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Explore the cutting-edge landscape of foundation models for time-series analysis in this 56-minute presentation from Open Data Science. Delve into specialized neural architectures designed to unravel the complex temporal dynamics of sequential data that permeate financial markets, meteorological patterns, sensor networks, and numerous other domains. Learn how open-source models can unlock powerful predictive capabilities and insights for time-series data, which remains less explored in generative AI compared to language, image, and audio processing. Discover techniques for semantic search over time-series using the open source vector database Milvus, and understand how to build RAG and agentic systems with these technologies. The presentation offers valuable insights for anyone looking to advance their understanding of AI applications for temporal data analysis.
