#171 Anna Marie Wagner: Harnessing AI for Synthetic Biology
Join host Craig Smith on episode #171 of Eye on AI, for an enlightening conversation with Anna Marie Wagner, SVP, Head of AI at Ginkgo Bioworks, renowned for their work in synthetic biology and its integration with artificial intelligence. In this episode, we explore groundbreaking projects like engineering self-fertilizing corn, pioneering RNA therapeutics, and developing sustainable materials. Discover how Ginkgo leverages its genomic library and AI to design custom proteins, pushing scientific boundaries and paving the way for revolutionary industry applications. We'll also tackle the vital topics of biosecurity and ethical considerations in biotech, highlighting the balance between innovation and responsibility. Anna Marie Wagner's insights provide a glimpse into the transformative potential at the crossroads of biology and technology, making this episode a must-listen for anyone intrigued by the future of scientific advancements. Tune in to Eye on AI for this enlightening discussion, and don't forget to rate us on Apple Podcast and Spotify if you enjoy the episode. Stay Updated: Craig Smith Twitter: https://twitter.com/craigss Eye on A.I. Twitter: https://twitter.com/EyeOn_AI (00:00) Preview and Introduction (01:37) Anna 's Role at Ginkgo and Her Journey in AI and Biotech (02:25) Ginkgo Bioworks: History, Founders, and Philosophy (08:05) Who Can Use Ginkgo's Services? (10:30) Small Molecules, Biologics, and the Scope of Ginkgo's Work (12:48) The Role of AI in Biotechnology (16:46) Enzyme Engineering and ML-Guided Searches (19:11) Ginkgo's Unique Approach to AI and Biotech (24:33) The Corn Nitrogen Fixation Project with Bayer (27:20) Genetic Mechanisms for Nitrogen Fixation (33:19) Addressing Biosafety and Biosecurity Concerns (36:47) Exploring New Materials and Environmental Concerns (40:27) Innovations in Biotech (42:01) Increasing Biotech Awareness (46:46) Collaboration with Google (48:06) Building Foundation Models on Google's Infrastructure (53:20) The Potential of AI in Biology