Beyond Automation: How AI-Powered Robots Are Reshaping Our Physical World

AI-powered robots are transforming industries by bridging digital intelligence with the physical world. In 2025, these adaptive, multi-tasking machines enhance manufacturing, healthcare, and small businesses, enabling greater efficiency and collaboration. As they evolve, ethical considerations and equitable access remain crucial for a future where humans and robots thrive together.

Conference discusses the impact of artificial intelligence in diagnosing the causes of autism | Gulf Newspaper [Arabic]

The International Conference on Autism Research, under the patronage of Sheikh Khalid bin Zayed Al Nahyan, explores the transformative role of artificial intelligence in diagnosing autism. The event emphasizes collaboration and innovation, aiming to enhance the lives of individuals with autism through advanced research and tailored interventions.

Emotional robots: Can machines replace friends? – Emirates News [Arabic]

Emotional robots represent a significant advancement in artificial intelligence, designed to understand and interact with human emotions. While they can provide companionship and reduce feelings of loneliness, they lack the emotional depth and social intelligence of real friends, serving instead as tools to enhance, not replace, human relationships.

We must find future sources of income… The broader Samsung family bets on a cousin alliance [biz-plus] [Korean]

Samsung and CJ are collaborating on the development of AI-based humanoid logistics robots, marking a significant partnership after past conflicts. This alliance aims to enhance automation in the logistics industry, focusing on innovative technologies that can adapt to diverse product handling, potentially transforming the future of logistics operations.

AI-Enabled Prediction of Heart Failure Risk From Single-Lead Electrocardiograms [English]

A noise-adapted AI model for single-lead electrocardiograms (ECGs) effectively predicts heart failure risk, offering a scalable strategy for risk stratification. This study analyzed data from diverse cohorts, demonstrating that AI-ECG significantly improves risk assessment compared to traditional methods, highlighting its potential in community-based health monitoring.

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