If algorithms can track, classify, and predict behaviour at scale, can they also narrate a life before it is lived?

AI transformation cannot be "AI for everything." Successful enterprises focus on a limited set of high-impact use cases with measurable outcomes.

AI agents are powerful, but without a strong control plane and hard guardrails, they’re just one bad decision away from chaos.

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Evolution of intelligent automation enables enterprises to move beyond observing problems towards autonomously solving them ...

The stock exchange is using the artificial intelligence extensively throughout the organization, including in development of a distributed ledger for tokenized securities.

A new study reveals that the next generation of blockchain defenses will not rely on fixed rules alone but on adaptive, learning-based systems capable of evolving alongside intelligent adversaries.

First impressions matter. And when AI fails publicly, it doesn’t just fail a task, it erodes trust before the product ever has a second chance.

Real-world optimization problems often require an external “modeling engine” that computes fitnesses or data that are then input to an objective function. These programs often have much longer ...

QScreen AI Inc (CSE: QAI) (OTC Pink: PMEDF) (FSE: 3QP), an innovator fusing Quantum-AI technologies to transform health screening and employee wellness, today announced the filing of a provisional ...

The typical failure pattern is predictable. A treasury team deploys an AI forecasting tool, but forecasts are inaccurate and the vendor gets blamed. But if the organisation has five definitions of ...

Rumman Chowdhury said even where responsible AI teams survive leadership changes, their effectiveness depends on where they sit within an organisation — a question she said is rarely discussed.