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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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 Kesä 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 ...

4 Kesä 201845min

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...

31 Touko 201846min

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...

28 Touko 201834min

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...

25 Touko 201821min

Agile Data Science with Sarah Aerni - TWiML Talk #143

Agile Data Science with Sarah Aerni - TWiML Talk #143

Today we continue our TrainAI series with Sarah Aerni, Director of Data Science at Salesforce Einstein. Sarah and I sat down at the TrainAI conference to discuss her talk “Notes from the Field: The Pl...

24 Touko 201838min

Tensor Operations for Machine Learning with Anima Anandkumar - TWiML Talk #142

Tensor Operations for Machine Learning with Anima Anandkumar - TWiML Talk #142

In this episode of our TrainAI series, I sit down with Anima Anandkumar, Bren Professor at Caltech and Principal Scientist with Amazon Web Services. Anima joined me to discuss the research coming out ...

23 Touko 201834min

Deep Learning for Live-Cell Imaging with David Van Valen - TWiML Talk #141

Deep Learning for Live-Cell Imaging with David Van Valen - TWiML Talk #141

In today’s show, I sit down with David Van Valen, assistant professor of Bioengineering & Biology at Caltech. David joined me after his talk at the Figure Eight TrainAI conference to chat about his re...

22 Touko 201837min

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