Dedicated accelerator hardware for artificial intelligence and machine learning algorithms are increasingly prevalent in data centers and endpoint devices. These accelerators handle important data which has value and must be protected. Many security threats exist that can compromise these assets. Fortunately, there are security techniques which can mitigate these threats.

Part 1 of this webinar series will answer the following questions:

  • How is the growing complexity of electronic systems lowering their security?
  • What are typical architectures of edge and data center AI devices?
  • What are threat models and how can they be used in scoping security risks?
  • What are the security threats to AI/ML accelerators?

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Watch more in the Implementing Strong Security for AI/ML Accelerators series:

Part Two
Part Three