13

Jul

Teaser image to Generative AI in the Industry, Media, and Beyond. Chances and Challenges of Stable Diffusion

Panel discussion

Generative AI in the Industry, Media, and Beyond. Chances and Challenges of Stable Diffusion

Thiemo Fieger, BMW
Björn Ommer, Computer Vision & Learning Group, LMU Munich
Christian Schiffer, Bayerischer Rundfunk
Martin Skultety, Image Agency Image Professionals

   13.07.2023

   7:00 pm - 9:00 pm

   CAS Munich

Stable Diffusion, an AI model, generates photo-realistic images from text descriptions without requiring special skills or hardware. It has rapidly impacted research, start-ups, and industries, with millions of daily users. This panel explores the transformative potential, challenges, and changes brought by Stable Diffusion.


Related

Link to Ähren im Wind – Political Orientation in Challenging Times

Panel  •  05.12.2024  •  Literaturhaus München, Salvatorplatz 1, 80333 Munich, Germany, In-Person and Live Stream

Ähren im Wind – Political Orientation in Challenging Times

Join Alena Buyx at the Munich panel "Political Orientation in Challenging Times ", as she explores ethics and responsibility in modern politics.


Link to Can we think better, faster, and deeper with ChatGPT?

Panel  •  29.07.2024  •  CDTM, Marsstraße 20, 80335 Munich

Can we think better, faster, and deeper with ChatGPT?

Join the panel with leading experts to gain insights, ask questions, and engage in discussions about humanity's role in the AI era.


Link to ChatGPT and other Large Language Models in Teaching and Research

Keynote and Panel Discussion  •  24.06.2024  •  LMU Munich, Main Building, Große Aula

ChatGPT and other Large Language Models in Teaching and Research

Keynote by AI ethics expert Dr. Silvia Milano and a panel discussion moderated by Sven Nyholm, with professors Peter Adamson, Frauke Kreuter, and Albrecht Schmidt.


Link to Wie grün ist die KI?

Panel Discussion  •  11.06.2024  •  LMU Munich, Main Building, M210

Wie grün ist die KI?

AI's ambivalent role in sustainability involves high energy use and vital data analysis. Experts discuss this and answer audience questions on its impact.


Link to Opportunities and Limitations for Deep Learning in the Sciences

Round-Table  •  22.05.2023  •  LMU Munich

Opportunities and Limitations for Deep Learning in the Sciences

Philipp Grohs, University of Vienna, examines the potential and constraints of utilizing deep learning methods in computational sciences.