Key facts
- NTT is establishing an IOWN AI Fund with over 70 billion yen ($440 million) to invest in AI infrastructure.
- The fund will focus on startups developing photonics-electronics convergence, AI semiconductors, and AI models.
- NTT's IOWN initiative aims to create an All-Photonics Network (APN) for faster, lower-latency, and more energy-efficient data transmission.
- The APN technology promises up to 100 times lower power consumption and over 120 times greater transmission capacity compared to current networks.
- This strategic shift is driven by the slowdown in NTT's traditional telecom business and the increasing demands of AI workloads.
Japanese telecom giant NTT is significantly shifting its strategy to focus on AI infrastructure, data centers, and "value domains," moving away from its traditional, slower-growing telecom business. This pivot includes a substantial investment in next-generation optical networks through the establishment of the IOWN AI Fund, with assets exceeding 70 billion yen (approximately $440 million).
The fund aims to accelerate the global expansion of NTT's Innovative Optical and Wireless Network (IOWN) initiative, which centers on an All-Photonics Network (APN). This APN technology utilizes light instead of electricity for data transmission, promising dramatically lower power consumption, higher transmission capacity, and reduced latency—critical factors for the power-hungry and data-intensive demands of artificial intelligence.
NTT is collaborating with South Korea's SK Group and Taiwan's Chunghwa Telecom on this venture. The fund plans to invest in startups across North America, Asia, and Europe that are working on photonics-electronics convergence, AI semiconductors, and advanced AI models designed to leverage IOWN infrastructure. This strategic move positions NTT to address the growing bottlenecks in current network architectures that are struggling to keep pace with the rapid advancements in AI and generative models, which are driving up data center power consumption and demand for more efficient communication systems.