In this episode of Embedded Insiders, Brandon and Rich review some of the highlights from the 2020 Consumer Electroncis Show (CES). Most notably, many embedded technology companies and organizations continue to embrace the world of open source, both within their product offerings and in the way they deliver products to market.

Later, Wensi Jin and Mark Corless of The MathWorks take the wheel as the discussion turns to simulation in the automotive sector.

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Every IoT device represents a potential vulnerability to complex systems of systems. Side-channel attacks can, of course, be devastating. And if an insecure connected device can reach a vulnerable cloud instance, well... the exploitation potential is exponential.

Jack Ogawa, senior director of embedded security at Cypress, introduces the company's PSoC 64 secure microcontrollers, which allow engineers to embedded unique and secure identities into IoT devices. He explains how, once a device's identity has been secured, IoT system architects can confer trust throughout their entire infrastructure.

To demonstrate this end-to-end security chain, Cypress is leveraging Arm's Pelion platform to establish trusted connections with the cloud.

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Neural networking is on the rise. So is the need to process these workloads. By default, this requires compute architectures that can efficiently compute neural network graphs. So, how do traditional CPU-, GPU-, and DSP-based solutions fare in this context?

According to representatives from Blaize (formerly Thinci), not well. Why? Because, among other things, their need to constantly access memory consumes significant time and energy. Dinakar Munagala, the ceo of Blaize, explains how the company?s graph streaming processor (GSP) architecture has been optimized for neural network applications like smart vision and autonomous driving.

Here, two demos of Blaize technology show how the company?s solution can be applied in autonomous driving and facial recognition use cases.

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Automotive engineering ain't what it used to be. Today's vehicles rely on inputs from high-resolution safety sensors distributed across multiple subsystems. Artificial intelligence (AI) is helping make safety-critical decisions. And all of this must occur in the context of control system designs that comply with industry and government standards.

At CES 2020, Tino Schulz of dSPACE provides an end-to-end view of how his company's simulation and validation solutions can accelerate automotive engineering in the face of increasing complexity. Through an open, collaborative ecosystem approach, automated driving technology are able to hit the road.

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With an increasing amount of electronic content in today's vehicles, automotive OEMs and their suppliers are in search of powerful-yet-flexible computing solutions that can meet the demands of body systems, infotainment and vehicle clusters, and even next-generation lighting. And do so, of course, at the lowest overall system cost.

Sven Natus of Cypress Semiconductor introduces the Traveo II line of microcontrollers at CES 2020, illustrating how secure firmware over-the-air (FOTA) update capability on the devices gives automakers the agility to meet the demands of vehicles today and for years to come.

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