In this episode of our AI For the Benefit of Society with Microsoft series, we’re joined by Lucas Joppa and Zach Parisa.
Lucas is the Chief Environmental Officer at Microsoft, spearheading their 5 year, $50 million AI for Earth commitment, which seeks to apply machine learning and AI across four key environmental areas: agriculture, water, biodiversity, and climate change. Zack is Co-founder and president of SilviaTerra, a Microsoft AI for Earth grantee whose mission is to help people use modern data sources to better manage forest habitats and ecosystems.
In our conversation we discuss the ways that machine learning and AI can be used to advance our understanding of forests and other ecosystems and support conservation efforts. We discuss how SilviaTerra uses computer vision and data from a wide array of sensors like LIDAR, combined with AI, to yield more detailed small-area estimates of the various species in our forests. We also briefly discuss another AI for Earth project, WildMe, a computer vision based wildlife conservation project we discussed with Jason Holmberg back on episode 166.
The complete show notes for this episode can be found at https://twimlai.com/talk/288. To follow along with the entire AI for the Benefit of Society series, visit https://twimlai.com/ai4society.
We’d like to thank Microsoft for their support and their sponsorship of this series. Microsoft is committed to ensuring the responsible development and use of AI and is empowering people around the world with intelligent technology to help solve previously intractable societal challenges spanning sustainability, accessibility and humanitarian action. Learn more at https://Microsoft.ai.
Causal Conceptions of Fairness and their Consequences with Sharad Goel - #586
Brain-Inspired Hardware and Algorithm Co-Design with Melika Payvand - #585
Equivariant Priors for Compressed Sensing with Arash Behboodi - #584
Managing Data Labeling Ops for Success with Audrey Smith - #583
Engineering an ML-Powered Developer-First Search Engine with Richard Socher - #582
On The Path Towards Robot Vision with Aljosa Osep - #581
More Language, Less Labeling with Kate Saenko - #580
Optical Flow Estimation, Panoptic Segmentation, and Vision Transformers with Fatih Porikli - #579
Data Governance for Data Science with Adam Wood - #578
Feature Platforms for Data-Centric AI with Mike Del Balso - #577
The Fallacy of "Ground Truth" with Shayan Mohanty - #576
Principle-centric AI with Adrien Gaidon - #575
Data Debt in Machine Learning with D. Sculley - #574
AI for Enterprise Decisioning at Scale with Rob Walker - #573
Data Rights, Quantification and Governance for Ethical AI with Margaret Mitchell - #572
Studying Machine Intelligence with Been Kim - #571
Advances in Neural Compression with Auke Wiggers - #570
Mixture-of-Experts and Trends in Large-Scale Language Modeling with Irwan Bello - #569
Daring to DAIR: Distributed AI Research with Timnit Gebru - #568
Hierarchical and Continual RL with Doina Precup - #567
Create your
podcast in
minutes
It is Free
20/20
The Dropout
Ten Percent Happier with Dan Harris
World News Tonight with David Muir
NEJM This Week