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Welcome to the Drive World with ESC 2019 Presentation Store. Here you can view and download conference presentations before, during, and after the event. If you’re looking for a presentation from a specific session that you’re unable to find here, note that it’s likely because the presenter has not provided permission for external use or has not yet shared their presentation with us. Please check back after the event for a more complete catalogue of available presentations.

Artificial Intelligence: The Winter of Our Discontent or Mild Spring Frost?

Sky Matthews  (CTO, Internet of Things, IBM)

Location: Engineering Theater

Date: Thursday, August 29

Time: 12:15 pm - 1:00 pm

Track: Engineering Theater

Format: Technical Session

Vault Recording: TBD

Recents events and revelations of AI failures have brought out the detractors, along with commentaries that the early projections of AI for autonomous driving and other large scale intelligence challenges were overly optimistic ("AI's failure to live up to the hype is starting to put off investors", Mike Lynch, Wired UK Jan 2 2019; "Artificial Intelligence Hits the Barrier of Meaning", Melanie Mitchell, New York Times, Nov 2018). Some even suggest that AI will never be able to overcome the current limitations of deep learning and neural network based approaches. So are we looking at another pullback from AI as happened with the "AI Winter" in the 90s and 00s? Or is this merely a speed bump on the road to wider AI adoption and achievement? While there are bound to be failures and missed expectations, there are also many examples of successful AI implementations in use today. Understanding what is practical with today's AI technology is critical to successfully leveraging AI in automotive. This session will illustrate many of the practical examples of AI in production today. It will also discuss the potential for near-term AI success, highlight some of the recent trajectories for commercial AI systems, and also lay out some of the challenges ahead that need to be solved before AI tackles more complex problems and becomes more widespread.

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