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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.
