There are not many books on Deep Learning at the moment because it is such a young area of study.

Embedded Python/NumPy/Scikit-learn functions in MonetDB to perform machine-learning tasks on a real business case.

The project, which is being done with Sweetwater Tech Resources, utilizes Water Planet's IMS-5000 Integrated Produced Water Treatment Solution powered by IntelliFlux. The IMS-5000 technology used in the pilot is an integrated mechanical and membrane filtration system that incorporates ceramic membranes to filter the water. It was developed to perform in oil & gas produced water treatment, one of the most challenging water treatment applications on the planet. As part of the project, Water Planet is also running a standard reverse osmosis unit to desalt the brackish water that is left after treatment by the ceramic ultrafiltration membranes. "We are currently running a series of demonstrations using a range of waters provided by a consortium of California oil producers to evaluate treating produced water for potential use in agricultural irrigation.

Aliyun, the cloud computing unit of Alibaba Group Holding, on Wednesday officially introduced an artificial intelligence (AI) robot named Ai that's meant to compete with overseas AI players. The Ai system was developed on the basis of neural networks and social computing, according to a press release Alibaba sent to the Global Times on Wednesday. The Ai system is good at predicting and understanding human emotions, the company said. Neural networks are based on animals' central nervous systems, and they are used to mimic functions involving many inputs. Social computing can be defined as the intersection of social behavior and computing systems.

The threat from such machines is real enough for 100 states to come together and debate the matter of their ban for three consecutive years now. The use of autonomous machines could potentially change the vocabulary of warfare, just like gun powder and nuclear arsenal upon their entry into the battlefield. In April 2013, NGOs associated with successful efforts to ban landmines and cluster munitions got together in London and issued a call to governments urging the negotiation of a treaty preventing the development, deployment and use of what are known as'Killer Robots' in popular parlance. In July 2015, some of the world's leading Artificial Intelligence (AI) scientists including Apple co-founder Steven Wozniak, Skype co-founder Jaan Tallin and Professor Stephen Hawking signed a letter with nearly 21,000 signatures asking for an outright ban on these autonomous weapons systems (AWS). "Autonomous weapons will become the Kalashnikovs of tomorrow," states the letter.

This paper tackles the problem of endogenous link prediction for knowledge base completion. Knowledge bases can be represented as directed graphs whose nodes correspond to entities and edges to relationships. Previous attempts either consist of powerful systems with high capacity to model complex connectivity patterns, which unfortunately usually end up overfitting on rare relationships, or in approaches that trade capacity for simplicity in order to fairly model all relationships, frequent or not. In this paper, we propose Tatec, a happy medium obtained by complementing a high-capacity model with a simpler one, both pre-trained separately and then combined. We present several variants of this model with different kinds of regularization and combination strategies and show that this approach outperforms existing methods on different types of relationships by achieving state-of-the-art results on four benchmarks of the literature.

Over the past week much has been made about the launch and (temporary) shutdown of Microsoft's chatbot Tay. For those of you who might not know, Tay is a machine learning project that was launched with the goal of conducting research and development in the field of conversational understanding. It's a bot that can chat with users online, and it has presence over several platforms, including Twitter, GroupMe and Kik. Tay is programmed to mimic the behavior of a young woman, tell jokes and offer comments on pictures, but she's also designed to repeat after users and learn from them in order to respond in personalized ways. Unfortunately, Tay was shut down shortly after her launch because she was found to make racist and offensive comments. Apparently, the quirks in the bot's behavior were capitalized by a subset of users to promote Nazism and attack other Twitter users.

Welcome to California Inc., the weekly newsletter of the L.A. Times Business Section. Expect financial markets to face headwinds today after the Federal Reserve reported Friday that U.S. industrial production fell more than expected in March. This is the latest sign that economic growth slowed significantly in the first quarter. On the plus side, though, many economists still forecast a rebound in growth as the year plods ahead. Tax deadline: Monday is the deadline for most Americans to submit their tax returns.

Oracle Corp. has acquired Israeli machine-learning Big Data startup Crosswise, Inc. The price of the acquisition was not officially disclosed but is believed to be 50 million according to local media. Founded in 2013, Crosswise provides an authoritative consumer device map to ad tech vendors, consumer brands, and premium publishers. The company's platform combines data science, Big Data and machine learning, to identify which PCs, phones, tablets, digital TVs and other connected devices are being used by individual consumers; by applying advanced data science and proprietary machine-learning techniques to this data, Crosswise constructs a new probabilistic Device Map matching multiple devices to individual users in an accurate, scalable and high-quality manner. According to Crosswise, the benefits in being able to provide this data is that it allows marketers and premium publishers to deliver advertising, personalization and analytics across different sorts of devices.

David Ledbetter, data scientist at the Children's Hospital Los Angeles, shares how his team is using TITAN X GPUs and deep learning to help provide better recommendations of drug treatments for children in their pediatric intensive care unit. To train their models, 13,000 patient snapshots were created from ten years of electronic health records at the hospital to understand the interactions between a patient's vital state, heart rate, blood pressure and the treatments they were given. By understanding the most important relationships in the data, they are then able to generate the probability of survival predictions for the patients moving forward as well as physiology predictions in order to simulate augmented treatments. David presented his research poster "Dr. Watch more scientists and researchers share how accelerated computing is benefiting their work at http://nvda.ly/X7WpH