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Practical Use for AI and Machine Learning in Science

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Manage episode 425393155 series 2513416
Content provided by Fraser Cain. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Fraser Cain or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

AI is practically everywhere right now. But what practical use does it have in science? How can machine learning and large language models help in Astronomy and Cosmology? What can they look like and what use can we get out of them?

🟣 Guest: Dr Mike Smith
https://www.mjjsmith.com/

👉 AstroPT on GitHub: https://github.com/Smith42/astroPT
👉 AstroPT Discord: discord.gg/MNEVegvfJq

📜 AstroPT: Scaling Large Observation Models for Astronomy
https://arxiv.org/abs/2405.14930

🦄 Support us on Patreon:
https://patreon.com/universetoday

📚 Suggest books in the book club:
https://www.goodreads.com/group/show/1198440-universe-today-book-club

  • 00:00 Intro
  • 01:40 AI in modern science
  • 05:33 Astronomy data for AstroPT
  • 10:50 How does it work
  • 17:15 How people can use AstroPT
  • 19:58 Training data
  • 22:45 Better understanding of Physics
  • 28:58 What's next
  • 38:51 The perfect data to feed AI
  • 43:55 Current obsessions
  • 47:40 Final thoughts

📺 VIDEO VERSION
https://youtu.be/SexDIF__8l4

📰 EMAIL NEWSLETTER
Read by 60,000 people every Friday. Written by Fraser. No ads.
Subscribe. It's FREE: https://universetoday.com/newsletter

🎧 PODCASTS
Universe Today: https://universetoday.fireside.fm/
Astronomy Cast: http://www.astronomycast.com/

🤳 OTHER SOCIAL MEDIA
Twitter: https://twitter.com/fcain
Twitter: https://twitter.com/universetoday
Facebook: https://facebook.com/universetoday
Instagram: https://instagram.com/universetoday

📩 CONTACT FRASER
frasercain@gmail.com

⚖️ LICENSE
Creative Commons Attribution 4.0 International (CC BY 4.0)

Support Universe Today Podcast

  continue reading

1172 episodes

Artwork
iconShare
 
Manage episode 425393155 series 2513416
Content provided by Fraser Cain. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Fraser Cain or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

AI is practically everywhere right now. But what practical use does it have in science? How can machine learning and large language models help in Astronomy and Cosmology? What can they look like and what use can we get out of them?

🟣 Guest: Dr Mike Smith
https://www.mjjsmith.com/

👉 AstroPT on GitHub: https://github.com/Smith42/astroPT
👉 AstroPT Discord: discord.gg/MNEVegvfJq

📜 AstroPT: Scaling Large Observation Models for Astronomy
https://arxiv.org/abs/2405.14930

🦄 Support us on Patreon:
https://patreon.com/universetoday

📚 Suggest books in the book club:
https://www.goodreads.com/group/show/1198440-universe-today-book-club

  • 00:00 Intro
  • 01:40 AI in modern science
  • 05:33 Astronomy data for AstroPT
  • 10:50 How does it work
  • 17:15 How people can use AstroPT
  • 19:58 Training data
  • 22:45 Better understanding of Physics
  • 28:58 What's next
  • 38:51 The perfect data to feed AI
  • 43:55 Current obsessions
  • 47:40 Final thoughts

📺 VIDEO VERSION
https://youtu.be/SexDIF__8l4

📰 EMAIL NEWSLETTER
Read by 60,000 people every Friday. Written by Fraser. No ads.
Subscribe. It's FREE: https://universetoday.com/newsletter

🎧 PODCASTS
Universe Today: https://universetoday.fireside.fm/
Astronomy Cast: http://www.astronomycast.com/

🤳 OTHER SOCIAL MEDIA
Twitter: https://twitter.com/fcain
Twitter: https://twitter.com/universetoday
Facebook: https://facebook.com/universetoday
Instagram: https://instagram.com/universetoday

📩 CONTACT FRASER
frasercain@gmail.com

⚖️ LICENSE
Creative Commons Attribution 4.0 International (CC BY 4.0)

Support Universe Today Podcast

  continue reading

1172 episodes

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