How Advanced Analytics Can Transform Institutions of Higher Learning

NVIDIA CUDA Cores are the parallel compute units driving AI and HPC workloads, with the H200 GPU representing their fullest expression. The H200 significantly boosts performance by providing 4.8 TB/s memory bandwidth, 141 GB HBM3e, and FP8 precision, ensuring CUDA Cores are continuously fed and highly utilised. Throughput, not theoretical FLOPs, is the true measure of CUDA Core effectiveness, with H200 enabling up to 380K tokens/sec for 70B FP8 LLMs. Proper architecture and orchestration are critical to keep these cores saturated, avoiding pitfalls like memory fragmentation and outdated builds. When optimised, H200 clusters deliver unmatched performance-to-cost ratios, showing gains of +81% in throughput and -38% in power cost, leading to significant ROI and business outcomes.

AI has the potential to dramatically reshape education through personalized learning experiences. Here’s what’s in store for the future.

With its more than 1 million active duty and millions more civilian personnel, the U.S. Department of Defense (DoD) makes a global impact. Its distributed assets protect billions of people in geographically dispersed countries. But with hundreds of thousands of assets, vehicles, and facilities in operation on any given day, its carbon footprint impacts the globe as well.

Business leaders across the world are coming to terms with the realities of a permanent hybrid work model, one in which many employees will work remotely on a permanent basis, at least part of the time. An astonishing 75% of global CEOs expect their office spaces to shrink as result, Forrester reports, where “70% of U.S. and European countries will pivot to a hybrid work model” even after COVID-19 subsides.

Digital technology is transforming 21st century warfare, where future victories will go to countries with the most sophisticated applications of artificial intelligence (AI), human augmentation, drone technology, and Big Data. In the United States, the growing closeness of private Silicon Valley startups