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.

Episoder(783)

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(2/5) Klustera - Location-Based Intelligence for Smarter Marketing - TWiML Talk #18

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(1/5) HelloVera - AI-Powered Customer Support  - TWiML Talk #18

(1/5) HelloVera - AI-Powered Customer Support - TWiML Talk #18

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This week my guest is Shubho Sengupta, Research Scientist at Baidu. I had the pleasure of meeting Shubho at the Rework Deep Learning Summit earlier this year, where he delivered a presentation on Syst...

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My guest this week is Dr. James McCaffrey, research engineer at Microsoft Research. James and I cover a ton of ground in this conversation, including recurrent neural nets (RNNs), convolutional neural...

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My guest this week is Brendan Frey, Professor of Engineering and Medicine at the University of Toronto and Co-Founder and CEO of the startup Deep Genomics. Brendan and I met at the Re-Work Deep Learni...

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