Next AI Engineering Lab seminar: AI-based digital clones by Dan Thompson from Sensay
Tuesday Oct. 29th, 10-11 am, via Zoom.
Title: "Turning myself into an AI"
Abstract:
A discussion on what identity means when we have indistinguishable digital replicas and how we can achieve digital immortality through accurate AI representations of ourselves.
Dan Thompson's Bio:
Dan Thomson is founder of Sensay, a leading platform for the creation of AI-based digital clones and a pioneer in digital immortality. He founded Sensay in 2023 to create solutions across a range of sectors, from healthcare to education, building a knowledge capture and share platform for the betterment of humanity.He has a track record of launching and scaling new ideas, whether in the food and beverage industry or technology startups.Dan has a BA in Philosophy from King’s College London and an MBA from the University of Cambridge. He has authored two books to date: ‘Immortality in a Digital Age’ and ‘The Digital Afterlife’.
Andreas Vogelsang to present in the first AI Engineering Lab event!
Sept 30th, 11-12 hybrid in Jupiter 473 and zoom.
Title: "Prompting the Future: Integrating Generative LLMs and Requirements Engineering"
Abstract:
Generative LLMs, such as GPT, have revolutionized our interaction with artificial intelligence. Their ability to understand, generate, and manipulate language presents unprecedented opportunities and challenges across various disciplines, including RE. Generative LLMs have the potential to redefine the landscape of requirements elicitation, specification, and validation.
The talk is structured into two primary segments. The first part delves into the application of generative LLMs in automating RE tasks. It explores how these models can assist in accurately capturing and specifying requirements, generating requirement documents, and automating the verification of requirements consistency and completeness. By examining examples and current research, this part will highlight the transformative potential of generative LLMs in enhancing efficiency, accuracy, and comprehensiveness in RE.
The second part positions RE as a critical discipline for developing well-crafted prompts essential for interacting with generative LLMs. It underscores the importance of precise, unambiguous, and comprehensive requirements in formulating prompts that elicit accurate and relevant responses from the models. This part will also discuss the art and science of crafting effective prompts, drawing parallels between requirements specification techniques and prompt engineering strategies.
Bio:
Andreas Vogelsang is full professor for Software and Systems Engineering at the University of Cologne. He received a PhD from the Technical University of Munich. His research is at the intersection between requirements engineering, empirical software engineering, and machine learning. He has published over 100 papers in international journals and conferences such as TSE, JSS, IEEE Software, RE, and ICSE. In 2018, he was appointed as Junior-Fellow of the German Society for Informatics (GI). Further information can be obtained from https://cs.uni- koeln.de/sse.
