Today we’re joined by Wilka Carvalho, a PhD student at the University of Michigan, Ann Arbor.
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We first met Wilka at the Black in AI workshop at last year’s NeurIPS conference, and finally got a chance to catch up about his latest research, ‘ROMA: A Relational, Object-Model Learning Agent for Sample-Efficient Reinforcement Learning.’ In the paper, Wilka explores the challenge of object interaction tasks, focusing on every day, in-home functions like filling a cup of water in a sink.
In our conversation, we discuss his interest in understanding the foundational building blocks of intelligence, how he’s addressing the challenge of ‘object-interaction’ tasks, the biggest obstacles he’s run into along the way.
Celebrating 400 Interviews!
We recently released the 400th episode of the TWIML AI Podcast! While 400 is an amazing milestone, what’s even more interesting to us is how we grow and evolve over the next 100 episodes to better serve all of you. We’ve already introduced a ton of new programs this year, from video interviews to watch parties to premium courses, and this is just the beginning.
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Connect with Wilka!
- ROMA: A Relational, Object-Model Learning Agent for Sample-Efficient Reinforcement Learning
- Black in AI 2019: Efficiently Learning to Perform Household Tasks with Object-Oriented Exploration
- AI2-THOR Open Source Interactive Environment for Embodied AI
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“More On That Later” by Lee Rosevere licensed under CC By 4.0