Join us this Sunday for our virtual workshop - a deep dive into data chunking strategies!
As GPT has a limited context window of around 4-8k tokens, breaking down data into smaller chunks becomes necessary. Our default approach is to divide the data into smaller, fixed-size chunks.
During this workshop, we will focus on improving the performance of your ChatGPT/LLM using the following data chunking strategies:
Chunking data into fixed sized smaller chunks
Creating a summary for each chunk
Generating potential questions/answers users might ask
Hypothetical Document Embeddings
Writing your own custom chunking strategies and applying it to all chunks
Prototyping efficient data loading and pre-processing strategies
Come collaborate with other AI engineers, data scientists, and ML engineers to discuss best practices and explore innovative techniques.
By the end of the workshop, you will have a solid understanding of how to implement advanced chunking strategies to improve the performance of your ChatGPT/LLM app.