Basecamp Research is on a mission to capture the vastness of life on Earth at an unprecedented scale. Phil Lorenz, CTO at Basecamp Research, discusses using AI and biodiversity data to advance fields like medicine and environmental conservation with host Noah Kravitz in this AI Podcast episode recorded live at the NVIDIA GTC global AI conference. Lorenz explains Basecamp's systematic collection of biodiversity data in partnership with nature parks worldwide and its use of deep learning to analyze and apply it for use cases such as protein structure prediction and gene editing. He also emphasizes the importance of ethical data governance and touches on technological advancements that will help drive the future of AI in biology.
Basecamp Research is a member of the NVIDIA Inception program for cutting-edge startups.
Stay tuned for more episodes recorded live at GTC, and hear more from Lorenz in this GTC session.
The AI Podcast Basecamp's Phil Lorenz on Combining AI With Biodiversity Data Ep. 223
Time Stamps 1:31: What is Basecamp Research?
3:08: How does the process of sequencing biodiversity work?
5:15: What is the collected biodiversity data used for?
7:56: Gene editing and how biodiversity data can enhance it
9:00: How the development of AI has affected Basecamp's work
14:33: Basecamp's breakthroughs
16:49: AI and machine learning-related challenges Basecamp has encountered
26:02: Ethical considerations in data collecting
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Basecamp Research is on a mission to capture the vastness of life on Earth at an unprecedented scale. Phil Lorenz, CTO at Basecamp Research, discusses using AI and biodiversity data to advance fields like medicine and environmental conservation with host Noah Kravitz in this AI Podcast episode recorded live at the NVIDIA GTC global AI conference. Lorenz explains Basecamp's systematic collection of biodiversity data in partnership with nature parks worldwide and its use of deep learning to analyze and apply it for use cases such as protein structure prediction and gene editing. He also emphasizes the importance of ethical data governance and touches on technological advancements that will help drive the future of AI in biology. 
