With so much attention devoted to the purported wonders of predictive cognitive computing models (typically characterized by classic machine learning and deep learning), it’s easy to lose sight of the ...

Why Data Matters for AI Poor data quality and fragmented identity undermine predictive performance. TransUnion’s identity graph and enrichment capabilities provide the single source of truth AI ...

The efficient management of hospital resources, particularly in terms of bed utilisation and staff allocation, is increasingly critical in modern healthcare systems. Predictive modelling for hospital ...

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...

Theoretical and simulation estimates of turbulent transport (high-dimensional data that depend on plasma conditions such as density, temperature, and magnetic field) are used as low-fidelity data, and ...

The semiconductor industry, as always, is at the forefront of transformational technological innovation, driving escalating complexity of manufacturing processes that extend time-to-market delivery, ...

Predictive modeling technology is capable of sifting through massive data sets and uncovering the patterns and trends that correlate the target data elements to some outcome(s) of interest. Paul ...

John Readman is the CEO of ASK BOSCO, which gives online retailers and marketing agencies the power of AI predictive marketing analytics. Between 2010 and 2025, the total amount of data created across ...

With the addition of Scytec’s DataXchange software, Minitab extends its capabilities to collect comprehensive, real-time operational data from machines such as CNC (Computer Numerical Control) ...

The acquisition brings the firm’s regulation-ready rent data and AI-driven modeling to REBA’s operational analytics platform.

Five big data leaders - FICO, TDC, FFIV, SPGI and MCO - are leveraging AI, analytics and acquisitions to capture rising data ...