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After the long wait, from May 2015 to the second half of 2019, the market hopes that Google's Project Soli will finally be ready to add its new HMI capabilities, and spark a new market for chips enabling the features.

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After the long wait, from May 2015 to the second half of 2019, the market hopes that Google's Project Soli will finally be ready to add its new HMI capabilities, and spark a new market for chips enabling the features.

An example of an electrode array like the ones from Micro-Leads Medical that will be used in the project (Image: Brown University)

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The physical implants will use a high-resolution spinal cord stimulation technology developed by Micro-Leads, called HD64. The first phase of the project will use 24-contact electrode arrays, moving to 64-contact arrays in the second phase. The contact sizes are in the order of 1 millimetre squared, and since a neuron is around 20 microns, each electrode will record or stimulate hundreds of thousands of neurons at a time. The signals to be recorded are electrical signals; as neurons communicate with each other, there is an electrical voltage change, and the electrode senses and records the change in electric field.

That's the exciting part of what we're going to find out. Typically, there are different frequency bands in the signal that can represent different underlying neuronal processes. So that can be a clue for us as to what is actually going on,” said Hanlin Tang, principal engineer at Intel’s AI Products Group, himself a former neuroscientist and the Intel lead on the project. But it is a lot of work on the machine learning side, to be able to interpret these signals well enough to know what to stimulate on the other side of the gap.”

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Intel’s team will use its hardware and machine learning expertise to help build an AI system that interprets the signals.

The key challenge here is that listening into the spine is not high fidelity,” Tang said. It's like trying to relay a message, but you can't really hear one side and you can only mention a few words on the other side. Using machine learning, you might be able to use some prior knowledge to try to fill in the gaps and be a good interface to bridge this type of injury.”

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The AI will also tackle mapping between the two electrode arrays, from one side of the injury site to the other, a crucial task.

Targeting this newly emerging AI accelerator market, Ceva, for one, unveiled at the AutoSens conference the company's new AI core and ‘Invite API.

Curiously, though, a new generation of feature-rich vehicles hasn’t exactly launched the deployment of fresh AI chips yet — beyond those designed by Nvidia and Intel/Mobileye, and full self-driving (FSD) computer” chips developed by Tesla for its internal use.

On Semiconductor’s RGB + IR camera announcement at AutoSens, on the other hand, revealed that the On Semi/Eyeris team has picked Ambarella’s SoC as its AI processor for in-vehicle monitoring tasks.

Acknowledging that Ambarella is not generally known as an AI accelerator outfit (it is, rather, a traditional video compression and computer vision chip company), Modar Alaoui, CEO of Eyeris, said, We couldn’t find any AI chips that can support 10 neural networks, consume less than 5 watt and capture 30 frames per second video by using up to six cameras — all looking inside a vehicle” to run Eyeris’ AI in-vehicle monitoring algorithms. But Ambarella’s CV2AQ SoC fit the bill, he said, beating all the other much-hyped accelerators.

Alaoui is hopeful, however, that his company’s AI software will be additionally ported to three other hardware platforms by the Consumer Electronics Show in Las Vegas next January.

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