AI Engineering Pitfalls with Chip Huyen - #715

AI Engineering Pitfalls with Chip Huyen - #715

Today, we're joined by Chip Huyen, independent researcher and writer to discuss her new book, “AI Engineering.” We dig into the definition of AI engineering, its key differences from traditional machine learning engineering, the common pitfalls encountered in engineering AI systems, and strategies to overcome them. We also explore how Chip defines AI agents, their current limitations and capabilities, and the critical role of effective planning and tool utilization in these systems. Additionally, Chip shares insights on the importance of evaluation in AI systems, highlighting the need for systematic processes, human oversight, and rigorous metrics and benchmarks. Finally, we touch on the impact of open-source models, the potential of synthetic data, and Chip’s predictions for the year ahead. The complete show notes for this episode can be found at https://twimlai.com/go/715.

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ML Models for Safety-Critical Systems with Lucas García - #705

ML Models for Safety-Critical Systems with Lucas García - #705

Today, we're joined by Lucas García, principal product manager for deep learning at MathWorks to discuss incorporating ML models into safety-critical systems. We begin by exploring the critical role o...

14 Loka 20241h 16min

AI Agents: Substance or Snake Oil with Arvind Narayanan - #704

AI Agents: Substance or Snake Oil with Arvind Narayanan - #704

Today, we're joined by Arvind Narayanan, professor of Computer Science at Princeton University to discuss his recent works, AI Agents That Matter and AI Snake Oil. In “AI Agents That Matter”, we explo...

7 Loka 202454min

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 comple...

30 Syys 202448min

Stealing Part of a Production Language Model with Nicholas Carlini - #702

Stealing Part of a Production Language Model with Nicholas Carlini - #702

Today, we're joined by Nicholas Carlini, research scientist at Google DeepMind to discuss adversarial machine learning and model security, focusing on his 2024 ICML best paper winner, “Stealing part o...

23 Syys 20241h 3min

Supercharging Developer Productivity with ChatGPT and Claude with Simon Willison - #701

Supercharging Developer Productivity with ChatGPT and Claude with Simon Willison - #701

Today, we're joined by Simon Willison, independent researcher and creator of Datasette to discuss the many ways software developers and engineers can take advantage of large language models (LLMs) to ...

16 Syys 20241h 14min

Automated Design of Agentic Systems with Shengran Hu - #700

Automated Design of Agentic Systems with Shengran Hu - #700

Today, we're joined by Shengran Hu, a PhD student at the University of British Columbia, to discuss Automated Design of Agentic Systems (ADAS), an approach focused on automatically creating agentic sy...

2 Syys 202459min

The EU AI Act and Mitigating Bias in Automated Decisioning with Peter van der Putten - #699

The EU AI Act and Mitigating Bias in Automated Decisioning with Peter van der Putten - #699

Today, we're joined by Peter van der Putten, director of the AI Lab at Pega and assistant professor of AI at Leiden University. We discuss the newly adopted European AI Act and the challenges of apply...

27 Elo 202445min

The Building Blocks of Agentic Systems with Harrison Chase - #698

The Building Blocks of Agentic Systems with Harrison Chase - #698

Today, we're joined by Harrison Chase, co-founder and CEO of LangChain to discuss LLM frameworks, agentic systems, RAG, evaluation, and more. We dig into the elements of a modern LLM framework, includ...

19 Elo 202459min

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