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 ...
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 ...
VentureBeat

IBM Granite 3.2 uses conditional reasoning, time series forecasting and document vision to tackle challenging enterprise use cases

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now In the wake of the disruptive debut of ...
JSTOR Daily

Sampling the Future: A Bayesian Approach to Forecasting from Univariate Time Series Models

The Box-Jenkins methodology for modeling and forecasting from univariate time series models has long been considered a standard to which other forecasting techniques have been compared. To a Bayesian ...
Óstáilte ar MSN

IBM Launches New AI Model Designed for Time-Series Forecasting

Tech giant IBM (IBM) has launched a new AI model called FlowState, which is designed to make accurate predictions using time-series data. For reference, this type of data is used to forecast ...