Empromptu's "golden pipeline" approach tackles the last-mile data problem in agentic AI by integrating normalization directly into the application workflow — replacing weeks of manual data prep with ...

The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

Outside of tightly controlled environments, most robotic systems still struggle with reliability, generalization and cost. The gap between what we can demonstrate and what we can operate at scale ...

The degradation is subtle but cumulative. Tools that release frequent updates while training on datasets polluted with synthetic content show it most clearly. We’re training AI on AI output and acting ...

World models could revolutionise robotics by teaching AI physics. But data bottlenecks and infrastructure limits delay ...

Thomson Reuters Corp. is betting big on generative artificial intelligence, and it has the data foundation in place to do so. The global provider of professional information for the legal, accounting, ...

To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...

Mathematics, like many other scientific endeavors, is increasingly using artificial intelligence. Of course, math is the ...

AI’s future doesn’t depend on ever-larger models but on better, human-curated data. AI risks bias, hallucinations and irrelevance without expert oversight and high-quality training sets. AI is a paper ...