AI drives decision inputs: In 2025, both big pharma and small pharma use advanced predictive modeling, digital twins, and AI-powered analytics throughout R&D and regulatory processes. This reduces ...

In today’s rapidly evolving tech landscape, centralized architectural decision-making can become a bottleneck to delivery performance and innovation. Through stories from our own journey, we’ll share ...

Classic cybersecurity tools are nearly powerless against semantic attacks. Signature detection, hashing, and code audits all depend on identifying explicit changes in code or data, but meaning-level ...

Economists and psychologists work together to understand how human behavior impacts people's decision-making in the marketplace.

On one hand, we need raw materials such as copper for the transition to climate-friendly technologies, but on the other hand, ...

A black box model refers to the level of transparency involved with a very complex computer algorithm. Read on to learn more ...

AI-powered ‘data fabrics’ bring advanced capabilities to disaster response by unifying disparate data streams and bringing ...

An emerging approach in AI innovation is hybrid AI, which combines the scalability of machine learning (ML) with the ...

Yet, ironically, MAHA’s core concern—that the nation’s most seasoned public-health experts have been rendered senseless over ...

Quiq reports on key questions surrounding AI, covering its capabilities, risks, ethical challenges, and future implications ...

Even within AI systems, human direction continues to shape the outcome. People define the model’s parameters, select the data ...

To help asset managers substantiate their renovation decisions, TNO is developing a promising tool together with ...