What is Index Refreshing?
The process of updating retrieval system indices to reflect changes in the underlying data.
More about Index Refreshing:
Index Refreshing involves regularly updating the indices used by retrieval systems to ensure they reflect the latest changes in the underlying data. This process is critical for maintaining the accuracy and relevance of results in systems like semantic search or dense retrieval.
Index refreshing is especially important in dynamic environments where content frequently changes, such as news platforms, product catalogs, or live knowledge bases.
Frequently Asked Questions
Why is index refreshing important for retrieval systems?
It ensures that retrieval results remain accurate and up-to-date, improving user satisfaction and system reliability.
How is index refreshing implemented?
By periodically re-indexing data or incrementally updating indices when changes occur in the dataset.
From the blog
Custom model training and fine-tuning for GPT-3.5 Turbo
Today OpenAI announced that businesses and developers can now fine-tune GPT-3.5 Turbo using their own data. Find out how you can create a custom tuned model trained on your own data.
Herman Schutte
Founder
Create an AI version of yourself for your coaching business
Harnessing the power of Artificial Intelligence is no longer reserved for tech giants or sci-fi enthusiasts. As a coach, what if you could scale your expertise, offering guidance at any hour without extending your workday?
Herman Schutte
Founder