Lutron announced today that its Caséta wireless lighting systems are now compatible with Amazon's Alexa voice-control system, enabling owners of Amazon's Echo, Echo Dot, Amazon Tap, or Amazon Fire TV to control Caséta-connected lighting fixtures with voice commands. "Caséta users who also own Alexa-capable devices can now dim, brighten, and control individual lights or groups of lights using their voice," Lutron product manager Neil Orchowski said in an embargoed briefing last week. Lutron's Caséta Wireless Smart Bridge and Caséta Wireless Smart Bridge Pro can control up to 50 Caséta lighting-control devices, using Lutron's proprietary Clear Connect technology. The company's Caséta Wireless Smart Bridge Pro is also compatible with Apple's HomeKit platform, and the company has partnered with Nest (participating in the Works With Nest program), Comcast (it can be integrated into Xfinity Home systems), and several smart thermostat manufacturers (including Honeywell, Carrier, and Ecobee). The Caséta line also includes in-wall switches and dimmers.

Shares of graphics chip maker Nvidia (NVDA) are down 6 cents at 35.69, following yesterday's annual meeting with analysts. A webcast replay of presentations CEO Jen-Hsun Huang and other executives, and the Q&A, can be viewed from the company's investor relations page. Huang made the pitch that with new frontiers of machine learning and artificial intelligence, Nvidia "are no longer a co-processor," meaning a handmaid to the PC microprocessor. "There is no workload we run," said Huang, such as a video game. Instead, he said, with the company's programming technology, "CUDA," "we run an application that a developer writes on top of it."

Channel Mark Ventures announced today that it will be launching Inteladesk through their technology development and sales company CenturySoft Ltd. This next generation customer helpdesk management solution is powered by a revolutionary artificial intelligence (AI) platform. "Inteladesk's AI-based engagement solution is the ideal complement to our insight-driven approach of sales acceleration for our clients at their specific domain level," said Dan O'Shea, CEO at Channel Mark Ventures. In discussing their Inteladesk product O'Shea explained that "Inteladesk essentially drives a personalized sales experience. Inteladesk helps companies perfect their knowledge base by explaining misstep queries or missed opportunities to improve FAQs. Combined with the technology, Inteladesk users will have the ability to reduce incoming customer service emails and calls. With Inteladesk at work, new processes will emerge as the technology helps companies introduce new service enriching CRM processes not previously possible or financially feasible. In turn, employees can take on higher-level roles to formulate new ways to enrich customer service. We are beyond thrilled at the prospects here. There is nothing like it available on the market today. The Live Agent learns as it works and provides high-quality responses consistently, every day of the year, in every language your customers speak. Cognitive Code's technology is truly game-changing."

Isabel Dedring, Deputy Mayor, Transport at Greater London Authority will be a keynote speaker at the event of 28th June, hosted at The House of Lords. Dedring will explore how policies have to change in order for cities to be able to adapt to these changes in an ideal way. To download the brochure and to attend the Intelligent Mobility event, please visit http://frost.ly/78. The two major concerns connected to cars are accidents and pollution – which will be significantly reduced or even eliminated, once electric vehicles and autonomous driving work together. AI enabled automated driving also has the potential to eliminate traffic jams, as Frost & Sullivan Senior Partner Sarwant Singh explains: "Today, when you are caught in a traffic jam, it is already too late. In future, AI combined with data analytics could predict a traffic jam, avoiding not only you getting into the traffic jam but preventing congestion in the first place."

SAN JOSE, Calif.?Nvidia Corp. is stepping up plans to expand beyond computer graphics into the field of artificial intelligence, unveiling an unusual processor for the purpose and a computer that uses it to solve scientific problems at extremely high speed. The company on Tuesday said the new Tesla P100 chip, designed for use in corporate data centers, achieves very high performance by packing 15 billion transistors on a piece of silicon. That is roughly twice as many as Nvidia's prior high-end graphics processor and some new server chips Intel Corp. announced last week. "It's the largest chip that has ever been made," said Jen-Hsun Huang, Nvidia's chief executive, during a speech kicking off the company's annual technology conference here. He predicted the chip would initially be purchased by unidentified cloud computing services and next year would begin arrive in servers sold by other companies.

SAN JOSE, CA--(Marketwired - Apr 5, 2016) - GPU Technology Conference -- NVIDIA (NASDAQ: NVDA) today announced that it is a founding technology partner of the MGH Clinical Data Science Center, which aims to advance healthcare by applying the latest artificial intelligence techniques to improve the detection, diagnosis, treatment and management of diseases. Massachusetts General Hospital -- which conducts the largest hospital-based research program in the United States, and is the top-ranked hospital on this year's US News and World Report "Best Hospitals" list -- recently established the MGH Clinical Data Science Center in Boston. The center will train a deep neural network using Mass General's vast stores of phenotypic, genetics and imaging data. The hospital has a database containing some 10 billion medical images. To process this massive amount of data, the center will deploy the NVIDIA DGX-1 -- a server designed for AI applications, launched earlier today at the GPU Technology Conference -- and deep learning algorithms created by NVIDIA engineers and Mass General data scientists.

Nvidia's fastest GPU yet, the new Tesla P100, will be available in servers next year, the company said. Dell, Hewlett Packard Enterprise, Cray and IBM will start taking orders for servers with the Tesla P100 in the fourth quarter of this year, Nvidia CEO Jen-Hsun Huang said during a keynote at the GPU Technology Conference in San Jose, California. The servers will start shipping in the first quarter of next year, Huang said Tuesday. The GPU will also ship to companies designing hyperscale servers in-house and then to outsourced manufacturing shops. It will be available for in-house "cloud servers" by the end of the year, Huang said.

Nvidia's varied range of GPU developer tools have been spread out into specialized kits, but that's not the case any more. The company has announced the Nvidia SDK unified toolkit, which brings together its game development, supercomputing, virtual reality, automotive and drone and robot development tools into one package. The toolkit brings together essential tools and libraries necessary for GPU development, Jen-Hsun Huang, CEO of Nvidia, said during a keynote at the company's GPU Technology Conference in San Jose, California. The toolkit is tuned for Nvidia's latest Pascal GPU architecture, which the company is expected to detail at the show. Pascal contains many technological improvements that could trigger changes in the way applications are written for GPUs.

Google has announced plans to open its machine-learning software to developers. The multinational tech company is hoping this will attract more companies to its cloud-computing services, which already includes image identification, voice recognition and AI technology. The market for cloud-computing services is a competitive one, with Microsoft, Amazon and IBM offering similar products. While modern cloud systems are based on "decades-old" technology, Google said, the company's forthcoming products and services are designed for the next wave of cloud computing. And Google is already a leader in AI, using the technology to support its web-based services and apps.

Whether we realize it or not, machine learning is already a part of our everyday lives. Think about a simple Google search, a quick query to Apple's Siri, an afternoon visit to Facebook, or, of course, a great product recommendation on Amazon. As the prevalence of high-performance computing continues to grow, the thought of computers doing things we could only dream of is exhilarating and, for many, almost magical. This is especially true when it comes to marketing. Yet, as we apply machine learning to marketing and unique business goals, oftentimes all of that mystery and intrigue turn to disillusion and struggle with the practical applications.