AIS. AI-in-Sensor. No digitizing. No latency. No distortion. No bus. No power -- almost. No problem.

AIS. AI-in-Sensor. No digitizing. No latency . No distortion. No bus. No power -- almost. No problem.

A storm is coming. AIStorm presents its AI-in-Sensor SoCs…

Sensors are not digital devices. To convert sensor information into a digital representation takes time, power, silicon, and adds distortion & noise. AIS solutions can be finished processing before the competition even has enough digital information to begin. So why not skip the middle man and consider our SoCs for your next project?

HIGHEST PERFORMANCE

Our patented charge domain technology guarantees a high performance, fully integrated SoC that you can’t find anywhere else.

LOWEST POWER

Because we don’t have to digitize sensor information, we offer the lowest power usage for performance in the industry.

LOW COST

We pass cost savings onto you by eliminating energy-intensive GPUs and DSPs so that you can focus on making your next project even better.

Technology

We’ve all heard about process in memory. Why stop there?

The sensors are the system's eyes, ears and fingers. Sensors can focus on what we care about and ignore the rest – a face, another car, an intruder, a sound, a change…

…event-driven digital just isn’t & memory needs something to remember. Consider an image sensor watching a warehouse. Only a few pixels are involved with the area around a door in the far corner where an intruder might enter.

So the system has to poll, or incorporate some complicated handshake scheme with the processing system to try to work out where to focus. No matter how it is done it is slow and complicated. So why bother? Now consider a camera scanning faces at an intersection. Distractions abound… cars, trees, clouds, winds, rain, snow, debris blowing by. How is a digital system going to deal with that with all those ADCs and handshakes going on?

AIS technology is analog and mixed signal technology, but it's more than that. For the first time the sensor itself is smart enough to deal with events, make decisions and can perform complex analysis…often before the other guy even receives his digital sensor representation to start processing.

Imagine a smart car braking faster; or a camera lasting years on a single battery; biometric login by small wearable devices like watches, bands and glasses. AIS has the power to enable new technologies like handset gesture control, heart-based security, through screen image sensors and advanced machine vision.

The Nitty Gritty

- compatible with TensorFlow & other AI abstraction languages

- programmable architecture

- >10 TOPs/W

- >2.5 TOPs

- up to 100’s of thousands of neurons in a few square mm’s

- Mhz to Multi-GHz DEC* clocking speeds

- distributed wavefront memory

- fast deep learning capable

- no noise penalty

- integrated sensors

- low cost

*Digital Equivalent

Applications

Through Screen Fingerprint Sensor

Augmented Transportation

Security & Traffic Cameras

A Warehouse Security Camera

A digital system watching the door in the background could easily miss an intruder due to the need to continuously poll different areas of the image. Otherwise, complicated interface schemes are required. AIS offers true event driven operation that can allow years of operation on a single battery.

A Face Recognition Traffic Camera

Security & Traffic Cameras

A Warehouse Security Camera

A Face Recognition Traffic Camera

Digital systems need complex arbiters to ignore background information like trees, cars, rain, snow, wind, clouds, debris, etc. and focus on faces. With AIS the cost and complication of digital processing is not needed.

A digital system watching the door in the background could easily miss an intruder due to the need to continuously poll different areas of the image. Otherwise, complicated interface schemes are required. AIS offers true event driven operation that can allow years of operation on a single battery.

"Heart Muscle Waveform Authentication" vs. "Fingerprint"

Wearable devices require a continuous, long life, authentication scheme. AIStorm and its partner companies own the patents to this technology and are using AIS to make it work.

Gesture control

Gesture control sensors can operate in the 50mW range, but the current level of processing takes too much power for handsets or watches. AIS technology enables this function by making it usable in portable applications.

Food service automation

Freeing personnel from redundant tasks and lowering costs for consumers, AI is already redefining the food industry. AIStorm is partnered with leaders in the food equipment industry to help usher in the next generation of AI-powered products.

medical imaging diagnosis

AI-augmented medical machine diagnostics is helping the medical industry reduce errors, distribute leading techniques and bring their services to remote locations. AIS technology can help improve medical devices by improving performance and lowering costs.

Edge voice processing

Voice is a key human interface device (HID). Already cell phones and stand-alone devices offer high-performance voice solutions. However, they are often dependent upon the cloud for operation. By pushing more capability into the device, bandwidth requirements can be reduced and the technology can be used for transportation and other applications where the cloud connection may not be reliable.

AIStorm – Recognized by Frost & Sullivan for Innovation

AIStorm has recently received the Technology Innovation Award for System-on-Chip Artificial Intelligence Sensor for Fast Edge Processing by leading global research organization Frost & Sullivan.

Our unique AIS technology can be integrated into existing facilities to enhance and streamline applications in a wide range of industries including consumer, automotive, security, medical imaging, and industrial automation.

“AIStorm’s AIS solution, powered by its charge domain and switched charge circuit processing technology, has the opportunity to overcome the shortcomings of existing GPUs and NPUs for high-performance, AI-based edge computing applications and is positioned to become a significant standard for edge computing and AI systems.”