Trends in Deep Reinforcement Learning with Kamyar Azizzadenesheli - #560
2022-02-21 · 78 min · episode 560 · 16 entities
Asserted relationships
-
→ appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast0.68
evidence rules-v4
Trends in Deep Reinforcement Learning with Kamyar Azizzadenesheli - #560
-
0.55
evidence rules-v4
Feed author/publisher: Sam Charrington
-
0.50
evidence rules-v4
professor at Purdue University
-
0.50
evidence rules-v4
professor at Purdue University
-
0.40
evidence rules-v4
Feed category: Science
-
0.40
evidence rules-v4
Feed category: Technology
-
0.40
evidence rules-v4
Feed category: News
-
0.40
evidence rules-v4
Feed category: Tech News
-
0.40
evidence rules-v4
Feed author/publisher: TWIML
Entities found in this episode
companys 7
-
0.70
evidence rules-v4
Feed author/publisher: TWIML
-
0.62
evidence rules-v4
professor at Purdue University
-
0.50
evidence rules-v4
Feed category: Technology
-
0.50
evidence rules-v4
professor at Purdue University
-
0.50
evidence rules-v4
professor at Purdue University
-
0.40
evidence rules-v4
Feed category: Technology
-
0.40
evidence rules-v4
Feed author/publisher: TWIML
concepts 5
-
0.50
evidence rules-v4
Feed category: Science
-
0.50
evidence rules-v4
Feed category: Tech News
-
0.40
evidence rules-v4
Feed category: Science
-
0.40
evidence rules-v4
Feed category: News
-
0.40
evidence rules-v4
Feed category: Tech News
persons 3
-
0.72
evidence rules-v4
Trends in Deep Reinforcement Learning with Kamyar Azizzadenesheli - #560
-
0.70
evidence rules-v4
Feed author/publisher: Sam Charrington
-
0.55
evidence rules-v4
Feed author/publisher: Sam Charrington
podcasts 1
-
appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast0.68
evidence rules-v4
Trends in Deep Reinforcement Learning with Kamyar Azizzadenesheli - #560
Episode description as stored
Today we’re joined by Kamyar Azizzadenesheli, an assistant professor at Purdue University, to close out our AI Rewind 2021 series! In this conversation, we focused on all things deep reinforcement learning, starting with a general overview of the direction of the field, and though it might seem to be slowing, thats just a product of the light being shined constantly on the CV and NLP spaces. We dig into themes like the convergence of RL methodology with both robotics and control theory, as well as a few trends that Kamyar sees over the horizon, such as self-supervised learning approaches in RL. We also talk through Kamyar’s predictions for RL in 2022 and beyond. This was a fun conversation, and I encourage you to look through all the great resources that Kamyar shared on the show notes page at twimlai.com/go/560!