Year/Course: 2021-2022, Lent 2022
Mentor: Dr Marc Bax

Inventor: Dr. Phillip Stanley-Marbell, Electrical Engineering & Signaloid
Mentor: TBC

Autonomous systems such as self-driving cars, drones and robots represent a rapidly-growing market that will touch every aspect of human life. To be widely deployed, they must be trusted by humans. Today, they are not: 70% of U.S. drivers report they would be afraid to ride in a self-driving vehicle and 63% report they would feel less safe sharing the road with a self-driving vehicle while walking or cycling (AAA 2018/2019/2020). The core of the problem is that the empirical data which drive autonomous systems (for example from sensors and cameras) are by nature uncertain, yet microprocessors today cannot track this uncertainty.

Signaloid has developed a new kind of computing hardware accelerator that can track uncertainty in data and provide an indication of that uncertainty even as multiple sensor measurements are combined. Signaloid has implemented this accelerator in a RISC-V processor and made it available to paying customers as part of a cloud computing service, available today. Users of the system are solving problems ranging from modeling aerospace metal alloys under materials-parameter uncertainty, to implementing the classical component of variational quantum algorithms.

Any computing system that operates on empirical data can be made faster and easier to design when running on Signaloid’s uncertainty-tracking computation platform. Signaloid’s technologies have the potential to be part of every general-purpose or application-specific microprocessor or computing accelerator and will be essential for real-world success of autonomous and AI systems.

The question for the i-Team is to investigate possible target applications for the Signaloid accelerator, within the field of autonomous systems. The team will interview relevant industry experts about their current and future use of increasingly autonomous systems. The team will aim to identify which products have the greatest need for the benefits that Signaloid can deliver, and recommend to the inventor which applications to pursue for the technology.