Earthly Machine Learning: Who It's For and Who Sponsors It

Est. audience: 200
Apple rating: 0 from 0
Cadence: Weekly
Latest: 2026-09-20
By: Amirpasha
Based on: 12 recent episodes

Covers: Summaries of academic research papers on machine learning models applied to weather forecasting, climate downscaling, and environmental data analysis.
For: Climate scientists, meteorologists, and machine learning researchers working on Earth science data.
Best for: Data scientists and climate researchers seeking quick reviews of modern Earth-focused AI research.
Skip if: General business audiences seeking standard enterprise AI or sales automation strategies.

Start with

Machine learning is revolutionizing weather forecasting – the next step is a change in how we work: Explains how AI models shift workflows across the weather forecasting value chain.
CORDEX-ML-Bench: A Benchmark for Data-Driven Regional Climate Downscaling—Experiment Design and Overview: Presents a standardized benchmark for testing data-driven climate downscaling models.
WV-Net: A Foundation Model for SAR Ocean Satellite Imagery: Introduces a foundational machine learning model for analyzing open-ocean satellite imagery.

Summarised by AI from 12 recent episodes. Audience estimate and Apple rating from Podscan, checked 2026-11-03; treat the estimate as a guide and ask the show for its own numbers. Prices are not included. Report a mistake.