#34 AI Series: HuggingFace - G. Channing

We are excited to feature Georgia Channing, who is currently leading the AI for Science team at Hugging Face and will discuss "When Silicon Meets Carbon: Bringing Synthetic Biology to Life", lasting approximately 45 minutes. After the talk, seize the opportunity to connect with fellow AI enthusiasts to share ideas and questions while enjoying free drinks and pizza. Door close by 7.15pm, so please come early! Also, "attend"ing (RSVP) here on Meetup is strictly necessary to be guaranteed entry.
Please note that Meetup has recently been quite keen on promoting its Plus program. However, you are not obligated to purchase it, as both our events and the platform remain free.

Who is this event for?
This event is open to everyone interested in state-of-the-art AI research. We especially design it for students, PhD candidates, academic researchers, and industry professionals with a research focus in machine learning.

Abstract: Foundation models have transformed how we read and design biological systems, from protein structure prediction to the generation of novel sequences. But building these models is as much an engineering problem as a scientific one. This talk looks at what it takes to bring AI for biology from research into practice, and at the challenges that make science a uniquely demanding domain for machine learning. We will cover how foundation models for biology are trained and deployed at scale, why scientific data is so different from the text and images that drive mainstream AI, and where the gap between a benchmark result and a real biological discovery still lies. The aim is to show how modern AI connects to living systems, and what we need to get right for synthetic biology to fully benefit from it.

Bio: Georgia Channing is the AI for Science Lead at Hugging Face, working at the intersection of machine learning and the natural sciences. She read for her Master’s and PhD in computer science at the University of Oxford, with a fo