In a recent paper, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and co-author William Gilpin show that a deceptively ...

Oversimplifies trends and ignores real-world disruptions. Can’t predict economic downturns, competitor actions and shifts in customer behavior on its own. Ignores randomness; every forecast will have ...

Paying invoices sounds simple enough. A vendor creates an invoice and sends a bill, your team approves it, and the money goes out. In practice, though, invoice payments are where a lot of finance ...

Amid the myriad discussions about AI – from the astounding amount of money being spent by vendors and enterprises and the debate about actual ROI those businesses are getting to the technology’s ...

People are now betting on everything. Prediction markets are amplifying those signals. The timing of the U.S. government shutdown. The likelihood of Taylor Swift canceling a tour date. The exact day ...

With increasing uncertainties on both the generation and load sides in power systems, ultra-short-term load forecasting (USTLF) and risk assessment have become crucial for ensuring the secure and ...

Storm Agnes is seen over the Bay of Biscay offshore western Europe on 27 September 2023 in this image captured by the Flexible Combined Imager on the Meteosat Third Generation satellite. Credit: ...

A new study by Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) shows that training large language models (LLMs) for complex, autonomous tasks does not require massive datasets.

Every three months, participants in the Metaculus forecasting cup try to predict the future for a prize pot of about $5,000. Metaculus, a forecasting platform, poses questions of geopolitical ...

A team of researchers have developed a domain adaption framework capable of transferring knowledge from solar power plants with abundant data to plants that need to be trained without labelled data.