They say a man’s home is his castle but in days of olde was possibly not the most important building in many a man’s life. Now this may be a particularly British thing but there was indeed another ...

For microwave imaging, a machine learning model can perform extremely well in the laboratory. The antenna geometry is known. The breast models are controlled. The frequency range is fixed.

In the previous chapter, we explored Data Integrity Testing, which focused on ensuring that data remains accurate, complete, and consistent as it moves from the source system to the target environment ...

Our author, Antoine Aymer, CTO for Quality Engineering & Testing at Sogeti, explains in Part 3 of this five-part blog series that a “good” AI system cannot be measured by a single score. Organizations ...

In modern medicine, the most critical decisions are rarely made by a single physician. For complex conditions like oncology, hospitals rely on Multi-Disciplinary Teams (MDTs) or tumor boards. Here, ...

Over the last year, I have spent a lot of time thinking about what it actually takes to move Agentic AI from an impressive demo into something I would be comfortable putting inside an enterprise. The ...

A machine learning model can only be as certain as the answer it was taught to predict. If an algorithm is trained to detect a tumor, someone must first decide which measurements contain a tumor. If ...

In the first chapter of this series, we explored the importance of planning, preparation, and establishing a structured approach to data migration testing. Once the migration strategy has been defined ...

For years, the High-Performance Computing (HPC) conversation around AI has centered on training: bigger clusters, more GPUs, faster interconnects, all in service of getting a model from raw data to a ...