Has anyone else stumbled upon this 3 year EU-funded research project called Nimble AI, kick-started in November 2022, that “aims to unlock the potential of neuromorphic vision?“ Couldn’t find anything here on TSE with the help of the search function except a reference to US-based company Nimble Robotics, but they seem totally unrelated.
The 19 project partners include imec in Leuven (Belgium) as well as Paris-based GrAI Matter Labs, highly likely Brainchip’s most serious competitor, according to other posters.
An article about Nimble AI’s ambitious project was published today:
What do you make of of the consortium’s claim that their 3D neuromorphic vision chip will have more than an edge over Akida once it will be ready to hit the market?
Today only very light AI processing tasks are executed in ubiquitous IoT endpoint devices, where sensor data are generated and access to energy is usually constrained. However, this approach is not scalable and results in high penalties in terms of security, privacy, cost, energy consumption, and...
www.hipeac.net
NimbleAI: Ultra-Energy Efficient and Secure Neuromorphic Sensing and Processing at the Endpoint
“Today only very light AI processing tasks are executed in ubiquitous IoT endpoint devices, where sensor data are generated and access to energy is usually constrained. However, this approach is not scalable and results in high penalties in terms of security, privacy, cost, energy consumption, and latency as data need to travel from endpoint devices to remote processing systems such as data centres. Inefficiencies are especially evident in energy consumption.
To keep up pace with the exponentially growing amount of data (e.g. video) and allow more advanced, accurate, safe and timely interactions with the surrounding environment, next-generation endpoint devices will need to run AI algorithms (e.g. computer vision) and other compute intense tasks with very low latency (i.e. units of ms or less) and energy envelops (i.e. tens of mW or less).
NimbleAI will harness the latest advances in microelectronics and integrated circuit technology to create an integral neuromorphic sensing-processing solution to efficiently run accurate and diverse computer vision algorithms in resource- and area-constrained chips destined to endpoint devices. Biology will be a major source of inspiration in NimbleAI, especially with a focus to reproduce adaptivity and experience-induced plasticity that allow biological structures to continuously become more efficient in processing dynamic visual stimuli.
NimbleAI is expected to allow significant improvements compared to state-of-the-art (e.g. commercially available neuromorphic chips), and at least 100x improvement in energy efficiency and 50x shorter latency compared to state-of-the-practice (e.g. CPU/GPU/NPU/TPUs processing frame-based video). NimbleAI will also take a holistic approach for ensuring safety and security at different architecture levels, including silicon level.”
What I find a little odd, though, is that this claim re expected superiority over “
state-of-the-art (e.g. commercially available neuromorphic chips)“ doesn’t get any mention on the official Nimble AI website (
https://www.nimbleai.eu/), in contrast to the expectation of “at least 100x improvement in energy efficiency and 50x shorter latency compared
to state-of-the-practice (e.g. CPU/GPU/NPU/TPUs Processing Frame-based Video).”
iot-analytics.com
www.edgeimpulse.com
www.theguardian.com
