Earthsight

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  • 5,0 (3)
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Chris and Krishna share big thoughts about the geospatial industry. Chris is a data scientist currently working in weather, but has previously worked at Los Alamos National Lab, The Earth Genome, Gro Intelligence and Demeter Labs. At those places he used earth observation data to solve problems such as crop mapping, yield prediction, change detection etc... Krishna is a data journalist who uses satellite imagery for news coverage. Previously he worked at Descartes Labs, Impact Observatory, The Earth Genome, Ceres Imaging and more. Krishna is an adjunct professor at The Cooper Union.

Épisodes

  1. 26 SEPT.

    Geospatial Platforms, Career Paths, Questions from Ep 1.

    In this episode Chris and Krishna talk a little about their career paths, reply to some questions from listeners about Episode 1 concerning embeddings, and profess their undying love for Google Earth Engine. Throughout this conversation, a common theme explored is the nature of the abstractions implemented in Google Earth Engine, vs the open-source ecosystem. If anyone from Google sees this: we would love more export tasks. (00:00) Introductions and career paths (08:00) Questions from Episode 1 (17:00) Geospatial platform discussion. Descartes Labs, Google Earth Engine, the Impact Observatory pipeline and more!

    1 h 4 min

  2. 9 SEPT.

    Embeddings in Context: Tools for Geospatial Problem Solving

    Chris and Krishna discuss their experiences working with geospatial embeddings, search and remote sensing in general, and how they think through problems. Timestamps sustainably sourced and hand crafted. (0:00) Intro (2:30) Background, earth observation and existing algorithms and the embedding fallacy. (9:49) Validation, how to solve problems, seductive embeddings, the museum of cool demos. (19:22) What are embeddings? (21:00) Search vs embeddings, the development of Earth Index. (25:00) Expert embeddings: the dumbest embeddings that work. (30:25) Computer vision embeddings/ImageNet. Experiments in pre-training, how to spend $40,000 in cloud credits. (37:22) Should we pre-train on satellite imagery? DINO v3 (44:30) What properties should embeddings have for search? Recall vs Precision/Landcover+ (50:00) Real world consequences of mapping (54:00) Future outlook, Krishna is jaded

    1 h
  • 2 épisodes

Notes et avis

5
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3 notes

À propos

Chris and Krishna share big thoughts about the geospatial industry. Chris is a data scientist currently working in weather, but has previously worked at Los Alamos National Lab, The Earth Genome, Gro Intelligence and Demeter Labs. At those places he used earth observation data to solve problems such as crop mapping, yield prediction, change detection etc... Krishna is a data journalist who uses satellite imagery for news coverage. Previously he worked at Descartes Labs, Impact Observatory, The Earth Genome, Ceres Imaging and more. Krishna is an adjunct professor at The Cooper Union.

Informations

  • Création
    cr458
  • Années d’activité
    2 k
  • Épisodes
    2
  • Classification
    Tous publics
  • Copyright
    © cr458
  • Site web de l’émission
    Earthsight

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