The Developer’s New Teammate: AI in Embedded and IoT Environments
summary
Panel reports concrete wins and concrete limits: AI generates first‑draft demo code and can remove the maloc in there on request, but produced code is often very verbose and hard to modify. AI extracts documentation and can extract requirements from code and suggest test cases to improve coverage; it helps tool‑chain onboarding but fails at system integration and safety certification. Transparency about training data and open models is recommended; prototypes and experiments exist, but full automation for embedded/automotive debugging and integration is not yet achieved.
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chapters (11)
- 0:00AI in embedded and IoT
- 1:08Current AI usage
- 4:16AI in automotive workflows
- 9:13AI for system design
- 12:24AI risks in safety-critical systems
- 15:33Building trust in AI tools
- 18:05Societal acceptance and business models
- 20:17Debunking AI hype
- 21:19AI productivity gains and limits
- 22:45AI in debugging
- 23:49Q&A
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