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Longer Context Windows and Interaction with Environment in AI Models
Using longer context windows in AI models can make single-shot tasks more achievable, like extracting information from a long PDF document. However, for tasks that require interaction with the environment and multiple iterations, chaining and agents are necessary. In scenarios where reasoning over multiple information points is crucial, such as in the case of RAG models, the focus should be on developing models that can process and reason over multiple data points rather than just finding a single point of information.