Just on Infineon.
Whilst this older paper (2022) doesn't mention Akida, I have highlighted one of their statements re neuromorphic AI in autonomous driving which I found encouraging. The 2 chips mentioned are still research chips.
I included where the authors worked or were aligned with. Some familiar names there, though Valeo wasn't represented, BMW & Infineon were.Automotive Radar Processing With Spiking Neural Networks: Concepts and Challenges
Frequency-modulated continuous wave radar sensors play an essential role for assisted and autonomous driving as they are robust under all weather and light conditions. However, the rising number of transmitters and receivers for obtaining a higher angular resolution increases the cost for...www.frontiersin.orgORIGINAL RESEARCH article
Front. Neurosci., 01 April 2022
Sec. Neuromorphic Engineering
Volume 16 - 2022 | https://doi.org/10.3389/fnins.2022.851774Automotive Radar Processing With Spiking Neural Networks: Concepts and Challenges
- 1Chair of Highly-Parallel VLSI-Systems and Neuro-Microelectronics, Faculty of Electrical and Computer Engineering, Institute of Principles of Electrical and Electronic Engineering, Technische Universität Dresden, Dresden, Germany
- 2Infineon Technologies Dresden GmbH & Co., KG, Dresden, Germany
- 3Department of Informatics, Technical University of Munich, Munich, Germany
- 4Infineon Technologies AG, Munich, Germany
- 5BMW Group, Research, New Technologies, Garching, Germany
- 6Centre for Tactile Internet (CeTI) With Human-In-The-Loop, Cluster of Excellence, Technische Universität Dresden, Dresden, Germany
When it comes to AI-based autonomous driving, ensuring functional safety of both software and hardware is a critical issue. The principles that are currently developed to support machine learning models (Henriksson et al., 2018; Mohseni et al., 2019) will also apply to SNNs. Similarly, neuromorphic hardware will have to fulfill the same standards as any automotive electronic system: adhere to temperature ranges, be resistant to vibrations, be deterministic and redundant, or contain self-monitoring. For that reason, only digital neuromorphic systems are candidates for integration in cars, while the use of analog or mixed-signal neuromorphic hardware seems out of scope at the moment due to their intrinsic variability. Hence, we suggest to focus on advanced digital systems such as SpiNNaker2 (Yan et al., 2021) or Loihi2 (Orchard et al., 2021) to further explore neuromorphic hardware for automotive radar processing and automated driving in general
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