Artificial intelligence shortens the path to autonomy and brings the home into the car.
Slowly but surely, artificial intelligence (AI) is invading more and more markets, and thus each person’s daily movements. At home, AI innovations like “Ok, Google” and “Alexa” are like members of the family, and now these systems are entering automobiles too, which will soon drive you to work fully autonomously. In fact, autonomous driving and infotainment are the two main automotive segments where AI has a huge impact.
On the autonomy side, two trends move in parallel: on one hand, the classic original equipment manufacturer (OEM) with the addition of functionalities (including deep-learning algorithms for object recognition) that facilitate increased advanced driver-assistance system (ADAS) levels; and on the other hand, startups and tech giants offering services based on robotic vehicles, i.e. shuttles and robot taxis.
For infotainment, AI enters the fray with speech and gesture recognition technologies, where the same tech giants that support you at home will serve you in your car.
The march to automated driving is quickening with the infusion of investment capital, innovation in artificial intelligence and public expectations. However there are many challenges facing the industry – from a fragmented landscape to technology challenges. Willard Tu, senior director, automotive at Xilinx will discuss the need for adaptable silicon solutions in ADAS and next-generation autonomous vehicles (AV). He will also touch on four key areas of ADAS and AV development including:
- Artificial Intelligence: Computer Vision vs Neural Nets
- Compute: Distributed vs Centralized
- Sensing: Camera, Radar, LiDAR
- Processing Engines: CPU, DSP, FPGA, GPU
What are the stakes? Who are the main players and what is their ecosystem? How is the market structured? What is AI’s automotive future in terms of technology, market, forecast? Join Yole Développement and Xilinx’s webcast for a discussion of these questions, where we will challenge assumptions and gain a better understanding of AI computing market trends in automotive from several perspectives – including market & technology and competitive dynamics.
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