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Notes on forecasting

7 notes

  1. LLMs and Agentic AI Systems for Smart Grids: A Tutorial on Architectures and Applications

    Source note · Jul 20, 2026 · ai, optimization, forecasting

    This paper discusses how large language models (LLMs) and agentic AI systems are being used in smart grids for tasks like forecasting, optimization, and control. The authors present a design principle called the…

  2. TopoBrick: Agentic Topology Sampling of Exogenous Variables for Zero-Shot Building IoT Forecasting

    Source note · Jul 7, 2026 · forecasting, knowledge graphs

    The paper introduces TopoBrick, a framework for zero-shot forecasting of Internet-of-Things (IoT) data in buildings, which does not require training and takes into account the physical topology, spatial hierarchy, and…

  3. TopoBrick: Agentic Topology Sampling of Exogenous Variables for Zero-Shot Building IoT Forecasting

    Source note · Jul 7, 2026 · ai, machine learning, forecasting

    The paper introduces TopoBrick, a new framework for forecasting IoT data in buildings without requiring training. It uses building knowledge graphs to create a structural skeleton and employs an agentic topology…

  4. When do prophets profit in prediction markets?

    Source note · Jul 7, 2026 · artificial intelligence, forecasting

    Researchers propose a betting strategy that ensures profit when a forecaster's predictions outperform market prices under certain conditions. The strategy is shown to be the only one with such a robust profitability…

  5. Human Capital, Not Model Benchmarks, Predicts Hybrid Intelligence in Forecasting

    Source note · Jul 2, 2026 · ai, forecasting

    The study shows that the effectiveness of human-AI collaboration in forecasting depends on specific forms of human capital such as perspective-taking, intellectual humility, and curiosity. Most people either deferred…

  6. Human Capital, Not Model Benchmarks, Predicts Hybrid Intelligence in Forecasting

    Source note · Jul 2, 2026 · ai, collaboration, forecasting

    The study examines the performance of human-AI collaboration in forecasting using real-money prediction markets as a benchmark. It finds that the effectiveness of this collaboration is dependent on a specific type of…

  7. Human Capital, Not Model Benchmarks, Predicts Hybrid Intelligence in Forecasting

    Source note · Jul 2, 2026 · ai, collaboration, forecasting

    A study using real-money prediction market Polymarket finds that the performance of human-AI collaboration in forecasting depends on specific forms of human capital such as perspective-taking, intellectual humility…

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