How AI won a Nobel Prize in Physics & Building a Virtual Friend

The MLAI Meetup is a community for AI researchers and professionals which hosts monthly talks on exciting research. Our format is:

• 6:00 - 6:20: Socializing
• 6:20 - 6:40: Announcements and AI news
• 6:40 - 7:40: Talk(s) and Q&A
• 7:40 - 8:00 Networking
• 8:00: Head to the nearest pub for dinner

Speaker 1: Chaehan So

Talk Title: From Academia to AI Startup: Building a Virtual Friend for Mental Well-being

Abstract: Chaehan So will share his journey from assistant professor to founder of Virtual Friend Inc., an AI startup that lets individuals with anxiety talk problems off their chest to an AI-generated virtual being that listens to them like their best friend. This work builds directly on his scholarly investigations into human-AI interactions and user experience design, shaping his work designing caring AI solutions for anxiety. His talk will explore this transition from academic research to practical application, highlighting the interplay of psychology, AI, and design in addressing real-world needs.

Speaker Bio: Dr. Chaehan So is the founder of Virtual Friend, an AI startup for mental health, and was previously Assistant Professor of Interaction Design and Applied AI. With a Ph.D. in Social Psychology from Humboldt University Berlin, he taught Machine Learning and Design Psychology. His publications examine how psychological factors shape first impressions to design artefacts and virtual characters, and were featured in journals like The Design Journal [1][2], Human Factors [3] and International Journal of Human-Computer-Interaction [4].

Speaker 2: Tommy Li

Talk title: A better love story than "Twilight": how AI won a Nobel physics prize

Abstract: As AI tightens its grip on the public consciousness with the emergence of now terrifyingly-advanced large language models, the utility of Machine Learning (ML) models for scientific research is a consideration that is at the forefront of many a scientific mind. While several areas of physics have enjoyed an intimate relationship with ML for many decades, a rapidly growing community of physicists is becoming enamoured, and it is this state of affairs that was celebrated by the 2024 Nobel physics prize, which was shared between a condensed matter physicist, John Hopfield, and a computer scientist, Geoffrey Hinton. Much of the physics community has decided that their fields--be it experimental particle physics, string theory, astronomy, quantum magnetism or quantum computing--and ML have a common destiny. In this talk I will tell the story of how modern physics became intertwined with the development of neural networks, how ML is currently impacting advances in physics, and what the future may hold for their relationship.

Speaker Bio: Tommy Li graduated with his Ph.D. in Physics from UNSW in 2017 and then moved to Europe to work as a researcher at the Niels Bohr Institute, Copenhagen and the Free University of Berlin. His research spans multiple domains in theoretical quantum physics, and has focused on quantum computing, quantum electronics and advanced materials. He is currently transitioning out of academia and looking to start a career in data science.