Bravo
If ARM was an arm, BRN would be its biceps💪!
On the edge
The key to resolving these issues is embedding artificial intelligence (AI) into the devices themselves; this means imbuing the edge of networks with the intelligence needed to eliminate reliance solely on cloud networks or corporations to capture and interpret data. I’ve previously written about the artificial intelligence of things (AIoT) and the potential impact that edge technology could have, especially on the smart home.
In one fell swoop, AIoT can address privacy issues and energy consumption. Allowing devices to process commands without the need for external communication, or a necessity of cloud connectivity, keeps consumers’ personal information local and secure. It also releases the handbrake in performance terms, thereby encouraging consumers to transition from established brand favorites to new high–performance devices. Where energy consumption is concerned, AIoT’s local processing means that devices can transition from ‘always listening’ to ‘always ready’. Sensors will only be in use when needed, ensuring that demand for electricity isn’t continually high.
But electronics engineers will be aware of the challenges involved embedding AI within electronics. Doing so has traditionally been expensive because AI chips tend to only address high–end AI demands. Embedding AI within electronics is also complex because it often require a significant redesign of electronics.
The good news is that a new breed of chipset technology has finally hit the market designed specifically with the smart home in mind. These chips provide simple AI capabilities at a fraction of the cost of traditional AI chips, are flexible enough to embed within any smart home device and program to almost any smart home AI use case easily.
In this way, ambient sensing technology at the edge is finally becoming the future of the smart devices industry.
I thought XMOS was a competitor? This article from 2020 says that some of its strategic partners were Robert Bosch Venture Capital, Huawei, and Xilinx.

XMOS unveils Xcore.ai, a powerful chip designed for AI processing at the edge
Bristol-based XMOS' new AI chip is designed for high-performance, low-cost AI and machine learning workloads at the edge.