Recently, ChatGPT from OpenAI has become the most frequently named AI innovation. It demonstrates the power of AI. This presentation is about 2 benefits from this for automotive: 1.) How can large language models such as ChatGPT be used in automotive processes and 2.) how can the advancements in the development of ChatGPT be used in other automotive use cases? 1.) Large Language Models such as ChatGPT can also be used for the enhancement of engineering processes. Automotive projects require a lot of resources. Currently many positions cannot be staffed, and this leads to incomplete or delayed processes and products. Examples will be presented how large language models can be beneficially used in problem decomposition, solution design, code generation and testing. 2.) An in-depth analysis of the development methodology from ChatGPT reveals important learnings about successful AI development. For the purpose of “lessons learned for automotive”, the development approach of ChatGPT can be summarized as follows: Openness to new ideas, very large data for training and testing, combination of supposedly competing concepts, data crunching with expensive computing power, and broadband verification. These learnings can be well transferred to automotive use cases. If these learnings are followed, automotive can be even more successful with AI. Recent advancements can boost the productivity of processes and/or facilitate new features and also set the expectations by our customers.
Session:
Data Science & AI
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| 14:10 - 14:40