Multi-modal Deep Learning for Complex Document Understanding with Doug Burdick - #541

Multi-modal Deep Learning for Complex Document Understanding with Doug Burdick - #541

Today we’re joined by Doug Burdick, a principal research staff member at IBM Research. In a recent interview, Doug’s colleague Yunyao Li joined us to talk through some of the broader enterprise NLP problems she’s working on. One of those problems is making documents machine consumable, especially with the traditionally archival file type, the PDF. That’s where Doug and his team come in. In our conversation, we discuss the multimodal approach they’ve taken to identify, interpret, contextualize and extract things like tables from a document, the challenges they’ve faced when dealing with the tables and how they evaluate the performance of models on tables. We also explore how he’s handled generalizing across different formats, how fine-tuning has to be in order to be effective, the problems that appear on the NLP side of things, and how deep learning models are being leveraged within the group. The complete show notes for this episode can be found at twimlai.com/go/541

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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. W...

22 Jan 202439min

Learning Transformer Programs with Dan Friedman - #667

Learning Transformer Programs with Dan Friedman - #667

Today, we continue our NeurIPS series with Dan Friedman, a PhD student in the Princeton NLP group. In our conversation, we explore his research on mechanistic interpretability for transformer models, ...

15 Jan 202438min

AI Trends 2024: Machine Learning & Deep Learning with Thomas Dietterich - #666

AI Trends 2024: Machine Learning & Deep Learning with Thomas Dietterich - #666

Today we continue our AI Trends 2024 series with a conversation with Thomas Dietterich, distinguished professor emeritus at Oregon State University. As you might expect, Large Language Models figured ...

8 Jan 20241h 5min

AI Trends 2024: Computer Vision with Naila Murray - #665

AI Trends 2024: Computer Vision with Naila Murray - #665

Today we kick off our AI Trends 2024 series with a conversation with Naila Murray, director of AI research at Meta. In our conversation with Naila, we dig into the latest trends and developments in th...

2 Jan 202452min

Are Vector DBs the Future Data Platform for AI? with Ed Anuff - #664

Are Vector DBs the Future Data Platform for AI? with Ed Anuff - #664

Today we’re joined by Ed Anuff, chief product officer at DataStax. In our conversation, we discuss Ed’s insights on RAG, vector databases, embedding models, and more. We dig into the underpinnings of ...

28 Dec 202348min

Quantizing Transformers by Helping Attention Heads Do Nothing with Markus Nagel - #663

Quantizing Transformers by Helping Attention Heads Do Nothing with Markus Nagel - #663

Today we’re joined by Markus Nagel, research scientist at Qualcomm AI Research, who helps us kick off our coverage of NeurIPS 2023. In our conversation with Markus, we cover his accepted papers at the...

26 Dec 202346min

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 disc...

22 Dec 202336min

Edutainment for AI and AWS PartyRock with Mike Miller - #661

Edutainment for AI and AWS PartyRock with Mike Miller - #661

Today we’re joined by Mike Miller, director of product at AWS responsible for the company’s “edutainment” products. In our conversation with Mike, we explore AWS PartyRock, a no-code generative AI app...

18 Dec 202329min

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