Code Interpreter

Language Agents: From Reasoning to Acting — with Shunyu Yao of OpenAI, Harrison Chase of LangGraph

Sep 27, 2024 · 1:26:33

Shunyu Yao of OpenAI and Harrison Chase of LangChain discuss the evolution of language agents, arguing that combining reasoning and acting through techniques like ReAct remains foundational, while tool design and cognitive architectures like CoALA will shape the next wave. Shunyu traces his work from text games to ReAct, showing how thinking as an action improves reliability; Harrison explains LangChain's adoption and the shift to LangGraph for stateful orchestration. They emphasize agent-computer interfaces (ACI) as a neglected area, noting that SWE-Agent's success came from optimizing tools for models, not humans. The conversation covers memory types (semantic, episodic, procedural) and applies CoALA's three dimensions to current systems. They highlight promising applications: customer support, coding agents, and spreadsheet-style UX for batch operations. Shunyu stresses that better benchmarks like SWE-Bench (which solved 30% of GitHub issues) and TauBench (best model 48%) are critical, and that data—not architecture—will drive future model improvements.

Building AGI with OpenAI's Structured Outputs API

Sep 17, 2024 · 1:12:23

Michelle, OpenAI's API tech lead, explains how the newly launched Structured Outputs feature achieves near-100% reliability for schema-following outputs by combining constrained decoding with model training, moving beyond the limitations of JSON mode and Function Calling. She details the refusal field that allows the model to decline harmful requests while maintaining parseable output, and discusses use cases like dynamic UI generation and mathematical chain-of-thought. The roadmap includes parallel function calling and custom grammars. The episode also covers the GA of GPT-4o fine-tuning, Batch API's 50% cost savings, Vision API integration with structured outputs, the Whisper API's surprising lack of diarization, and the shift toward speech-to-speech APIs. Michelle shares insights from her Waterloo co-op background and what qualities succeed at OpenAI: low ego, user-focused, and driven.