The release of Google's Gemini 1.5 Pro model has increased the context length to an astonishing 10 million Tokens. This breakthrough has triggered extensive discussions about the future direction of retrieval enhancement generation technology (RAG). Will the enhancement of long text input capabilities completely replace RAG technology? Or will RAG technology still play an important role? This article will provide an in-depth analysis of this and explore Google’s advantages in computing power and its impact on the industry.
The Gemini 1.5 Pro model released by Google increased the context length to 10 million Tokens, triggering industry discussions on the future of RAG technology. Some people think that long text input can replace RAG, but others think that RAG will still play an important role. Google's advantage in computing power puts it ahead of other companies in context-length exploration, which may have an impact on some startups.
The release of the Google Gemini 1.5 Pro model marks a huge leap in the information processing capabilities of AI models. Its impact on RAG technology and its potential impact on the entire AI industry deserve continued attention. In the future, long text processing and RAG technology may coexist and develop, jointly promoting the progress of AI technology.