New Delhi is using AI for an array of services but a consolidated approach is needed for deeper adoption, write Twesh Mishra ...

Srinubabu Kilaru said Bringing version control and CI/CD into data pipelines changed how quickly we could respond to policy ...

That’s the aim of predictive cyber resilience (PCR)—an emerging approach to security built on intelligence, automation and ...

Explore the essential incident management tools tailored for CIOs in 2025, focusing on AI automation, downtime reduction, and improved operational efficiency. Uncover their features, pricing, and ...

Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...

In the race to deliver faster, smarter, and more resilient networks, CSP and telco leaders are finding a powerful ally in ...

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...

US researchers say a self-supervised machine-learning tool can identify long-term physical defects in solar assets weeks or years before conventional inspections, potentially reducing operations and ...

The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.

The more important question for the decade ahead is whether AI will merely concentrate power or serve to strengthen public ...

Overview: AI in financial services uses machine learning and automation to analyze data in real time, improving speed, accuracy, and decision-making across bank ...

AI is the ultimate force multiplier for cybercriminals, because it makes scams faster, cheaper, and more convincing at scale. It can automate tasks that criminals used to do manually—or would never ...