At Bloomberg’s Technology and Innovation Forum in Singapore, the most useful conversation about quant research did not start ...

Open-source tools have made MMM more accessible, but reliable results still depend on clean data, thoughtful modeling, and ...

XL, dynamic interest modeling, and distributed stream computing to analyze large-scale e-commerce user behavior. By improving long-sequence prediction, real-time processing, and behavioral clustering, ...

Guest blog by Anthony Collins, Technical Director Data and Digital Competency Centre; Nathaniel Henman, Data Scientist; John ...

Researchers from the Oak Ridge National Laboratory, Cleveland Clinic and IBM announced a breakthrough on Monday that could ...

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

Despite C-suite optimism and more investment, there's a big gap between AI aspirations and enterprise readiness. The answer?

Data sovereignty has direct implications for regulatory compliance, legal authority and risk management for financial ...

Local AI inference at 32B-parameter quality, no cloud API required: University of Waterloo researchers released PAW on July 2 ...

Many AI initiatives fail not because of poor technology but because organizations lack shared definitions, context and ...

Model collapse AI training data risk grows as Meta’s Brand Memory ad tools flood the open web with synthetic content, ...

To make the shift from model-centric to systemic intelligence tangible, we use an autonomous order management system for machines as an example, through which customers can not only order but also ...