Forbes

IBM Improves Generative AI Forecasting Using Time, Not Just Attention

According to IBM, attention is not all you need when forecasting certain outcomes with generative AI. You also need time. Earlier this year, IBM made its open-source TinyTimeMixer (TTM) model ...
Crowdfund Insider

Sweden’s Riksbank Research : AI Models Outperforming Traditional Time Series Models in Predicting GDP, Inflation

Sweden’s central bank, the Riksbank, is embracing a transformative shift in economic forecasting, as recent findings from its Monetary Policy Department reveal that artificial intelligence (AI)-based ...
San Francisco Fed

The Anatomy of Out-of-Sample Forecasting Accuracy

We introduce the performance-based Shapley value (PBSV) to measure the contributions of individual predictors to the out-of-sample loss for time-series forecasting models. Our new metric allows a ...
ascopubs.org

Time Series Prediction of Lung Cancer Death Rates on the Basis of SEER Data

This study used SEER data from 1975 to 2018 and included 545,486 patients with lung cancer. The best parameters for ARIMA are ARIMA (p, d, q) = (0, 2, 2). In addition, the best parameter for SES was α ...
The Conversation

Inflation: I’ve been analysing the Bank of England’s forecasts over the past two years – here’s how they got it wrong

Costas Milas has received in the past funding by the Bank of England to work, as the principal investigator, on the project Liquidity and Output Growth in the UK. Costas Milas has received in the past ...
InfoWorld

5 ways companies can use time-series forecasting

Recent advances in AI, such as foundation models, make it possible for smaller companies to build custom models to make predictions, reduce uncertainty, and gain business advantage. Time series ...