In the evolving landscape of AI for agriculture, the future lies in hyper-personalization and multimodal models. AI will increasingly use diverse data sources, which include images and videos, to offer personalized solutions. The focus is on enhancing localization, predicting trends, and addressing challenges, such as climate change and market fluctuations. As AI becomes more integrated, institutions should embrace its transformative potential to benefit smallholder farmers, ensure the services are tailored to their unique needs, and contribute to a more sustainable and resilient agriculture ecosystem.

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