Preview: Humanloop for Large Language Models

Jordan Burgess

Today, we are announcing the preview of Humanloop for Large Language Models (LLMs).

LLMs like GPT-3 are a powerful and disruptive technology. With GPT-3, developers can integrate language-understanding AI in their applications with only a couple lines of code and some creative prompting. You can see impressive use cases of copy writing, intelligent summarisation, and even things like English to Regex and jargon to English.

However, there are many challenges between impressive demos and practical real-world applications. Off-the-shelf GPT-3 models can struggle with more specialized tasks that require domain knowledge or a specific style. Additionally, these models have reliability issues (there’s no guarantee it won’t generate incorrect or problematic outputs in response to certain inputs) and they can be too slow and expensive for certain use cases at scale.

Humanloop is helping tackle these issues. We’re currently helping companies that are building with GPT-3 create a systematic way to evaluate and improve their models. This makes them cheaper, faster and more reliable, while also providing you with a way to make your data a competitive advantage.

Sign up for the closed beta

If you’re building with GPT-3 or other large language model, sign up to be a part of our closed beta.

Please fill out this quick form or email us at for access.

Frequently asked questions
What is Humanloop?
What are LLMs (Large Language Models)?

About the author

Jordan Burgess
Cofounder and Chief Product Officer
Jordan Burgess is a co-founder and Chief Product Officer of Humanloop. He is inspired to build AI systems that transform how we interact with computers. He helped build the AI systems powering Alexa at Amazon, and was an early ML Engineer at Bloomsbury AI (acq. by Facebook). Jordan has an MPhil in Machine Learning from Cambridge and studied Engineering and Computer Science at MIT.
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