Foundation Models for Time Series

Time-series data permeates our world, pulsing through financial markets, meteorological patterns, sensor networks, and countless other domains. Despite their ubiquity, generative AI techniques for time-series remain far less explored compared to the well-established approaches in language, image, and audio processing. This presentation delves into the cutting-edge landscape of foundation models for time-series analysis. We will explore specialized neural architectures designed to unravel the complex temporal dynamics of sequential data and demonstrate how open-source models can unlock powerful predictive capabilities and insights. Further, we demonstrate semantic search over time-series using the open source vector database Milvus and how to build RAG and agentic systems with this. 👉 🔔 Subscribe like, share, and engage in the AI revolution! Want to stay ahead on AI? Then subscribe to ODSC today 🚀🧠- https://www.youtube.com/c/OpenDataSci... You can also follow ODSC on: LinkedIn -   / open-data-science   Twitter -   / _odsc   Facebook -   / opendatasci   Medium -   / odsc