The biggest bottleneck in large language models

Large language models (LLMs) like OpenAI’s GPT-4 and Anthropic’s Claude 2 have captured the public’s imagination with their ability to generate human-like text. Enterprises are just as enthusiastic, with many exploring how to leverage LLMs to improve products and services. However, a major bottleneck is severely constraining the adoption of the most advanced LLMs in production environments: rate limits. There are ways to get past these rate limit toll booths, but real progress may not come without improvements in compute …