Organizations adopt embedded intelligence because of this systems-driven approach which enables their transformation from episodic innovation to embedded intelligence
As global demand for multi-platform brand experiences grows, IP licensing is becoming an increasingly sophisticated discipline requiring creative integration and operational expertise.
A rare aerial clash between Indian Rafales and Pakistani J-10Cs has drawn global attention amid rising regional tensions. The encounter is offering military analysts a real-world look at cutting-edge air-to-air missile performance.
Thodupunuri is positioning himself at the forefront of DevOps innovation by exploring how generative AI can revolutionize observability and automation.
Ravi Kumar explains Traditional healthcare often fails chronic disease patients because it relies on occasional doctor visits and generalized treatment plans
Anurag Bhagat said technology is just a medium through which human vision expresses itself. The heart and mind behind the machine will always be what truly drives innovation forward.
Ravi Sankar Thinnati Palanichamy said I understand how Power Apps can serve as a customizable front-end platform, integrating seamlessly with project servers and communication tools like Microsoft Teams, to create a unified, transparent process
Reddy Srikanth Madhuranthakam has become a cornerstone figure in the global movement toward privacy-preserving AI proving that it's not only possible to innovate responsibly, but that doing so creates stronger, more trustworthy systems for everyone.
Ganesh Vadlakonda stands out as a thought leader and practitioner in the field of responsible AI. His work bridges the technical challenges of mobile AI development with ethical considerations around privacy, transparency, and user agency
Arun Kumar Sandu's breakthrough work in cloud infrastructure, distributed systems, and machine learning has set a new industry standard, enabling organizations to build scalable, resilient, and high-performing systems.
Niranjana Gurushankar believes that formal verification, emulation platforms, and investment in automation will improve the efficiency of AI hardware development