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Where quantum meets AI: joining the Sustainable Quantum AI Research Center (SQAI), a centre selected under JST's Program on Open Innovation Platform for Industry-academia Co-creation

2026.11.05

Arterect Inc. has joined the Sustainable Quantum AI Research Center (SQAI), where academia, government and industry work together. Through its research activities, beginning with Research Theme 1, Quantum Machine Learning, we will pursue research and development where quantum technology and AI meet.

About SQAI

SQAI is a centre selected under the Japan Science and Technology Agency (JST) Program on Open Innovation Platform for Industry-academia Co-creation.

Program on Open Innovation Platform for Industry-academia Co-creation | Japan Science and Technology AgencyA JST programme in which consortia of universities, national research institutes, companies and local governments carry out joint industry-academia research.

www.jst.go.jp · Japanese

The Center of Innovation for Sustainable Quantum AI (SQAI) is a quantum AI research centre built on collaboration between academia, government and industry. Its participants include the University of Tokyo, Keio University, RIKEN, the Okinawa Institute of Science and Technology Graduate University, the University of Chicago, the City of Kawasaki and a large number of companies. With a main site in Hongo, Tokyo, and a satellite site in Kawasaki, SQAI aims to create quantum AI technology that combines quantum machine learning, quantum simulation and quantum sensing devices, and to build a quantum HPC platform through which anyone can use quantum AI seamlessly.

An illustration of researchers looking at a quantum computer in a glass enclosure, in a sunlit research space overlooking green trees and blue sky. — An illustrative vision of quantum research, inspired by IBM Quantum System One in Shin-Kawasaki. Equipment details, architecture and people are fictional; this is not a depiction of the actual facility or a visit.

SQAI works on five research themes:

Theme 1: Quantum machine learning
Theme 2: Quantum simulation
Theme 3: Quantum embedding
Theme 4: Quantum optimisation
Theme 5: Quantum HPC

Quantum machine learning: Research learning methods using quantum representations and quantum data. / Quantum simulation: Combine quantum and classical computation to simulate molecules, solids and nuclei. / Quantum embedding: Connect data representations between classical and quantum computing. / Quantum optimisation: Study optimisation methods suited to the problem and computing hardware. / Quantum HPC: Develop infrastructure connecting quantum computers, supercomputers and other systems. — A summary of SQAI’s official research descriptions. It does not imply our participation in all five themes.This illustration summarises the official descriptions published by the Center of Innovation for Sustainable Quantum AI (SQAI): Research Theme 1: Quantum machine learning; Research Theme 2: Quantum simulation; Research Theme 3: Quantum embedding; Research Theme 4: Quantum optimisation; Research Theme 5: Quantum HPC. Follow each link to read the full description of that research theme.

Research Theme 1: Quantum Machine Learning

This theme uses the vast representational space of quantum computers to build machine-learning models that generalise well at a lower training cost than before. It also studies new machine-learning methods that take quantum data from quantum simulations and quantum devices directly as input.

Our approach

Why we joined

As we research and develop AI, starting with our language model Cardinal LLM, we have made the connection to quantum technology one of the pillars of that work. Quantum computers may be able to take on calculations that today's computers cannot finish in a realistic time, and they could change how AI is trained and how it reasons.

Quantum research, however, is still at an early stage of development, and there is a limit to what any one company can do on its own. To widen the scope of our work, we believed we needed to exchange information broadly with universities and other research institutions, and with companies that have a track record in or an interest in quantum technology, and to take part in the research itself. With that in mind, we had been considering joining an external organisation, and we have now joined SQAI, which brings academia, government and industry together to research quantum AI and put it to use.

An illustration of researchers and representatives from industry and government exchanging ideas outside AIRBIC, with its distinctive white vertical fins. — Connecting one company’s knowledge with universities, industry and government. This illustration is inspired by the exterior of AIRBIC, a venue for SQAI Shin-Kawasaki satellite activities, and depicts people with different areas of expertise meeting to exchange ideas. The people and interaction are fictional. The architecture is based on the official AIRBIC facility introduction; its role as an activity venue is documented in SQAI’s official announcement of its quantum programming workshop.

Applying the research to AI

Looking ahead, we see possible applications in fields where the task is to narrow a vast number of candidates down to the promising few, such as the search for new materials and medicines, and in Cardinal LLM itself. We will apply what we know about AI to quantum research, and bring what we learn from quantum research back into our AI research and development. Through that exchange, we will carry the results into our business and into real-world use.

Taking it into education

For all its potential, quantum technology is still unfamiliar to most people. Education is also a major focus for us, and we will draw on what we learn in research to create teaching materials and learning opportunities that explain quantum technology more clearly. By giving students and businesses more chances to encounter quantum technology, we aim to help develop the people who will lead the next era.

Comment from our CEO

"Quantum research is still developing, and there is only so much a single company can do on its own. That is exactly why we are honoured to learn and carry out research together with partners from academia, government and industry at SQAI. Drawing on what we have built up in AI research and development, we will contribute to bringing useful technology to society from both the quantum and the AI side."

— Hayate Esaki, Representative Director and CEO

AI research: Bring knowledge from Cardinal LLM and other AI work into quantum research. / Quantum research: Bring insights from quantum machine learning back into AI research. / Explore applications: Explore potential uses in materials, drug discovery and Cardinal LLM. / Learning opportunities: Turn research insights into learning materials and opportunities. — Research directions and possible applications described in this article, not demonstrated results.

Looking ahead

AI is at the centre of our business, which spans education, security, games, sports and research and development. We will keep working with partners across academia, government and industry to create new value from the combination of quantum technology and generative AI.

Thank you for your continued support of Arterect Inc.

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