The Problem of Big Data in Small Context Windows (Part 2)

Published
Author
Dr. Phil Winder
CEO

An introduction to the challenge of fitting big data into the context windows of LLMs. In this second installment, discover the key strategies involved to improve your use of the context window. Subsequent articles will provide more examples.

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ChatGPT from Scratch: How to Train an Enterprise AI Assistant

Published
Author
Dr. Phil Winder
CEO

This is a video of a presentation investigating how large language models are built and how to use them, inspired by our large language model consulting work. First presented at GOTO Copenhagen in 2023, the video investigates the history, the technology, and the use of large language models. The demo at the end is borderline cringe, but it’s a fun and demonstrates how you would fine-tune a language model on your proprietary data.

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LLMs: RAG vs. Fine-Tuning

Published
Author
Dr. Phil Winder
CEO

Abstract When: Wed Mar 13, 2024 at 16:30 UTC Large language models are applicable to a wide variety of AI problems and many leverage private data to enable bespoke use cases. But how do you best take advantage of that data? Two approaches have gained traction. Retrieving data from a database to place in the context window (RAG) and fine-tuning. Both are capable of ingesting “knowledge”. But which should you use?

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