Joe McKendrick

To address concerns about energy consumption, AI system providers are using research innovations and software and hardware improvements to increase energy efficiency.

The ability to observe, monitor, and if necessary, intervene in AI-driven processes in real time has become the most pronounced challenge for enterprises of all sizes in the months and years ahead.

The digital twin is not intended to serve up medical advice, but serves as a first-line awareness and educational tool that helps users better understand health topics, recognize when to seek real medical attention, and access trusted information in a non-intimidating way.

International standards provide guardrails for the responsible, safe and trustworthy development of AI, making them invaluable tools for regulators and policymakers worldwide.

Use of AI agents is transitioning from systems that learn from decisions to systems that learn to improve the decision environment itself.

Self-service needs to be viewed in context as part of an overall customer experience (CX) strategy that involves both humans and AI.

Addressing AI’s energy-guzzling nature all comes down to using artificial intelligence thoughtfully, according to a recent Accenture report.

The Digital Twin Consortium’s AI Agent Capabilities Periodic Table is a framework that offers a standardized approach for evaluating AI agent systems based on actual capabilities.

Manufacturers find that the integration of digital twins, AI, and simulation technologies supports advanced plant modeling, simulation, planning, and operations management.

Cobots are engineered for seamless human-machine interaction, offering advanced motion control, real-time reprogramming, and dynamic task execution.

Digital twins are expected to become commonplace by 2035. However, implementing them may require resources and expertise that may not be available to many companies.

Physical AI promises to reinvent industrial automation with more efficient ways to train and control entire digital workforces of autonomous mobile robots.