Health systems evaluating AI must look beyond datasets and algorithms to understand the assumptions and priorities embedded within the applications themselves.

Understand the problem first: Read the question carefully, identify inputs, outputs, and constraints before writing any code to avoid confusion and mistakes. Break complex problems into small steps: ...

Artificial intelligence and the internet of things are reshaping enterprise strategy across industries. From predictive ...

The study, “Conditions of benefits and risks when algorithmic technology is implemented for public sector policing and fraud detection: a systematic literature review,” published in AI & Society, ...

Most of you have used a navigation app like Google Maps for your travels at some point. These apps rely on algorithms that compute shortest paths through vast networks. Now imagine scaling that task ...

New reference architecture outlines a practical, scalable path for combining quantum and classical computingScientific breakthroughs in chemistry, materials science, and molecular simulation are ...

When fast-fashion giant Shein moved its headquarters to Singapore in 2022, the shift was widely seen as an attempt to distance the company from rising US-China tensions. The group presented itself as ...

DeepMind’s AlphaProof system solved four out of six problems at the 2024 International Mathematical Olympiad, generating ...

Some years ago, my linguistic research team and I started to develop a computational tool aimed at reconstructing the text of ...

A seemingly modest project, a stalled campaign or an almost-overlooked opportunity can reveal insights that shape how ...

As AI search becomes conversational, prompt patterns reveal how questions evolve and how content appears in search results and AI answers.

New research from the Complexity Science Hub (CSH) shows why widely used algorithms for measuring economic complexity produce trustworthy results ...