building the future of public transportation, it's moving on without the baggage of a messy lawsuit. The company announced today that it has reached a settlement with former employees, including co-founder and former CTO Brogan BamBrogan. No terms were disclosed, however, the lawsuit contained allegations of financial mismanagement, harassment and threats, which Hyperloop One had responded to with a $250 million suit of its own, claiming the exec had tried to lead a coup within the company. In a memo to current employees, CEO Rob Lloyd looked forward, citing the company's opening of a fabrication facility, acquiring $50 million in financing and new partnerships. Now the company can focus on more standard issues, like delivering on its vision of self-driving vehicles that turn into high-speed train cars.

CAMBRIDGE, MA - 10 Nov 2016: IBM Watson Health (NYSE: IBM) and the Broad Institute of MIT and Harvard today announced a research initiative aimed at discovering the basis of cancer drug resistance. The five year, $50 million project will study thousands of drug resistant tumors and draw on Watson's computational and machine learning methods to help researchers understand how cancers become resistant to therapies. The anonymized data will be made available to the scientific community to catalyze research worldwide. IBM Watson Health and the Broad Institute bring the data prowess of Watson to study cancer drug resistance in a $50M research collaboration. The goal is to identify patterns that could reveal clues into one of the greatest medical mysteries of cancer.

Intel announced a slew of products, technologies and investment in an effort to fix its position in the field of artificial intelligence. In the new move, Intel has assembled a set of technology options to drive AI capabilities in everything from smart factories and drones to sports, fraud detection and autonomous cars. Intel is increasing its focus on AI as it believes it can power the AI products released recently by companies like Facebook and Google. In a blog Intel CEO Brian Krzanich had said, "Intel is uniquely capable of enabling and accelerating the promise of AI. Intel is committed to AI and is making major investments in technology and developer resources to advance AI for business and society."

BOULDER, Colo.--(BUSINESS WIRE)--Few technologies have the transformative potential to reshape how we live, move, and work. Electricity and the Internet were two technologies that fundamentally transformed life in the 20th century. Artificial intelligence (AI) is the 21st century equivalent of electricity and the Internet. According to a new white paper from Tractica, AI is expected to bring massive shifts in how people perceive and interact with technology, with machines performing a wider range of tasks, in many cases doing a better job than humans. Tractica's white paper analyzes 10 key trends that are influencing the development of the global artificial intelligence market, and is available for free download on the firm's website.

"In 2015 Chartis's continuous market scan of end-user organizations identified Ayasdi as one of the most innovative AI players in the risk and compliance space," said Peyman Mestchian, Managing Partner at Chartis. "We have been particularly impressed by the practical use-cases and proof points provided by Ayasdi and how its large-scale machine intelligence-based applications and overall platform strategy help some of the world's largest financial services firms to reduce the cost and risk of compliance." Ayasdi is well positioned globally to help financial services firms leverage AI to address pressing challenging including CCAR/stress testing, risk management, internal surveillance, client intelligence, market intelligence, fraud detection and anti-money laundering. Ayasdi's enterprise machine intelligence platform ingests and processes large volumes of internal data, market data, and/or third party data and then applies multiple machine learning, statistical and geometric algorithms to gain insight and predict the future. For some applications, such as anti-money laundering, Ayasdi operates autonomously behind the scenes to help reduce false positives in existing rule-base AML systems.

LIDAR sensors are an essential element in future fully autonomous or semi-autonomous self-driving cars. The system operates on the principle of time-of-flight measurement. A very short laser pulse is transmitted, hits an object, is reflected and detected by a sensor. From the time-of-flight of the laser beam it is possible to calculate the distance to the object. Scanning LIDAR systems scan the surroundings of the car horizontally with a laser beam across a certain angular segment and produce a high-resolution 3D map of the environment.

SALT LAKE CITY, UT--(Marketwired - Nov 15, 2016) - At SC16, AMD (NASDAQ: AMD) announced that Radeon GPU technology will be available to Google Cloud Platform users worldwide. Starting in 2017, Google will use AMD's fastest available single-precision dual GPU compute accelerators, Radeon-based AMD FirePro S9300 x2 Server GPUs, to help accelerate Google Compute Engine and Google Cloud Machine Learning services.(1) AMD FirePro S9300 x2 GPUs can handle highly parallel calculations, including complex medical and financial simulations, seismic and subsurface exploration, machine learning, video rendering and transcoding, and scientific analysis. Google Cloud Platform will make the AMD GPU resources available for all their users around the world. "Graphics processors represent the best combination of performance and programmability for existing and emerging big data applications," said Raja Koduri, senior vice president and chief architect, Radeon Technologies Group, AMD.