Engineering the future of AI research at scale
“Infrastructure bottlenecks have disappeared. When researchers need compute, it is available. Training cycles shorten and publication timelines accelerate.”
About MBZUAI
MBZUAI is a research-focused university in Abu Dhabi, and the first university dedicated entirely to the advancement of science through AI. The university empowers the next generation of AI leaders, driving innovation and impactful applications of AI through world-class education and interdisciplinary research. In 2025, MBZUAI launched its first ever undergraduate program, a Bachelor of Science in AI, with two distinct streams: Business and Engineering.
Frontier research places unique pressure on infrastructure.
Training frontier models like Jais and K2 requires massive computational scale, with thousands of GPUs working through distributed training frameworks on high-performance, low-latency networks, where milliseconds of delay compound across runs spanning days or weeks.
Scale alone was not sufficient. Different research workloads have different optimal compute profiles. Frontier model training demands NVIDIA clusters, large exploratory workloads run efficiently on AMD infrastructure, and high-throughput inference suits specialized architectures such as Cerebras. Research directions shift quickly, and workloads had to move across accelerators without reengineering.
Sovereignty added critical complexity. Models designed for national use cases, such as Arabic LLMs and climate intelligence, must be trained and stored to meet strict regulatory and security expectations. And the infrastructure had to keep up with academic timelines, with consistency across the entire pipeline from first experiment through full-scale training and production inference.
AI Cloud, the engine of discovery.
Core42 AI Cloud provided MBZUAI with a sovereign, heterogeneous compute fabric built for large-scale scientific workloads. The platform combines multiple accelerators and unified operations to support rapid experimentation and training in a single environment.
Multi-accelerator infrastructure
Unified platform layer
High-performance foundations
Research velocity, unleashed.
MBZUAI has trained and deployed multiple frontier models, each representing months of intensive computation compressed into timeframes that match the pace of AI research.
Jais
Jais Climate
K2
Specialized portfolio
Published research demonstrating computational capability rivaling top global institutions attracts the faculty and students who drive the next breakthroughs. Prospective faculty see infrastructure that enables rather than limits ambition, and students train on the same systems used by leading AI laboratories worldwide.
Each workload runs on the accelerator with the best performance and cost profile. AMD supports large exploratory research while NVIDIA clusters are reserved for frontier-scale training. At deployment scale, those efficiencies fund additional research projects, and complete sovereign control keeps research breakthroughs UAE and MBZUAI assets.