Closing the Loop Between AI Training and Inference with Lin Qiao - #742

Closing the Loop Between AI Training and Inference with Lin Qiao - #742

In this episode, we're joined by Lin Qiao, CEO and co-founder of Fireworks AI. Drawing on key lessons from her time building PyTorch, Lin shares her perspective on the modern generative AI development lifecycle. She explains why aligning training and inference systems is essential for creating a seamless, fast-moving production pipeline, preventing the friction that often stalls deployment. We explore the strategic shift from treating models as commodities to viewing them as core product assets. Lin details how post-training methods, like reinforcement fine-tuning (RFT), allow teams to leverage their own proprietary data to continuously improve these assets. Lin also breaks down the complex challenge of what she calls "3D optimization"—balancing cost, latency, and quality—and emphasizes the role of clear evaluation criteria to guide this process, moving beyond unreliable methods like "vibe checking." Finally, we discuss the path toward the future of AI development: designing a closed-loop system for automated model improvement, a vision made more attainable by the exciting convergence of open and closed-source model capabilities. The complete show notes for this episode can be found at https://twimlai.com/go/742.

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Training Data Locality and Chain-of-Thought Reasoning in LLMs with Ben Prystawski - #673

Training Data Locality and Chain-of-Thought Reasoning in LLMs with Ben Prystawski - #673

Today we’re joined by Ben Prystawski, a PhD student in the Department of Psychology at Stanford University working at the intersection of cognitive science and machine learning. Our conversation cente...

26 Helmi 202425min

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...

19 Helmi 202445min

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...

12 Helmi 20241h 5min

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

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