An important first milestone has been achieved, but challenges remain. The recent announcement by the National Institute of Standards and Technology (NIST) of its first three post-quantum cryptography (PQC) algorithms
Developing and deploying AI applications requires highly optimized infrastructure, including purpose-built GPU servers, a robust AI/ML software stack, and a lossless, low-latency network fabric. An AI cluster typically has four
The quantum internet is poised to revolutionize how we communicate, compute, and secure data. By leveraging the principles of quantum mechanics, it will enable unparalleled capabilities that extend beyond the
AI and ML (machine learning) have been in development for decades, but even with today’s rapid advancements, the technology continues to be fragmented, bespoke, and poorly understood. At Juniper Networks,
Intelligent load balancing of AI/ML workloads AI/ML workloads in data centers generate distinct traffic called “Elephant flows.” These large amounts of remote direct memory access (RDMA) traffic are typically produced
In the ever-evolving landscape of higher education artificial intelligence (AI), the University of Wyoming is working at the forefront of AI innovation. Using cutting-edge technology, the university is setting up
The StateRAMP organization has announced that Juniper Mist™ has earned the StateRAMP Authorized certification, demonstrating the highest level of compliance with all required security controls for moderate impact. Now state
It may be no surprise that as a CIO, the most discussed topic among my peers is artificial intelligence. But the banter isn’t only about the possibilities and where to
This is the first in a series of technical blogs that will outline the key role that networking plays in AI/ML workloads – specifically, training and inference workloads. In this
We all know to avoid rush hour whenever we can, but in an AI training cluster, it’s always rush hour. In our previous blog on AI cluster design with rail