This podcast episode reflects on the year 2023, highlighting significant advancements in large language models (LLMs) and knowledge graphs, featuring insights from experts Tomasz Bratonic and Oskar Hane at Neo4j. The discussion traverses the evolution of LLMs from novelty to practical tool, the intricacies of fine-tuning models, and the challenges posed by vector search and embedding models. It also predicts the future of LLMs, emphasizing the importance of human interaction in maximizing their potential. Ultimately, the episode underscores the need for better user interfaces and tools in the rapidly evolving landscape of AI technology.
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