Industrial AI & Machine Lear1ing
 
Five Minutes With?Steen Graham, GM, IoT Ecosystem, Intel
RICH NASS, EMBEDDED COMPUTING DESIGN
The IoT is just starting to embrace AI and neural nets. While previously a Cloud-based application, such algorithms are migrating to the Edge, thanks to the latest and greatest microprocessors. One of those processor vendors who continue to exhibit expertise in the IoT ecosystem is Intel, and as such, became the subject of this week?s Five Minutes with ? discussion.
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SiFive, a provider of RISC-V core IP, recently announced its Freedom Aware (FA) family of SoC templates as well as a strategic development partnership with QuickLogic. The FA SoC templates, which focus on intelligent processors targeting Edge and end-point applications, potentially lowers the cost and development time associated with new SoC designs.
 
 
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If you were waiting for AI enhancements to MATLAB and Simulink, your wait is over. Mathworks recently released version 2019a of its popular software. According to the company, with R2019a, engineers can extend their AI skills to develop controllers and decision-making systems using reinforcement learning, training deep learning models on NVIDIA DGX and cloud platforms, or applying deep learning to 3D data.
 
 
 
 
 
 
Offer superior performance, high input bandwidths, and integrated signal processing.
 
 
 
 
 
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TrulyNatural categorizes speech into unlimited intents and entities, allowing the natural language understanding component to interpret any speech natively without the need for scripted grammar.
 
 
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The Snapdragon 855 Mobile HDK is an open-frame solution based on an Android 9 operating system that delivers CPU, GPU, and DSP compute for local artificial intelligence (AI) applications.
 
 
 
 
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AAEON and Intel joined forces on the product of the Second Generation Intel Xeon Scalable Processors to ensure a powerful platform was built to satisfy the high-data high performance demands of AIOT Edge networks, the FWS-8600 network appliance.
 
 
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A machine learning core in the sensor works with integrated finite-state machine logic to classify motion data based on known patterns. By offloading these functions from a host processor, motion-based apps can be accelerated and energy conserved.
 
 
 
 
 
 
Sponsored by: FogHorn Systems, QuickLogic
Date: May 14, 2:00 p.m. ET
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