AutoLang: Anpassning av LLM för programvaruutveckling inom fordonsindustrin
Forskningsprojekt, 2024
– 2026
The primary objective of AutoLang is to adapt generalist, open-source LLMs to the automotive domain to help assist/automate language-based tasks in automotive engineering. Many task artifacts and work products of automotive engineering are natural language documents. The corollary, of course, is that automotive engineers spend significant effort creating/reviewing these
documents, or even taking actions based upon compiled documents. An AutoLang family of LLMs adapted to documents from automotive domains has the potential to assist/automate document-based engineering, significantly improving productivity.
Looking ahead, it's conceivable to apply this approach to other domains such as telecommunications or healthcare, with much of the underlying logic remaining applicable. This project sets a strong foundation for future research into domain-specific large language models.
Deltagare
Yinan Yu (kontakt)
Chalmers, Data- och informationsteknik, Funktionell programmering
Dhasarathy Parthasarathy
Chalmers, Data- och informationsteknik, Funktionell programmering
Samarbetspartners
Volvo Group
Gothenburg, Sweden
Finansiering
Chalmers AI-forskningscentrum (CHAIR)
Finansierar Chalmers deltagande under 2024–2026
Relaterade styrkeområden och infrastruktur
Informations- och kommunikationsteknik
Styrkeområden
Transport
Styrkeområden