Machine Learning for Embedded Edge Applications

IEEE TEMS Santa Clara Valley / San Francisco / Oakland-East Bay Joint Chapter

IEEE Technology & Engineering Management Soc.- SCV

... what are the market requirements, customer use cases and key challenges ... and how to address the needs of this market.

Abstract: AI/ML is an all-pervasive technology that has the potential to transform our lives. It has use cases from Internet of Things (IoT) to edge devices to automotive to cloud. This presentation discusses how AI is disrupting traditional embedded edge market including surveillance, robotics, industrial automation, aerospace and defense applications. We will cover market requirements, customer use cases and key challenges. In addition, we will also discuss how next generation of purpose-built products are addressing the needs of this market.For more details: See <a href="https://r6.ieee.org/scv-tems/kodaks-journey-in-digital-photography-an-insiders-perspectives/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">http://techmanagers.org/</a> Speaker Bio: <a href="https://www.linkedin.com/in/gohegde/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Gopal Hegde</a> has over 30 years of experience in engineering and business leadership positions at startups and large public companies, including Cavium (acquired by Marvell), Calxeda, Cisco, Intel, and Acclaim Communications (acquired by Level One/Intel). He is a highly technical, results-oriented leader with a stellar track record in developing world-class products and increasing revenues to $100M+ while incubating new and scaling existing products. Currently he leads engineering and operations at <a href="https://sima.ai/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">SiMa.ai</a>. Under his leadership, SiMa.ai has launched their highly innovative machine learning SoC (MLSoC™) along with the Palette™ software that enables effortless machine learning for embedded edge applications. Hegde holds a master of science in electrical and computer engineering from the University of Massachusetts Amherst.

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Machine Learning for Embedded Edge Applications

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