ChatGPT

Large language models (LLMs) have become essential tools in various industries. While we previously discussed how to select the best LLM for your needs, we haven’t yet explored how to optimize LLMs for cost-efficient, production-ready setups. While there are a host of options for optimization, in this article, we’re going to explore options for optimizing LLMs including the usage of Open-Source, hardware selection as a strategy, and experiments driving our understanding of the benefits of modifying precision values. 

Struggling to create buyer personas? Discover how non-tech professionals can leverage AI to streamline the process. This post explores using ChatGPT to generate detailed personas and craft effective outreach messages. Learn how to optimize prompts and refine your approach for optimal results.

Our last post comparing Claude Opus vs GPT 4 highlighted Claude’s capabilities in areas such as summarization, spatial understanding, human-like writing style, and advanced knowledge.

Using LLMs to Create API Calls. Proxet answers the call to experiment - should data engineers be considered with this new use case for LLMs?

We’ve done the research and looked at benchmarks - read our analysis!

Explore the correlation between latency and token generation in Large Language Models. Learn how prompt size impacts response time.