AI Is Getting Scary Good at Making Predictions

At the end of 2024, no AI had even managed to place 100th in one of the major competitions. But they have since vaulted up ...

Beyond the lakehouse: Fundamental's NEXUS bypasses manual ETL with a native foundation model for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.

Fundamental emerges from stealth with first major foundation model trained for tabular data

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

Why World Models Like Google’s Project Genie Work

Google's Genie generates infinite interactive worlds from text. The secret? AI models compress reality's rules into ...
GitHub

Imprecise Probabilistic Machine Learning

“There are known knowns. There are known unknowns. But there are also unknown unknowns—things we do not yet realize we do not know.”—Donald Rumsfeld (2002) While modern machine learning (ML) ...
IEEE

Mobility-Aware Bivariate Line-of-Sight Probability for Air-to-Ground Communications Using Millimeter and Terahertz Waves

Abstract: This paper presents a mobility-aware bivariate line-of-sight (LoS) probability model for millimeter waves and terahertz air-to-ground communication. Current literature does not provide LoS ...
IEEE

Wind Power Probability Model Based on Spatiotemporal Correlation

Abstract: In this paper, a method to establish the output probability distribution model of wind farm is proposed. According to the spatiotemporal characteristics of wind, the time and space ...
GitHub

NASA-IMPACT/Prithvi-EO-2.0

Prithvi-EO-2.0 is based on the ViT architecture, pretrained using a masked autoencoder (MAE) approach, with two major modifications as shown in the figure below. Second, we considered geolocation ...