Relational, Object-Centric Agents for Completing Simulated Household Tasks with Wilka Carvalho

800 800 The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

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.

We want to hear your feedback on this occasion. Head to the comments section below and share your story on how the podcast has impacted you, your thoughts on how we can improve, and your tips on who we should interview!

As a thank you for your contribution we are printing up a fresh new batch of TWIML laptop stickers, and everyone who leaves a note will get some!

Connect with Wilka!

Resources

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“More On That Later” by Lee Rosevere licensed under CC By 4.0

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