From Cloud to Edge – The future of Artificial Intelligence
Dr. Krish Prabhu retired as Chief Technology Officer of AT&T, after a 40-year career covering the development and deployment of Optical Fiber, Wireless Networks, Internet Technology and Cloud Computing.
He started his career at Bell Laboratories in 1980, after getting a PhD in Electrical Engineering from the University of Pittsburgh.
He also has an MSc degree in Physics from IIT Bombay (1975).
Artificial intelligence (AI) loosely refers to the ability of a digital computer to perform tasks commonly associated with intelligent beings – the ability to reason, discover meaning, generalize, or learn from experience. Though the concept was first introduced in the 1930s, by 2020 progress in computing and networking led to deployment of AI in fields as diverse as medical diagnosis, computer search engines, voice or handwriting recognition, autonomous vehicles and chatbots. Today’s implementation is largely foused on deploying AI models and algorithms in cloud data centers.
Edge AI is a technology that deploys AI algorithms and models on edge devices such as smartphones, cameras, sensors, and robots, enabling data processing and decision-making at the end point. This approach avoids data transmission delays and privacy issues while improving response speed and security. The proliferation of 5G wireless networks makes it easier to interconnect billions of AI enabled smartphones and sensors, and millions of autonomous robots on a wide scale.
