Big Data + Powerful Hardware: The combination is essential to achieving higher levels of ADAS

Automated driver assist systems (ADAS) rely on intelligent software algorithms first and foremost. But without sufficient hardware, they’re going nowhere. System designers understand that aggregating data is merely step one to enabling autonomous capabilities. ADAS safety and success require the data accumulated be managed latency-free and in rigorous settings. To get there, designers must blend sophisticated software design and advanced hardware strategies.

Deep learning training and deep learning inference are data intensive processes vital to ADAS development. The former teaches the deep neural network to carry out AI tasks while the latter uses that training to predict what new and novel data means. But how are deep learning models trained and put to the test? And how integral are rugged hardware strategies to the process? Our article in Automotive World examines how ADAS development and innovation is reliant on such strategies to ensure passenger protection, observe road safety, and achieve superior vehicle performance.