About this episode
In the second of the “AI in Africa” spotlight episodes, we welcome guests from Radiant Earth to talk about machine learning for earth observation. They give us a glimpse into their amazing data and tooling for working with satellite imagery, and they talk about use cases including crop identification and tropical storm wind speed estimation. Join the discussion Changelog++ members save 3 minutes on this episode because they made the ads disappear. Join today! Sponsors: Me, Myself, and AI – A podcast on artificial intelligence and business produced by MIT Sloan Management Review and Boston Consulting Group. Each episode, Sam Ransbotham and Sheervin Khodabandeh talk to AI leaders from organizations like Nasdaq, Spotify, Starbucks, and IKEA. Me, Myself, and AI is available wherever you get your podcasts. Just search Me, Myself, and AI. Fastly – Compute@Edge free for 3 months — plus up to $100k a month in credit for an additional 6 months. Fastly’s Edge cloud network and modern approach to serverless computing allows you to deploy and run complex logic at the edge with unparalleled security and blazing fast computational speed. Head to fastly.com/podcast to take advantage of this limited time promotion! LaunchDarkly – Fundamentally change how you deliver software. Innovate faster, deploy fearlessly, and make each release a masterpiece. Featuring: Hamed Alemohammad – X Abba Barde – LinkedIn , X Chris Benson – Website , GitHub , LinkedIn , X Daniel Whitenack – Website , GitHub , X Joyce Nabende – X Show Notes: Radiant Earth ML for Earth Observation online course “Spot the crop” challenge Open for Good Alliance Something missing or broken? PRs welcome!