Artificial General Intelligence (AGI) Show with Soroush Pour
Soroush Pour
15 episodes
7 months ago
We speak with Stephen Casper, or "Cas" as his friends call him. Cas is a PhD student at MIT in the Computer Science (EECS) department, in the Algorithmic Alignment Group advised by Prof Dylan Hadfield-Menell. Formerly, he worked with the Harvard Kreiman Lab and the Center for Human-Compatible AI (CHAI) at Berkeley. His work focuses on better understanding the internal workings of AI models (better known as “interpretability”), making them robust to various kinds of adversarial attacks, and ca...
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We speak with Stephen Casper, or "Cas" as his friends call him. Cas is a PhD student at MIT in the Computer Science (EECS) department, in the Algorithmic Alignment Group advised by Prof Dylan Hadfield-Menell. Formerly, he worked with the Harvard Kreiman Lab and the Center for Human-Compatible AI (CHAI) at Berkeley. His work focuses on better understanding the internal workings of AI models (better known as “interpretability”), making them robust to various kinds of adversarial attacks, and ca...
Ep 1 - When will AGI arrive? - Logan Riggs Smith (AGI alignment researcher)
Artificial General Intelligence (AGI) Show with Soroush Pour
1 hour 10 minutes
2 years ago
Ep 1 - When will AGI arrive? - Logan Riggs Smith (AGI alignment researcher)
We speak with AGI alignment researcher Logan Riggs Smith about his timelines for AGI. He also speaks to how we might get there and some of the implications. Hosted by Hunter Jay and Soroush Pour Show links Further writings from Logan Riggs SmithCotra report on AGI timelines:Original report (very long)Scott Alexander analysis of this report
Artificial General Intelligence (AGI) Show with Soroush Pour
We speak with Stephen Casper, or "Cas" as his friends call him. Cas is a PhD student at MIT in the Computer Science (EECS) department, in the Algorithmic Alignment Group advised by Prof Dylan Hadfield-Menell. Formerly, he worked with the Harvard Kreiman Lab and the Center for Human-Compatible AI (CHAI) at Berkeley. His work focuses on better understanding the internal workings of AI models (better known as “interpretability”), making them robust to various kinds of adversarial attacks, and ca...
