Artwork

Inhalt bereitgestellt von MapScaping. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von MapScaping oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.
Player FM - Podcast-App
Gehen Sie mit der App Player FM offline!

Natural Language Geocoding

45:14
 
Teilen
 

Manage episode 431724295 series 2502116
Inhalt bereitgestellt von MapScaping. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von MapScaping oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

In this episode, I welcome Jason Gilman, a Principal Software Engineer at Element 84, to explore the exciting world of natural language geocoding.

Key Topics Discussed:

  1. Introduction to Natural Language Geocoding:

    • Jason explains the concept of natural language geocoding and its significance in converting textual descriptions of locations into precise geographical data. This involves using large language models to interpret a user's natural language input, such as "the coast of Florida south of Miami," and transform it into an accurate polygon that represents that specific area on a map. This process automates and simplifies how users interact with geospatial data, making it more accessible and user-friendly.
  2. The Evolution of AI and ML in Geospatial Work:

    • Over the last six months, Jason has shifted focus to AI and machine learning, leveraging large language models to enhance geospatial data processing.
  3. Challenges and Solutions:

    • Jason discusses the challenges of interpreting natural language descriptions and the solutions they've implemented, such as using JSON schemas and OpenStreetMap data.
  4. Applications and Use Cases:

    • From finding specific datasets to processing geographical queries, the applications of natural language geocoding are vast. Jason shares some real-world examples and potential future uses.
  5. Future of Geospatial AIML:

    • Jason touches on the broader implications of geospatial AI and ML, including the potential for natural language geoprocessing and its impact on scientific research and everyday applications.

Interesting Insights:

  • The use of large language models can simplify complex geospatial queries, making advanced geospatial analysis accessible to non-experts.
  • Integration of AI and machine learning with traditional geospatial tools opens new avenues for research and application, from environmental monitoring to urban planning.

Quotes:

  • "Natural language geocoding is about turning a user's textual description of a place on Earth into a precise polygon."
  • "The combination of vision models and large language models allows us to automate complex tasks that previously required manual effort."

Additional Resources:

Connect with Jason:

  • Visit Element 84's website for more information and contact details.
  • Google "Element 84 Natural Language Geocoding" for additional resources and talks.
  continue reading

238 Episoden

Artwork
iconTeilen
 
Manage episode 431724295 series 2502116
Inhalt bereitgestellt von MapScaping. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von MapScaping oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

In this episode, I welcome Jason Gilman, a Principal Software Engineer at Element 84, to explore the exciting world of natural language geocoding.

Key Topics Discussed:

  1. Introduction to Natural Language Geocoding:

    • Jason explains the concept of natural language geocoding and its significance in converting textual descriptions of locations into precise geographical data. This involves using large language models to interpret a user's natural language input, such as "the coast of Florida south of Miami," and transform it into an accurate polygon that represents that specific area on a map. This process automates and simplifies how users interact with geospatial data, making it more accessible and user-friendly.
  2. The Evolution of AI and ML in Geospatial Work:

    • Over the last six months, Jason has shifted focus to AI and machine learning, leveraging large language models to enhance geospatial data processing.
  3. Challenges and Solutions:

    • Jason discusses the challenges of interpreting natural language descriptions and the solutions they've implemented, such as using JSON schemas and OpenStreetMap data.
  4. Applications and Use Cases:

    • From finding specific datasets to processing geographical queries, the applications of natural language geocoding are vast. Jason shares some real-world examples and potential future uses.
  5. Future of Geospatial AIML:

    • Jason touches on the broader implications of geospatial AI and ML, including the potential for natural language geoprocessing and its impact on scientific research and everyday applications.

Interesting Insights:

  • The use of large language models can simplify complex geospatial queries, making advanced geospatial analysis accessible to non-experts.
  • Integration of AI and machine learning with traditional geospatial tools opens new avenues for research and application, from environmental monitoring to urban planning.

Quotes:

  • "Natural language geocoding is about turning a user's textual description of a place on Earth into a precise polygon."
  • "The combination of vision models and large language models allows us to automate complex tasks that previously required manual effort."

Additional Resources:

Connect with Jason:

  • Visit Element 84's website for more information and contact details.
  • Google "Element 84 Natural Language Geocoding" for additional resources and talks.
  continue reading

238 Episoden

Alle Folgen

×
 
Loading …

Willkommen auf Player FM!

Player FM scannt gerade das Web nach Podcasts mit hoher Qualität, die du genießen kannst. Es ist die beste Podcast-App und funktioniert auf Android, iPhone und im Web. Melde dich an, um Abos geräteübergreifend zu synchronisieren.

 

Kurzanleitung