Artificial General Intelligence (AGI) Show with Soroush Pour
When will the world create an artificial intelligence that matches human level capabilities, better known as an artificial general intelligence (AGI)? What will that world look like & how can we ensure it's positive & beneficial for humanity as a whole? Tech entrepreneur & software engineer Soroush Pour (@soroushjp) sits down with AI experts to discuss AGI timelines, pathways, implications, opportunities & risks as we enter this pivotal new era for our planet and species.
Hosted by Soroush Pour. Follow me for more AGI content:
Twitter: https://twitter.com/soroushjp
LinkedIn: https://www.linkedin.com/in/soroushjp/
Artificial General Intelligence (AGI) Show with Soroush Pour
Ep 4 - When will AGI arrive? - Ryan Kupyn (Data Scientist & Forecasting Researcher @ Amazon AWS)
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".
