COMPANY NEWS AND INFORMATION
Syntiant: Overcoming the Challenges of Edge AI
Syntiant CEO Kurt Busch addresses three fundamental challenges for deploying edge AI.
At the Edge: AI performance Cannot be Tiny Anymore (Part 2 of 2)
In the first part of this series, we explored the challenges posed by the current approach to edge AI, such as scalability issues, escalating network and cloud costs, and the limitations of legacy processors. As the demand for smarter, faster, and more secure AI applications grows, it is becoming increasingly clear that edge AI cannot be tiny anymore. In this follow-up, we will discuss the reasons behind this shift and introduce Syntiant’s new NDP250 chip as a prime example of how advanced edge AI processors are addressing these challenges and making Edge AI a reality.
Why Edge AI for EV Battery Management
EVs are equipped with hundreds of sensors and controllers to measure and process tons of data. As the techniques to make data-driven decisions evolve, the e-mobility industry has taken advantage of Big Data and AI to operate, monitor, and optimize a crucial piece of the EV powertrain: the battery. This article explores how Edge AI can improve Battery Management System (BMS) performance and safety.
How Neural Architectures Leverage Duty Cycling for Massive Efficiencies
In this blog post, we will show how modelers can leverage the true power and throughput performance of edge neural accelerators to get the best task performance.
