Summary:
- This article discusses the challenge of nondeterminism in large language models (LLMs) during the inference process.
- Nondeterminism refers to the unpredictable and inconsistent outputs that can occur when running the same input through an LLM multiple times.
- The article explores techniques like temperature scaling and top-k sampling to help reduce nondeterminism and improve the reliability of LLM outputs.