How MIT and IBM are joining forces to redefine AI and quantum computing

A decade after launching the MIT-IBM Watson AI Lab, MIT and IBM have unveiled the MIT-IBM Computing Research Lab—a bold expansion that merges artificial intelligence with quantum computing to explore entirely new frontiers in computation.

The initiative builds on a legacy of collaboration that began with the Watson AI Lab in 2017, now evolving to meet the demands of a rapidly changing technological landscape where AI has become mainstream and quantum computing is on the cusp of practical impact. Together, MIT and IBM aim to redefine the mathematical foundations of both AI and quantum systems, paving the way for computational approaches that surpass the capabilities of today’s classical architectures.

“This lab will stand at the forefront of a new era in computing,” says Jay Gambetta, IBM Research director and IBM Fellow, who also serves as the IBM chair of the MIT-IBM Computing Research Lab. “By bringing together the brightest minds from MIT and IBM, we’re not just advancing models or algorithms—we’re reimagining how systems are built for a future where AI and quantum computing converge.”

Anantha Chandrakasan, MIT provost and former dean of the School of Engineering, echoes that vision: “For 10 years, this partnership has driven innovation, mentorship, and professional growth for researchers on both sides. The achievements so far set an ambitious benchmark for the next decade, and I’m excited to see where we go from here.”

A shared mission to redefine computation

The MIT-IBM Computing Research Lab will serve as a hub for joint research in AI, algorithms, and quantum computing, with a focus on hybrid systems that combine quantum hardware with classical computing and advanced AI methods. The lab’s agenda includes enhancing AI’s role in traditional computing while exploring small, efficient language models, novel AI paradigms, and enterprise-ready systems prioritizing reliability, transparency, and trust.

On the quantum front, the lab will develop new algorithms for complex problems in materials science, chemistry, and biology, targeting challenges that exceed the reach of classical systems. Simultaneously, it will rethink the mathematical underpinnings of machine learning, optimization, and simulations—areas where current approaches struggle to model dynamic systems with precision.

Research outcomes could have far-reaching implications, from more accurate weather and financial market predictions to optimized supply chains and breakthroughs in protein structure prediction for drug discovery. The lab’s work in optimization could also reduce risks in finance and improve predictive modeling across industries.

Bridging academic excellence and industrial leadership

The new lab aligns with two of MIT’s strategic initiatives—the MIT Generative AI Impact Consortium and the MIT Quantum Initiative—both designed to address global challenges through cutting-edge research. It also leverages IBM’s leadership in quantum computing, including its roadmap to deliver the world’s first fault-tolerant quantum computer by 2029 and its efforts to integrate quantum systems with high-performance computing and AI accelerators.

Beyond research, the lab will play a key role in training the next generation of computational scientists. Faculty and students across MIT’s departments will collaborate on projects that accelerate discoveries in the physical and life sciences, fostering interdisciplinary innovation.

A collaborative leadership structure

The lab will be co-directed by Aude Oliva, a senior research scientist at MIT’s Computer Science and Artificial Intelligence Laboratory, and David Cox, IBM’s vice president of AI Foundations. Each of the lab’s three focus areas—AI, algorithms, and quantum—will have dedicated leadership:

• AI: Co-led by Jacob Andreas, an associate professor in MIT’s Department of Electrical Engineering and Computer Science (EECS), and Kenney Ng, IBM Research principal research scientist and the MIT-IBM science program manager.
• Algorithms: Co-led by Vinod Vaikuntanathan, the Ford Foundation Professor of Engineering in EECS, and Vasileios Kalantzis, IBM Research senior research scientist.
• Quantum: Co-led by Aram Harrow, a professor of physics at MIT, and Hanhee Paik, IBM’s director of Quantum Algorithm Centers.

As AI and quantum computing converge, the MIT-IBM Computing Research Lab is poised to unlock solutions that redefine what’s possible in science, industry, and beyond. With a decade of momentum behind it, this next phase of collaboration could shape the technological landscape for years to come.