Artificial Intelligence

Manufacturing has entered a new era, driven by advanced technologies that redefine traditional processes. Among the most transformative innovations is multimodal AI in manufacturing, a cutting-edge approach that combines data from various sources—visual, auditory, thermal, and more—to offer deeper insights and smarter automation. In the realm of quality

The future of healthcare is not just digital—it’s intelligent, adaptive, and deeply personalized. At the forefront of this transformation lies multimodal AI, a powerful advancement that is revolutionizing how we understand and treat individual patients. By seamlessly integrating diverse data sources—imaging, genomic sequences, EHRs, patient history, and

The rapid rise of artificial intelligence has already transformed multiple industries, but a groundbreaking evolution is gaining traction—Agentic AI. This next-generation AI goes beyond passive systems by enabling autonomous decision-making and self-directed task execution. When applied to business process automation, Agentic AI is unlocking new levels of efficiency, accuracy,

As AI becomes more embedded in our everyday experiences—think virtual assistants, recommendation engines, and AI chatbots—the need for responsible development has never been more critical. When it comes to agentic AI, or AI systems capable of autonomous decision-making, ensuring reliability and safety becomes even more important, especially in

In the fast-paced world of software development, the rise of artificial intelligence is bringing groundbreaking changes. One such innovation making waves is vibe coding. Unlike traditional programming methods that rely heavily on syntax and manual effort, vibe coding introduces a more intuitive, conversational approach—allowing developers to “speak” their code

When artificial intelligence (AI) continues to develop, it quickly becomes important to ensure privacy, security and credibility of the AI model. Large language models (LLMs), such as GPT -4, has shown remarkable abilities in natural language treatment. However, their complexity and large amounts of data are treated that raise concerns