Generative AI: A 2-year retrospective and what's next

The development of generative artificial intelligence (AI) has made significant progress since its debut in 2022, with advancements in retrieval-augmented generation architectures, vector databases, and commercial solutions from leading cloud platforms. However, despite enthusiasm for generative AI, many organizations face challenges in implementing it successfully, including establishing robust data architecture, integrating data sources, and curating high-quality data to improve model performance. To overcome these obstacles, tools like Fivetran have emerged to provide a solid foundation for AI projects, enabling the creation of practical applications such as FivetranChat, an internal chatbot that has become an invaluable productivity aid for employees. As generative AI continues to evolve, it holds promise for powering continued innovation and discovery in various industries, making information more accessible and actionable than ever before.

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