Japan’s Preferred Networks and AI-chip developer Tenstorrent have been selected for a five-year Japanese government-backed research project to develop an advanced computing platform that combines chiplets, photonics-electronics integration and advanced packaging.
The companies will work on an extensible processing unit, or xPU, architecture under a program administered by Japan’s New Energy and Industrial Technology Development Organization. NEDO announced the selected implementation structure on October 20, 2026, under its post-5G information and communications infrastructure initiative.
Project divides work across AI and CPU chiplets
Preferred Networks will lead development of AI chiplets, including designs that use three-dimensional memory stacking. Tenstorrent will develop open-architecture CPU chiplets with support for confidential-computing features, according to the joint announcement.
The project aims to connect multiple specialized chiplets through photonics-electronics integration and advanced packaging. Optical links can move data with lower electrical losses over some distances than conventional copper connections, while chiplet designs allow processors, memory and interface components to be developed separately and assembled into a larger system.
For AI systems, those approaches could help address bandwidth and power constraints created by rapidly growing models and data volumes. The work is still research and development, however, and the announcement did not disclose a commercialization timetable, target manufacturing process, foundry arrangement, prototype performance or funding amount.
Universities and research institutes join the effort
The companies said the University of Tokyo, Kobe University, Toyo University, the Japan Agency for Marine-Earth Science and Technology, the Japan Atomic Energy Agency and Tenstorrent Japan will participate as subcontractors.
The mix gives the project access to semiconductor, systems, security and scientific-computing expertise. Research workloads from marine science and nuclear-energy organizations could also provide demanding use cases for evaluating bandwidth, reliability and confidential-computing capabilities.
NEDO lists the project period as up to 60 months. Selection under the program establishes the research framework but does not guarantee that a resulting processor will reach commercial production or win customers. Development will have to integrate components from multiple teams, demonstrate manufacturability and produce software that can use the hardware efficiently.
Open architecture broadens the competitive angle
Tenstorrent designs AI accelerators and CPU cores based on the open RISC-V instruction set. Its role in the NEDO project extends that strategy into a Japanese research program focused on next-generation infrastructure and domestic technology capabilities.
The selection follows Tenstorrent’s October financing round, when the company raised $1.5 billion at a $6.2 billion post-money valuation. The fresh capital is intended to expand hardware, software and intellectual-property operations, but the NEDO collaboration is a separate research award and the companies did not link a specific portion of the funding to it.
Preferred Networks has developed processors and computing systems for deep learning and other high-performance workloads. The Japanese company also works on software and industry applications, giving it experience across the stack that could help connect chiplet design choices with model and systems requirements.
The project arrives as governments and technology companies seek alternatives to tightly integrated, proprietary AI-computing platforms. Chiplets and open instruction sets can give system builders more flexibility, but they shift more responsibility to interconnects, packaging, compilers and software compatibility.