FASTER AI:Fullständigt & Autonomt Förverkligande av Säkerhets- och Tidskritisk Inbäddad Artif. Intelligens
| Reference number | |
| Coordinator | Kungliga Tekniska Högskolan - KTH Skolan f elektroteknik och datavetenskap |
| Funding from Vinnova | SEK 8 349 645 |
| Project duration | January 2023 - June 2025 |
| Status | Ongoing |
| Venture | Advanced digitalization - Enabling technologies |
| Call | Advanced and innovative digitalization 2022 |
Purpose and goal
FASTER AI addresses emergent needs to embed machine learning (ML) inference capabilities within hardware infrastructure of critical importance and use. We focus on hardware utilized widely in telecommunications as well as airborne systems and other vehicles.
Expected effects and result
This project will contribute to the creation of a software methodology for ML on special critical hardware. The software will include a "neural architecture search" library as well as a compiler toolchain that can combine regular programs with ML-inference. Finally, we will demonstrate our methodology and software on two critical-purpose use-cases.
Planned approach and implementation
Our planned steps include the following steps: -establish project agreements (wp5) -develop software-agnostic libraries (wp1, wp2) -adapt libraries to the use-case hardware at runtime (wp3) -implement demonstrator projects (WP4)