Evaluating models, agents, and efficiency metrics

Ryan welcomes Benjamin Klieger, lead engineer at Groq, to explore the infrastructure behind AI agents, how you can turn a one-minute agent into a ten-second agent, and how they used fast inference and effective evals to build their efficient and reliable Compound agent. 

Episode notes: 

Groq delivers fast, low-cost inference using their custom-designed LPU, the first chip built for inference. Check out their agent, Compound, which can search the web and run code.

Connect with Benjamin on LinkedIn and X. 

Congrats to user Bart Kiers for winning a Stellar Answer badge on their response to Regular expression to match a line that doesn't contain a word. 

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