"Million Meals" project applied artificial intelligence, the Internet of Things and blockchain to drive efficiency and timeliness of lunch program in government schools across India Accenture and Akshaya Patra, the world's largest NGO-run Mid-Day Meal Program, collaborated on an innovative project that used disruptive technologies to exponentially increase the number of meals served to children in schools in India that are run and aided by the government. The "Million Meals" project revolutionized Akshaya Patra's supply chain and operations, resulting in improved food quality and expanded service reach. Rooted in a vision to eliminate child hunger, the "Million Meals" project demonstrated how disruptive technologies such as artificial intelligence (AI), the Internet of Things (IoT) and blockchain can help address significant challenges in mass meal production and delivery. Accenture Labs, the research and development arm of Accenture, executed the project over a period of six months in Akshaya Patra's Bengaluru kitchen. An analysis of the project indicated a potential to improve efficiency by 20 percent, which could boost the number of meals served by millions.

Panasonic will focus its research and development on artificial intelligence and the "internet of things" to drive growth in hopes of reversing the decline in group sales. The company plans a tenfold increase of AI-related engineers from the 100 currently employed within five years, executives announced at a news conference Wednesday outlining the strategy. Securing manpower has become an issue in the competition against American IT companies. Panasonic will triple its ranks of AI engineers to 300 in the next two years and aims to have 1,000 within five years, said Yoshiyuki Miyabe, director of the company's new business innovation division. The division, established April 1, will have a hand in the AI push. Panasonic has also been busy tapping outside talent.

Problem decomposition and theory reformulation, integrated cognitive architectures for autonomous robots, distributed constraint satisfaction problems, semigroup theory and dynamical systems, category theory in software design. Interests include machine learning, approximation algorithms, on-line algorithms and planning systems. Calvin, William H. – Theoretical neurophysiologist and author of "The Cerebral Code", and "How Brains Think". Gesture and narrative language, animated agents, intonation, facial expression, computer vision. Intersection of computer science and game theory, computer science and economics, multiagent systems, automated negotiation and contracting.

Japan's leading P&C insurance company, Sompo Japan Nipponkoa, improved their customer call centers with AI speech recognition technology. The insurance company chose NTT Communications' ForeSight Voice Mining System for their advisor support platform. The technology uses NTT Group's voice mining system and the corevo AI engine to transcribe audio-to-text conversations and pull up relevant FAQs to help advisors assist customers. See how the system helped Sompo Japan Nipponkoa cut assistance time by one third. Learn how NTT Communications' technology can ensure better customer service for your business.

Nintendo's NES mini console was an instant hit when it hit the market last year – selling around 1.5 million units right out the gate - until the firm mysteriously stopped production. Now, it is believed the gaming company is set to follow up with another console with the hopes of recreating the same success. The SNES mini is set to launch around Christmas this year, which is believed to be designed with better software and catalog of games more advanced than its predecessor. The SNES, known as the Super Famicon in Japan, was Nintendo's 16-bit followup to its hugely popular NES console. The system came with a host of popular games, including Street Fighter 2, Chrono Trigger, Super Mario World, and the Legend of Zelda: A Link to the Past.

The analysis in Part I revealed interesting properties for subgradient learning algorithms in the context of stochastic optimization when gradient noise is present. These algorithms are used when the risk functions are non-smooth and involve non-differentiable components. They have been long recognized as being slow converging methods. However, it was revealed in Part I that the rate of convergence becomes linear for stochastic optimization problems, with the error iterate converging at an exponential rate $\alpha^i$ to within an $O(\mu)-$neighborhood of the optimizer, for some $\alpha \in (0,1)$ and small step-size $\mu$. The conclusion was established under weaker assumptions than the prior literature and, moreover, several important problems (such as LASSO, SVM, and Total Variation) were shown to satisfy these weaker assumptions automatically (but not the previously used conditions from the literature). These results revealed that sub-gradient learning methods have more favorable behavior than originally thought when used to enable continuous adaptation and learning. The results of Part I were exclusive to single-agent adaptation. The purpose of the current Part II is to examine the implications of these discoveries when a collection of networked agents employs subgradient learning as their cooperative mechanism. The analysis will show that, despite the coupled dynamics that arises in a networked scenario, the agents are still able to attain linear convergence in the stochastic case; they are also able to reach agreement within $O(\mu)$ of the optimizer.

Spectral dimensionality reduction algorithms are widely used in numerous domains, including for recognition, segmentation, tracking and visualization. However, despite their popularity, these algorithms suffer from a major limitation known as the "repeated Eigen-directions" phenomenon. That is, many of the embedding coordinates they produce typically capture the same direction along the data manifold. This leads to redundant and inefficient representations that do not reveal the true intrinsic dimensionality of the data. In this paper, we propose a general method for avoiding redundancy in spectral algorithms. Our approach relies on replacing the orthogonality constraints underlying those methods by unpredictability constraints. Specifically, we require that each embedding coordinate be unpredictable (in the statistical sense) from all previous ones. We prove that these constraints necessarily prevent redundancy, and provide a simple technique to incorporate them into existing methods. As we illustrate on challenging high-dimensional scenarios, our approach produces significantly more informative and compact representations, which improve visualization and classification tasks.

As American soldiers were being maimed by roadside bombs in Iraq and Afghanistan, the U.S. military was working feverishly on a solution. One problem: It wasted nearly a decade developing one that was available off the shelf in Israel, a staunch U.S. ally. "That's just one anecdote of the kind of parochialism that's been the case at the Pentagon. That mentality, that mindset needs to change," said Ken Weinstein, president and CEO of the Hudson Institute, a Washington think tank on international affairs and technology. More collaboration with foreign partners is needed, but that might be easier said than done, Dr. Weinstein said during a trip to Atlanta to speak at the annual AmCham Germany Business Day event organized by BridgehouseLaw at the Porsche Experience Center.

Virgin Media has announced an incredibly fast new broadband tier for small- and medium-sized enterprises. Voom Fibre, which will be available from 2 May, promises download speeds of up to 350Mbps as standard. Virgin Media says that's four times faster than anything offered by its rivals. Business customers will be able to choose between three different packages, which start at £30 per month. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph.

Chinese PC maker Lenovo plans to pour over US$ 1.2 billion into artificial intelligence, Internet of Things and big data in the next four years, as part of its efforts to diversify their operations amid the stalled growth of its PC and smartphone business, local media is reporting (in Chinese). Lenovo CEO Yang Yuanqing said the annual investment in the above three areas will represent over one-fifth of the company's total annual R&D expenditure by March 2021. Lenovo remained the top PC vendor in the first quarter of 2017, garnering a 19.9% share in the global market by shipping 12.377 million units, IT research firm Gartner noted. Yet its rival HP has narrowed Lenovo's lead with shipments of 12.118 million. Among the company's three main lines of business, namely data centers, mobile devices, and PCs and smart devices (PCSD), revenue from PCSD business accounted for around 70% of its total revenue for the three months ended Dec. 31, 2016, according to the firm's Q3 FY 2016/17 results released this February.