New memory types compete to replace conventional memories | SK Telecom turns to Xilinx FPGAs for data center AI acceleration | Intel acquires deep-learning specialist Vertex.AI
August 17, 2018
JEDEC SmartBrief
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Today's Tech Buzz
New memory types compete to replace conventional memories
Carbon nanotube random access memory, phase-change memory and ferroelectric RAM are among the next-generation memory technologies that could replace conventional memory types in the future. However, many new memory types are expensive and "rely on exotic materials and switching mechanisms, making them difficult to fabricate and/or operate in the field," Mark Lapedus writes.
Semiconductor Engineering (8/16) 
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ICs, Memory & More
SK Telecom turns to Xilinx FPGAs for data center AI acceleration
SK Telecom has chosen Xilinx field-programmable gate arrays to supply artificial intelligence acceleration for its automatic speech-recognition application. The use of Xilinx FPGAs has improved performance by up to five times while delivering 16 times better per-watt performance, according to SK Telecom.
New Electronics (8/16) 
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Intel acquires deep-learning specialist Vertex.AI
Intel is extending its work on artificial intelligence with the acquisition of Vertex.AI, a startup focusing on the development of "deep learning for every platform." Intel said it will be putting to work Vertex's entire team and intellectual property "to further enable flexible deep learning at the edge."
TechCrunch (8/16) 
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Going Green
Corporations worldwide embracing clean energy
Corporations are purchasing record amounts of clean energy worldwide, and long-term contracts in place indicate the trend will continue. The 7.2 gigawatts of clean energy purchased by corporations worldwide in the first seven months of 2018 already exceeds 2017's full-year record of 5.4 GW, according to Bloomberg NEF.
Bloomberg Professional Services (8/15) 
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Semiconductors in Action
AVSdsp, researchers create Mipy AI chip
AVSdsp has teamed with electrical engineering professors from National Taiwan Normal University to develop the Mipy chip, an artificial intelligence processor that is said to represent the smallest size and lowest cost on the AI market. The deep-learning image recognition AI chip's low cost makes it a good fit for applications such as home products, automotive products, toys and industrial equipment.
DigiTimes (8/17) 
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Testing & Standards
Unpatterned wafer inspections grow in difficulty, cost
It's becoming more difficult to find defects in unpatterned wafers due to shrinking critical dimensions, writes Mark Lapedus. "Increasing requirements to detect and classify defects like pits and slip lines add challenges and complexity to the inspection process," said Felix Moellmann of Rudolph Technologies Systems.
Semiconductor Engineering (8/16) 
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JEDEC publishes JEP155B: Recommended ESD Target Levels for HBM/MM Qualification
JEP155B was written with the intent to provide information for quality organizations in both semiconductor companies and their customers to assess and make decisions on safe ESD level requirements. For more information and to download the publication, visit the JEDEC website.
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