Speculations on Test-Time Scaling for Large Language Models (o1)
This talk surveys the emergent literature on test-time compute as a scaling axis for large language models, drawing connections to OpenAI's o1 research. It examines how increases in test-time computation can yield predictable improvements in accuracy, akin to parameter and data scaling.
