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 ...
IEEE

Corrections to “Data Mode Related Interpretable Transformer Network for Predictive Modeling and Key Sample Analysis in Industrial Processes”

Abstract: In [1], to maintain the integrity of the publication and uphold academic standards, a correction is requested for an identified error. Fig. 12 in the ...
Scientific Research Publishing

Safety Leadership and Safety Performance: An integrative Model for Ghanaian Construction Industry ()

Safety Leadership, Worker Behaviour, Safety Performance, Integrative Model, Ghanaian Construction Industry Share and Cite: ...
Elektroniknet

Edge AI needs software, not just powerful hardware

In an interview with Markt & Technik, Rich Simoncic, Microchip Technology's COO, explains that edge AI tends to fail more due ...
Central Banking

Regtech and suptech in central banks 2026 case studies: Part one – research and investment priorities

Central Banking’s regtech and suptech interviews are in‑depth exploration of the pioneering work at central banks and ...
GitHub

An actuarial stochastic modeling library in python.

The Proteus Actuarial Library (PAL) is a fast, lightweight framework for building simulation-based actuarial and financial models. It handles complex statistical dependencies using copulas while ...
GitHub

Neural Graphics Model Gym

Please be aware that this is a beta release. Beta means that the product may not be functionally or feature complete. At this early phase the product is not yet expected to fully meet the quality, ...
IEEE

Data-Driven Linear Parameter-Varying Model Predictive Control for Unknown Nonlinear Systems

Abstract: This article proposes a data-driven linear parameter variation model predictive control (DDLPVMPC) method for unknown nonlinear (NL) systems. The approach eliminates reliance on prior ...