Nightshade: Data Poisoning to Fight Generative AI with Ben Zhao - #668

Nightshade: Data Poisoning to Fight Generative AI with Ben Zhao - #668

Today we’re joined by Ben Zhao, a Neubauer professor of computer science at the University of Chicago. In our conversation, we explore his research at the intersection of security and generative AI. We focus on Ben’s recent Fawkes, Glaze, and Nightshade projects, which use “poisoning” approaches to provide users with security and protection against AI encroachments. The first tool we discuss, Fawkes, imperceptibly “cloaks” images in such a way that models perceive them as highly distorted, effectively shielding individuals from recognition by facial recognition models. We then dig into Glaze, a tool that employs machine learning algorithms to compute subtle alterations that are indiscernible to human eyes but adept at tricking the models into perceiving a significant shift in art style, giving artists a unique defense against style mimicry. Lastly, we cover Nightshade, a strategic defense tool for artists akin to a 'poison pill' which allows artists to apply imperceptible changes to their images that effectively “breaks” generative AI models that are trained on them. The complete show notes for this episode can be found at twimlai.com/go/668.

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Neural Ordinary Differential Equations with David Duvenaud - #364

Neural Ordinary Differential Equations with David Duvenaud - #364

Today we’re joined by David Duvenaud, Assistant Professor at the University of Toronto, to discuss his research on Neural Ordinary Differential Equations, a type of continuous-depth neural network. In...

9 Huhti 202049min

The Measure and Mismeasure of Fairness with Sharad Goel - #363

The Measure and Mismeasure of Fairness with Sharad Goel - #363

Today we’re joined by Sharad Goel, Assistant Professor at Stanford. Sharad, who also has appointments in the computer science, sociology, and law departments, has spent recent years focused on applyin...

6 Huhti 202048min

Simulating the Future of Traffic with RL w/ Cathy Wu - #362

Simulating the Future of Traffic with RL w/ Cathy Wu - #362

Today we’re joined by Cathy Wu, Assistant Professor at MIT. We had the pleasure of catching up with Cathy to discuss her work applying RL to mixed autonomy traffic, specifically, understanding the pot...

2 Huhti 202035min

Consciousness and COVID-19 with Yoshua Bengio - #361

Consciousness and COVID-19 with Yoshua Bengio - #361

Today we’re joined by one of, if not the most cited computer scientist in the world, Yoshua Bengio, Professor at the University of Montreal and the Founder and Scientific Director of MILA. We caught u...

30 Maalis 202049min

Geometry-Aware Neural Rendering with Josh Tobin - #360

Geometry-Aware Neural Rendering with Josh Tobin - #360

Today we’re joined by Josh Tobin, Co-Organizer of the machine learning training program Full Stack Deep Learning. We had the pleasure of sitting down with Josh prior to his presentation of his paper G...

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The Third Wave of Robotic Learning with Ken Goldberg - #359

The Third Wave of Robotic Learning with Ken Goldberg - #359

Today we’re joined by Ken Goldberg, professor of engineering at UC Berkeley, focused on robotic learning. In our conversation with Ken, we chat about some of the challenges that arise when working on ...

23 Maalis 20201h 1min

Learning Visiolinguistic Representations with ViLBERT w/ Stefan Lee - #358

Learning Visiolinguistic Representations with ViLBERT w/ Stefan Lee - #358

Today we’re joined by Stefan Lee, an assistant professor at Oregon State University. In our conversation, we focus on his paper ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for V...

18 Maalis 202027min

Upside-Down Reinforcement Learning with Jürgen Schmidhuber - #357

Upside-Down Reinforcement Learning with Jürgen Schmidhuber - #357

Today we’re joined by Jürgen Schmidhuber, Co-Founder and Chief Scientist of NNAISENSE, the Scientific Director at IDSIA, as well as a Professor of AI at USI and SUPSI in Switzerland. Jürgen’s lab is w...

16 Maalis 202034min

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