AI Agents for Data Analysis with Shreya Shankar - #703

AI Agents for Data Analysis with Shreya Shankar - #703

Today, we're joined by Shreya Shankar, a PhD student at UC Berkeley to discuss DocETL, a declarative system for building and optimizing LLM-powered data processing pipelines for large-scale and complex document analysis tasks. We explore how DocETL's optimizer architecture works, the intricacies of building agentic systems for data processing, the current landscape of benchmarks for data processing tasks, how these differ from reasoning-based benchmarks, and the need for robust evaluation methods for human-in-the-loop LLM workflows. Additionally, Shreya shares real-world applications of DocETL, the importance of effective validation prompts, and building robust and fault-tolerant agentic systems. Lastly, we cover the need for benchmarks tailored to LLM-powered data processing tasks and the future directions for DocETL. The complete show notes for this episode can be found at https://twimlai.com/go/703.

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Reasoning Over Complex Documents with DocLLM with Armineh Nourbakhsh - #672

Reasoning Over Complex Documents with DocLLM with Armineh Nourbakhsh - #672

Today we're joined by Armineh Nourbakhsh of JP Morgan AI Research to discuss the development and capabilities of DocLLM, a layout-aware large language model for multimodal document understanding. Armi...

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Are Emergent Behaviors in LLMs an Illusion? with Sanmi Koyejo - #671

Are Emergent Behaviors in LLMs an Illusion? with Sanmi Koyejo - #671

Today we’re joined by Sanmi Koyejo, assistant professor at Stanford University, to continue our NeurIPS 2024 series. In our conversation, Sanmi discusses his two recent award-winning papers. First, we...

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AI Trends 2024: Reinforcement Learning in the Age of LLMs with Kamyar Azizzadenesheli - #670

AI Trends 2024: Reinforcement Learning in the Age of LLMs with Kamyar Azizzadenesheli - #670

Today we’re joined by Kamyar Azizzadenesheli, a staff researcher at Nvidia, to continue our AI Trends 2024 series. In our conversation, Kamyar updates us on the latest developments in reinforcement le...

5 Helmi 20241h 10min

Building and Deploying Real-World RAG Applications with Ram Sriharsha - #669

Building and Deploying Real-World RAG Applications with Ram Sriharsha - #669

Today we’re joined by Ram Sriharsha, VP of engineering at Pinecone. In our conversation, we dive into the topic of vector databases and retrieval augmented generation (RAG). We explore the trade-offs ...

29 Tammi 202435min

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 Tammi 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 Tammi 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 Tammi 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 Tammi 202452min

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