MBZUAI and MIT Launch AI Research Collaboration
The Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) and MIT Schwarzman College of Computing have launched a collaborative research program to advance artificial intelligence across various domains. Announced in a press release, the MIT–MBZUAI Collaborative Research Program aims to strengthen AI's technological foundations and accelerate its application in scientific discovery, human thriving, and planetary health.
This partnership will see faculty, students, and research staff from both institutions working together on high-impact projects. Each project will be jointly led by a principal investigator from MBZUAI and MIT. The program is directed by Le Song, Professor of Machine Learning at MBZUAI, and Philip Isola, Class of 1948 Career Development Professor at MIT.
The collaboration aligns with the goals of the MIT Schwarzman College of Computing to advance computing across disciplines and address the social and ethical responsibilities of AI. It also supports the UAE's mission to become a global hub for high-impact AI innovation. The initiative will focus on areas such as health, robotics, and efficient computing, aiming to create a transcontinental bridge for AI discovery and application.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Enterprise AI Brief or Daily AI Brief.
Also, consider following us on social media:
More from Enterprise
Oct 16 BOC Group Adds AI Assistant to ADOIT 21 Oct 16 Huawei Brings Upgraded Stellar Network Solution to Europe Oct 16 Element to Manage Waymo's Toronto Fleet for 2028 Launch Oct 16 CTM and Huawei Plan AI Network Security Upgrades in Macao Oct 16 Huawei and 14 partners form Global AI CITY allianceEnterprise AI Brief
Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Canada and Germany Commit Up to C$300 Million to LawZero
Huawei Launches AI Practice LAB for University Teaching
Ohio State and Google Partner on AI Research Hub
INSEAD AI Forum Examines Automation and Human Skills
Mashreq Pilots IBM Bob for Software Engineering
Daily AI Brief: the AI news that matters, in your inbox.