Gemini API introduces a context caching feature that aims to assist users in retaining AI research findings by saving up to 70% on costs. The feature allows for the creation of apps like email summarization and chatting with favorite books.
LLM context caching unlocks just-in-time machine learning. Instead of training or fine-tuning, large context LLMs like Gemini can learn things on the fly (in context learning) and then you can cache that learnt skill — as this Replit demo shows. This is a lowkey game-changer. https://t.co/bJezB2bmy5
Gemini API context caching is here! 🎉 This is a HUGE win for Google devs! 🙌 https://t.co/kPJ6nAT5sj
I wanted everyone to experience the magic of Gemini caching, so I built a free app! Simply enter your API key and the file, and you can chat with it. 💬 I spent all night chatting with my favorite books. Gemini creativity combined with caching, it's amazing. Hosted on @Replit https://t.co/0ByeIGP3qn
We just dropped a game-changer to slash your Gemini API costs 🤯 Yesterday we launched Gemini Context Caching, saving you up to 70% on your bill 💸💸 Here's how it works. Gemini let’s you add powerful AI models to create apps like: 📧 Email apps that summarize entire threads… https://t.co/2BvfRHN3RB
The context caching feature for Gemini is really neat! As you all know, I write a lot and document AI research progress in lots of places. But I also tend to forget research findings due to the vast amount of papers I read so I wanted to try whether context caching can help me… https://t.co/EGPzweGvdd