Sports analytics is routinely used to assign values to such things as shots taken or to compare player performance, but a new automated method based on deep learning techniques - developed by researchers at Disney Research, California Institute of Technology and STATS, a supplier of sports data - will provide coaches and teams with a quicker tool to help assess defensive athletic performance in any game situation. The innovative method analyzes detailed game data on player and ball positions to create models, or "ghosts," of how a typical player in a league or on another team would behave when an opponent is on the attack. It is then possible to visually compare what a team's players actually did during a defensive play versus what the ghost players would have done. "With the innovation of data-driven ghosting, we can now, for the first time, scalably quantify, analyze and compare detailed defensive behavior," said Peter Carr, research scientist at Disney Research. "Despite what skeptics might say, you can indeed measure defense."

Google's cryostats reach temperatures of 10 millikelvin to run its quantum processors. From aspects of quantum entanglement to chemical reactions with large molecules, many features of the world cannot be described efficiently with conventional computers based on binary logic. The solution, as physicist Richard Feynman realized three decades ago1, is to use quantum processors that adopt a blend of classical states simultaneously, as matter does. Many technical hurdles must be overcome for such quantum machines to be practical, however. These include noise control and improving the fidelity of operations acting on the quantum states that encode the information.

Three years after its founding, Seattle's Allen Institute for Artificial Intelligence is racking up recognition in the field of AI research – and some of its research will have an impact on the burgeoning AI market. The institute, known as AI2, was founded by Microsoft co-founder Paul Allen in 2014 with longtime computer science researcher Oren Etzioni as its CEO. Since its founding, AI2 has spawned two spin-offs: Kitt.ai, which was created a little more than a year ago; and Xnor.ai, which made its debut this month. AI2 has built its workforce up to 75 people, which Etzioni says makes it the largest nonprofit AI research center in North America. Etzioni said the institute is sharpening its focus on the moonshot challenges that artificial intelligence can address.

H2O.ai, an AI company that provides industry-leading data products for enterprise businesses, today announced it has been named by Gartner, Inc., the leading provider of research and analysis on the global machine learning industry, as a Representative Provider of deep learning platform provider that allows users to create their own deep learning solutions. Gartner's January 2017 Innovation Insight for Deep Learning report listed H2O's Deep Water as one provider of deep learning platforms, placing it alongside other offerings from Caffe, Ersatz Labs, Facebook's Torch, Google TensorFlow, Intel's Nervana, The Microsoft Cognitive Toolkit, Theano and Skymind's Deeplearning4j. "We believe our inclusion in this report validates and enforces our standing in the industry," said SriSatish Ambati, co-founder and CEO of H2O.ai. "We're excited to continue expanding our suite of deep learning solutions." H2O.ai launched in 2011 with the goal of democratizing data science by open sourcing deep learning and AI for everyone.

C3 IoT updated its Internet of Things platform with more machine learning and artificial intelligence technology, integrated more with Amazon Web Services and has more than 100 million sensors and devices under management. The tech revolution is spreading to every corner of the earth with the Internet of Things, and it's enabling data analytics and automation in ways never before imagined in business. Version 7 of C3 IoT's platform will help the company expand into new verticals. As noted previously, C3 IoT initially gained traction with utilities and then moved into new verticals. Houman Behzadi, chief product officer at C3 IoT, said the company is actively working on implementations at oil and gas, health care, and financial services companies.

NVIDIA (NASDAQ:NVDA) was one of the hottest tech stocks of 2016, jumping 230% over the past 12 months. The company makes the vast majority of its revenue from gaming -- about 62% in the fiscal fourth quarter 2017 -- but NVIDIA is much more than just a a gaming processor company. The artificial intelligence (AI) market is quickly expanding and NVIDIA is positioning itself to make big gains in the space. According to an investor note published by Goldman Sachs' Toshiya Hari a couple of months ago, NVIDIA's total addressable market in AI and deep learning could be as big as $5 billion to $10 billion -- out of a total market of $40 billion. Hari mentioned that NVIDIA already has a lead in the AI space and that the company's competition "continues to face high barriers to entry."

As machine learning gains traction in digital businesses, technical professionals must explore and embrace it as a tool for creating competitive advantage. We discuss the benefits and pitfalls of machine learning, the requirements of its architecture, and how to get started.

If voice assistants really are the next big user interface, then Amazon is off to fantastic start -- by the numbers, at least. As this chart from Statista shows, Amazon's Alexa assistant now has more than 10,000 "skills" (i.e., third-party voice-enabled applications). That's double the amount that was available just last quarter. To be clear: That developers are interested in Alexa is good news for Amazon, and Alexa itself seems to be well ahead in the home compared to rivals like Google Assistant, the AI found in the Google Home speaker that competes directly with the Alexa-centric Amazon Echo. Calling up an Uber or ordering a pizza just by yelling across the room is convenient enough, but for every useful skill, there are 500 CorkOrnaments.com

Health Catalyst and the Regenstrief Institute are working together to commercialize nDepth, Regenstrief's natural language processing technology. Indianapolis-based Regenstrief developed the technology to harness unstructured data. Salt-Lake City-based Health Catalyst, a data warehousing and analytics company, has been in the business of extracting data to boost care quality since it launched in 2008. It was developed within the Indiana Health Information Exchange, the largest and oldest HIE in the country. Regenstrief fine-tuned nDepth through extensive and repeated use, searching more than 230 million text records from more than 17 million patients.

When it comes to public cloud-based IoT platforms, Amazon and Microsoft have fierce competition from an unexpected corner – IBM. While the company hasn't seen much traction with SoftLayer (IaaS), and Bluemix (PaaS), it's upping the ante on IoT and Cognitive Computing. IBM Watson is slowly but steadily gaining customer adoption. From Visa to BMW to Bosch to Kone, Watson now boasts of some impressive partnerships. IBM recently hosted a two-day briefing at its newly minted IoT facility in Munich.