At Siemens Corporate Technology in Princeton, New Jersey and Berkeley, California, scientists and researchers are working on the future of robotics and automation.
MetLife Japan, today launched “collab 4.0,” an open innovation platform inviting entrepreneurs and insurtechs globally to scale their business with MetLife while solving some of the insurer’s biggest innovation challenges across its Japan business.
Wysdom.AI, the most mature full-stack cognitive care platform for automating customer journey management, announced today their partnership with the Vector Institute for artificial intelligence (AI) to solve industry challenges and share research around the adoption of AI in the enterprise.
CloudMedx, a healthcare artificial intelligence company based in Palo Alto, Calif., announced today a research collaboration with the UCSF Department of Orthopaedic Surgery to study how patient-generated health care data collected from consumer-grade wearable sensors may predict clinical outcomes following hip and knee replacement surgery.
The "AI Chipsets for Wireless Networks and Devices, Cloud and Next Generation Computing, IoT, and Big Data Analytics 2018 - 2023" report has been added to ResearchAndMarkets.com's offering.
Thailand's robotics and automation industry is anticipated to expand significantly in the coming years, and the Thailand Board of Investment is making a concerted effort to support robotics companies that establish operations in the country by making them eligible to benefit from the Kingdom's new Eastern Economic Corridor scheme.
Gumstix, Inc., the leader in design-to-order embedded systems, announces the release of the Aerocore 2 for NVIDIA Jetson board and NVIDIA Jetson TX(1/2/2i) COM Connector in Geppetto.
Amateur and professional musicians alike may spend hours pouring over YouTube clips to figure out exactly how to play certain parts of their favorite songs. But what if there were a way to play a video and isolate the only instrument you wanted to hear?
Baidu Inc. today announced Kunlun, China’s first cloud-to-edge AI chip, built to accommodate high performance requirements of a wide variety of AI scenarios. The announcement includes training chip “818-300”and inference chip “818-100”. Kunlun can be applied to both cloud and edge scenarios, such as data centers, public clouds and autonomous vehicles.
When the word "manufacturing" is mentioned, the image of automotive assembly lines bristling with robots often comes to mind. Few industrial processes embody the intricacies of modern manufacturing better than automated vehicle assembly plants. It is therefore hardly surprising that these facilities are implementing AI technology.
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