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Ep 4 - When will AGI arrive? - Ryan Kupyn (Data Scientist & Forecasting Researcher @ Amazon AWS)

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Manage episode 359462325 series 3428190
Content provided by Soroush Pour. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Soroush Pour 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.

In this episode, we speak with forecasting researcher & data scientist at Amazon AWS, Ryan Kupyn, about his timelines for the arrival of AGI.
Ryan was recently ranked the #1 forecaster in Astral Codex Ten's 2022 Prediction contest, beating out 500+ other forecasters and proving himself to be a world-class forecaster. He has also done work in ML & works as a forecaster for Amazon AWS.
Hosted by Soroush Pour. Follow me for more AGI content:
Twitter: https://twitter.com/soroushjp
LinkedIn: https://www.linkedin.com/in/soroushjp/
== Show links ==
-- About Ryan Kupyn --
* Bio: Ryan is a forecasting researcher at Amazon. His main hobby outside of work is designing walking tours for different Los Angeles neighborhoods.
* Ryan's meet-me email address: coffee AT ryankupyn DOT com
* Ryan: "I love to meet new people and talk about careers, ML, their best breakfast recipes and anything else."
-- Further resources --
* Superintelligence (Bostrom)
* Superforecasting (Tetlock, Gardner)
* Elements of Statistical Learning (Hastie, Tibshirani, Friedman)
* Ryan: "For general background on forecasting/statistics. This book is my go-to reference for understanding the math behind a lot of foundational statistical techniques."
* Animal Spirits (Akerlof, Shiller)
* Ryan: "For understanding how forecasts can be driven by emotion. I find this a useful book for understanding how forecasts can be wrong, and a useful reminder to be mindful of my own forecasts."
* Normal Accidents (Perrow)
* Ryan: "For understanding how humans interact with systems in ways that negate attempts by their creators to make them safer. I think there’s some utility in looking at previous accidents in complex systems to AGI, as presented in this book".

  continue reading

15 episodes

Artwork
iconShare
 
Manage episode 359462325 series 3428190
Content provided by Soroush Pour. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Soroush Pour 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.

In this episode, we speak with forecasting researcher & data scientist at Amazon AWS, Ryan Kupyn, about his timelines for the arrival of AGI.
Ryan was recently ranked the #1 forecaster in Astral Codex Ten's 2022 Prediction contest, beating out 500+ other forecasters and proving himself to be a world-class forecaster. He has also done work in ML & works as a forecaster for Amazon AWS.
Hosted by Soroush Pour. Follow me for more AGI content:
Twitter: https://twitter.com/soroushjp
LinkedIn: https://www.linkedin.com/in/soroushjp/
== Show links ==
-- About Ryan Kupyn --
* Bio: Ryan is a forecasting researcher at Amazon. His main hobby outside of work is designing walking tours for different Los Angeles neighborhoods.
* Ryan's meet-me email address: coffee AT ryankupyn DOT com
* Ryan: "I love to meet new people and talk about careers, ML, their best breakfast recipes and anything else."
-- Further resources --
* Superintelligence (Bostrom)
* Superforecasting (Tetlock, Gardner)
* Elements of Statistical Learning (Hastie, Tibshirani, Friedman)
* Ryan: "For general background on forecasting/statistics. This book is my go-to reference for understanding the math behind a lot of foundational statistical techniques."
* Animal Spirits (Akerlof, Shiller)
* Ryan: "For understanding how forecasts can be driven by emotion. I find this a useful book for understanding how forecasts can be wrong, and a useful reminder to be mindful of my own forecasts."
* Normal Accidents (Perrow)
* Ryan: "For understanding how humans interact with systems in ways that negate attempts by their creators to make them safer. I think there’s some utility in looking at previous accidents in complex systems to AGI, as presented in this book".

  continue reading

15 episodes

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