Models for Human-Robot Collaboration with Julie Shah - #538

Models for Human-Robot Collaboration with Julie Shah - #538

Today we’re joined by Julie Shah, a professor at the Massachusetts Institute of Technology (MIT). Julie’s work lies at the intersection of aeronautics, astronautics, and robotics, with a specific focus on collaborative and interactive robotics. In our conversation, we explore how robots would achieve the ability to predict what their human collaborators are thinking, what the process of building knowledge into these systems looks like, and her big picture idea of developing a field robot that doesn’t “require a human to be a robot” to work with it. We also discuss work Julie has done on cross-training between humans and robots with the focus on getting them to co-learn how to work together, as well as future projects that she’s excited about. The complete show notes for this episode can be found at twimlai.com/go/538.

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Why Jev Is Changing How We Build With AI with Diogo Almeida - #779

Why Jev Is Changing How We Build With AI with Diogo Almeida - #779

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From Math Olympiads to Navier-Stokes: How Fast Is AI Progressing? with Greg Burnham - #778

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From Voice Agents to AI Avatars with Alexander Smola - #777

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Do AI Tokenomics Matter More Than Model Benchmarks? with Chris Potts - #776

Do AI Tokenomics Matter More Than Model Benchmarks? with Chris Potts - #776

As reasoning models consume more tokens and AI systems become more expensive to run, understanding what those tokens actually buy is becoming increasingly important. In this episode, Stanford professo...

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World Models and the Future of Spatial AI with Justin Johnson - #775

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Why the Next AI Breakthrough May Come from Physics with Max Welling - #774

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Why Image Generation Needs More Than Bigger Models with Fatih Porikli - #773

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Why Models Are AI’s Next Training Dataset with Damian Borth - #772

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