IBM unveils their latest innovations and shows us how Watson helps the U.S. Open Sara Snyder, USA TODAY NEW YORK--The computer that famously became a Jeopardy champ a few years ago isn't about to take on top seeded tennis superstar Serena Williams. But off the court, IBM Watson is making its presence felt at the Billie Jean King National Tennis Center in Flushing Meadows, Queens, home to the U.S. Open Tennis Championships that began this week. IBM has collaborated with the United State Tennis Association on technology for more than a quarter-century, but Watson, IBM's self-proclaimed cognitive computer, is a newbie at the Open. IBM is leveraging Watson's machine learning smarts and cloud-based analytics to try and bolster the fan experience during the tournament--while simultaneously raising Watson's profile. IBM of course is not the only company with a vested interest in artificial intelligence, and the field has become a hotbed of activity. Google, Microsoft, Facebook and others, have planted major stakes in the ground.

"All hands on deck" may become a thing of the past. Ship designers, their operators and regulators are gearing up for a future in which cargo vessels sail the oceans with minimal or even no crew. Advances in automation and ample bandwidth even far offshore could herald the biggest change in shipping since diesel engines replaced steam. Ship operators believe more automation will enable them to optimize ship use, including cutting fuel consumption. "The benefit of automation is as an enabler of further efficiency across the 630 vessels we operate," said Palle Laursen, head of Maersk Line Ship Management, a unit of cargo-ship giant A.P. Moeller-Maersk AMKBY 0.00 % A/S.

After months of cancer treatment at the University of Tokyo Hospital, the patient – a woman in her 60s – was not getting much better. So the medical team plugged the woman's symptoms into IBM's Watson, the supercomputer that once famously trounced human champs in the TV quiz show Jeopardy! Watson rifled through its storehouse of oncology data and announced that she had a rare form of secondary leukemia. The team changed the treatment, and she was soon out of hospital. Watson spotted in minutes what could otherwise have taken weeks to diagnose, one doctor told The Japan Times. "It might be an exaggeration to say AI saved her life, but it surely gave us the data we needed in an extremely speedy fashion."

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This is a program for a general feedforward neural network and is intended for educational purposes. It is simple and short, making it easy for a reader to quickly get into the details of how a neural network can be implemented. NeuralNet2.ipynb contains the code for the neural network, the rest of the .ipynb This code accompanies a set of tutorials on neural networks, including a walkthrough of the NeuralNet2.ipynb, NeuralNet2.ipynb is a vectorized implementation of a general feedforward neural network in Python Two example applications are provided.

This article is featured in the new DZone Guide to Big Data Processing, Volume III. Get your free copy for more insightful articles, industry statistics, and more. In the past few decades, computer systems have achieved a whole lot. They have managed to organize and catalog the information produced by our civilization as a whole. They have relieved us from stringent cognitive tasks and increased our productivity significantly. One could say that where the industrial revolution automated labor, the digital revolution has automated cognitive labor. This statement isn't entirely correct however, if it was we would all be without a job.

Hewlett Packard Enterprise Co. (HPE) has updated its Vertica analytics suite while introducing new machine learning capabilities to Haven OnDemand. Vertica is software that analyzes structured data, for example information that's stored in rows and fields. But with the new update, Vertica 8, codenamed "Frontloader", HPE has introduced a unified architecture as well as in-database analytics capabilities. According to HPE, Vertica 8 has been designed to help customers extract intelligence from data that resides in multiple silos throughout the data center, be it on-premises, in private and public clouds, or in Hadoop data lakes. Meanwhile, Vertica's new in-database machine learning algorithms enable users to create and deploy R-based machine learning models directly inside the software.

Microsoft is working with Liebherr's appliance division to rebuild the refrigerator and make it smarter, faster, strong; well, maybe just smarter. The new collaboration between the two will see Microsoft provide computer vision technology, via its Microsoft Cognitive Services Computer Vision API, to let the fridge identify objects contained within. Why would you want a fridge that knows what it's holding? It'll save you those extra return trips to the grocery store for things you forgot, for one. The deep learning algorithms in use will be able to learn new food types based on its experience from processing millions of generic food packaging images, and it should be able to get smarter very quickly while in use when and if it eventually comes to market, using data gathered from a wide pool of real-world users. Other fridges have the ability to let you peer inside remotely, but Microsoft's data science team worked directly with Liebherr on this prototype to make a learning fridge that won't force you to rely on your pathetic human eyes looking at a grainy image over a poor cellular connection to roll the dice while shopping.

The Seattle tech titan hired eBay's head of artificial intelligence, Hassan Sawaf, to lead its own A.I. operation in Palo Alto, Calif. Sawaf is now Director of Artificial Intelligence at Amazon-owned A9 Labs, the Wall Street Journal reports. Poaching Sawaf from rival eBay is the latest in a series of moves this week that indicate Amazon is doubling down on A.I. The company just acquired a machine learning team in Cambridge, UK and used some of the 100 million Amazon Alexa fund to invest in natural language processing startup DefinedCrowd. In 2012, Jeff Bezos provided 2 million to fund machine learning professorships for Turi CEO Carlos Guestrin and his wife, Emily Fox at the University of Washington.