Google’s Gemini API has introduced context caching to improve the efficiency of long context LLMs by reducing processing time and costs. This feature is explained in a video that covers how to use context caching, its impact on performance, and implementation details with examples.
The video provides links to resources such as Context Caching, Vertex AI, a notebook, and pricing information. It also offers a course on RAG Beyond Basics, as well as options to connect through Discord, buy coffee, support through Patreon, consulting services, and business contact information.
The timestamps in the video outline the key points covered, including the introduction to Google’s Context Caching, how it works, setting up the cache, cost and storage considerations, example implementation, creating and using the cache, managing cache metadata, and concluding with future prospects.
Additionally, the video lists other interesting videos on topics like LangChain, LLM, Midjourney, and AI Image Generation for further exploration. The video also provides a link to a pre-configured localGPT VM with a discount code and a signup for a newsletter related to localgpt.
Overall, the video serves as a comprehensive guide to understanding and utilizing Google’s context caching feature to enhance the performance of long context LLMs.
Source link
Source link: https://www.youtube.com/watch?v=KvwJtleXCtU