The Berlin, Germany-based startup said that its software is designed for processing large amounts of automotive sensor data combined with machine learning to achieve up to 10 times the processing speed by just using existing automotive hardware.
Normally, the constrained hardware environment of an automobile prohibits the processing of the large amounts of data that autonomous vehicle systems require without specialist chips.
"Automobiles are adding ever larger amounts of sensors to enable autonomous vehicles and this explosion in data is a problem because of latency." said Daniel Richart CEO and co-founder of Teraki. "Our software can work with the limited processing capabilities of current microcontrollers on the market."
Using the cloud for automotive applications is considered risky because latency issues can be deadly in a moving car if a wireless signal is lost or there's a weak connection.
Teraki's software is able to process large amounts of data inside the vehicle. Car makers can adapt their existing designs to use Teraki software because edge processing algorithms reduce the data load needed to analyze key automobile performance information.
Infineon's AURIX micro controllers are the first to feature Teraki's AI software technologies.
Ritesh Tyagi, head of the Infineon Silicon Valley Automotive Innovation Center, said, "For applications such as accident detection, driver behavior identification and predictive maintenance, the combination of these technologies translates into greater accuracy in detecting and responding to real-time events, resulting in higher levels of system reliability."
Teraki was founded by former quantum computing researchers. They've applied their quantum computing algorithmic expertise to solving the problem of massive amounts of data being generated by modern vehicles; and the need to provide rapid analysis and apply vehicle control processes in real-time.
The automotive electronics market is booming and is valued at $395 billion says Teraki and it has its sights set on an even larger market in Internet of Things applications and other environments where computing and memory resources are constrained by the hardware available.
It's edge processing technology limits the amount of data that needs to be send over networks and speeds up overall processing by factors of four to 10 times depending on the environment.