Responsible AI in the Generative Era with Michael Kearns - #662

Responsible AI in the Generative Era with Michael Kearns - #662

Today we’re joined by Michael Kearns, professor in the Department of Computer and Information Science at the University of Pennsylvania and an Amazon scholar. In our conversation with Michael, we discuss the new challenges to responsible AI brought about by the generative AI era. We explore Michael’s learnings and insights from the intersection of his real-world experience at AWS and his work in academia. We cover a diverse range of topics under this banner, including service card metrics, privacy, hallucinations, RLHF, and LLM evaluation benchmarks. We also touch on Clean Rooms ML, a secured environment that balances accessibility to private datasets through differential privacy techniques, offering a new approach for secure data handling in machine learning. The complete show notes for this episode can be found at twimlai.com/go/662.

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Towards the Self-Driving Enterprise with Kirk Borne - TWiML Talk #151

Towards the Self-Driving Enterprise with Kirk Borne - TWiML Talk #151

In this show, the first of our PegaWorld 18 series, I'm joined by Kirk Borne, Principal Data Scientist at management consulting firm Booz Allen Hamilton. In our conversation, Kirk shares his views on ...

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How a Global Energy Company Adopts ML & AI with Nicholas Osborn - TWiML Talk #150

How a Global Energy Company Adopts ML & AI with Nicholas Osborn - TWiML Talk #150

On today’s show I’m excited to share this interview with Nick Osborn, a longtime listener of the show and Leader of the Global Machine Learning Project Management Office at AES Corporation, a Fortune ...

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Problem Formulation for Machine Learning with Romer Rosales - TWiML Talk #149

Problem Formulation for Machine Learning with Romer Rosales - TWiML Talk #149

In this episode, i'm joined by Romer Rosales, Director of AI at LinkedIn. We begin with a discussion of graphical models and approximate probability inference, and he helps me make an important connec...

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AI for Materials Discovery with Greg Mulholland - TWiML Talk #148

AI for Materials Discovery with Greg Mulholland - TWiML Talk #148

In this episode I’m joined by Greg Mulholland, Founder and CEO of Citrine Informatics, which is applying AI to the discovery and development of new materials. Greg and I start out with an exploration ...

7 Juni 201842min

Data Innovation & AI at Capital One with Adam Wenchel - TWiML Talk #147

Data Innovation & AI at Capital One with Adam Wenchel - TWiML Talk #147

In this episode I’m joined by Adam Wenchel, vice president of AI and Data Innovation at Capital One, to discuss how Machine Learning & AI are being integrated into their day-to-day practices, and how ...

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Deep Gradient Compression for Distributed Training with Song Han - TWiML Talk #146

Deep Gradient Compression for Distributed Training with Song Han - TWiML Talk #146

On today’s show I chat with Song Han, assistant professor in MIT’s EECS department, about his research on Deep Gradient Compression. In our conversation, we explore the challenge of distributed traini...

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Masked Autoregressive Flow for Density Estimation with George Papamakarios - TWiML Talk #145

Masked Autoregressive Flow for Density Estimation with George Papamakarios - TWiML Talk #145

In this episode, University of Edinburgh Phd student George Papamakarios and I discuss his paper “Masked Autoregressive Flow for Density Estimation.” George walks us through the idea of Masked Autoreg...

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Training Data for Computer Vision at Figure Eight with Qazaleh Mirsharif - TWiML Talk #144

Training Data for Computer Vision at Figure Eight with Qazaleh Mirsharif - TWiML Talk #144

For today’s show, the last in our TrainAI series, I'm joined by Qazaleh Mirsharif, a machine learning scientist working on computer vision at Figure Eight. Qazaleh and I caught up at the TrainAI confe...

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