Author(s): Salvatore Raieli Originally published on Towards AI. In-context length is the LLM’s secret weapon, but with long-context is all changingPhoto by Angely Acevedo on Unsplash It is better to know some of the questions than all of the answers. — James Thurber In-context learning (ICL) is one of the most fascinating phenomena of large language models (LLMs). Just provide a few examples and the models can understand the task and execute it with surprising accuracy. Moreover, you do not have to alter a parameter because ICL is performed in inference. What is and how does it work what makes Large Language Models so powerful towardsdatascience.com We still do not really know why it emerges during the training of LLMs but it is the key to the success of LLMs. With the emergence of the long context model, some researchers are beginning to think that it may be the alternative to fine-tuning. In other words, why not provide a large number of examples and let the model figure out what it needs to do? Is it really true that long-context LLMs are killing the RAG? levelup.gitconnected.com Although this is an attractive alternative we have no idea if it works. After all, the ICL study so far has been conducted only on models with a small context length (most of the models studied had no more than 4K context length)…. Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor. Published via Towards AI