Japan’s Nippon Telegraph and Telephone (NTT) announced on 8 June that it will create an investment fund of more than 70 billion yen (about $440 million) to accelerate the deployment of its Innovative Optical and Wireless Network (IOWN) platform. The fund, named the IOWN AI Fund, will be jointly managed with South Korea’s SK Group and Taiwan’s Chunghwa Telecom, and will also involve the Development Bank of Japan.

According to a report by the Yomiuri Shimbun, the fund will target startups in North America, Asia and Europe that are developing technologies related to photonics‑electronics convergence, AI‑specific semiconductors and advanced AI models that can run on IOWN infrastructure. The initiative is intended to broaden the real‑world use of IOWN beyond the research and pilot projects that have already been underway.

IOWN is a next‑generation optical communications platform that uses light rather than electrical signals for data transmission inside chips and across networks. NTT introduced the concept in 2019 and has since formed the IOWN Global Forum with partners such as Intel and Sony. The forum, launched in 2020, brings together companies in telecommunications, semiconductors, data centers and cloud computing to develop standards and proof‑of‑concept demonstrations.

A key milestone for the partnership was the launch of an international IOWN optical link in 2024. The link connects Chunghwa Telecom’s data center in Taoyuan, Taiwan, with NTT’s research and development centre in Musashino, Tokyo. The two companies reported a one‑way latency of about 17 milliseconds over a distance of roughly 1,860 miles.

The IOWN AI Fund will also seek to leverage the strengths of each partner. For NTT, the collaboration offers a pathway to combine Japan’s optical communications expertise with SK Group’s semiconductor capabilities and Chunghwa Telecom’s network infrastructure. The Development Bank of Japan will provide financial support, while a range of other Japanese firms have expressed interest in investing. These include Mitsubishi UFJ Bank, Sumitomo Mitsui Banking Corp., Mizuho Bank, Sumitomo Mitsui Trust Bank, Toshiba, Sony Group and Fujitsu.

The fund’s focus on photonics‑electronics convergence is timely. Generative AI workloads are driving rapid growth in data‑center power consumption, and the industry is looking for ways to reduce energy use and communication delays. Photonics‑based data transmission can lower power requirements and increase bandwidth compared with traditional electrical interconnects.

In the broader AI semiconductor market, the United States‑based Nvidia remains the dominant player, while China’s Huawei is accelerating development of telecommunications equipment and AI chips. The IOWN initiative represents a shift in the region’s AI competition from model development toward the underlying infrastructure that supports large‑scale AI workloads.

The fund’s launch is part of a broader trend of cross‑border collaboration in AI infrastructure. SK Group’s participation signals its intent to invest in the physical layer of AI systems, a move that aligns with recent discussions between SK executives and leaders of other AI firms.

While the fund’s exact investment strategy and timeline have not yet been disclosed, the announcement underscores the growing importance of optical networking and photonics in the next phase of AI infrastructure development. The partnership also highlights the role of public‑private collaboration in advancing high‑performance computing technologies.

In the coming months, the IOWN AI Fund is expected to announce its first portfolio companies and to outline concrete plans for scaling IOWN technology in commercial data centers. The initiative will likely influence the pace at which optical networking and photonics‑based solutions are adopted in AI‑heavy workloads across the globe.

The fund’s creation marks a significant step toward integrating optical communications with AI‑specific hardware and software, potentially reshaping the architecture of future data centers and high‑performance computing systems.