2024 REPORT

Report on NTT R&D Forum 2024 - IOWN Integral

NTT R&D Forum 2024 - IOWN Integral was held over five days from November 25 to 29, 2024.
The field of Innovative Optical and Wireless Network (IOWN), a next-generation information and communications infrastructure centered on optical technology, is steadily expanding from networks to artificial intelligence (AI), and continues to evolve toward the creation of a sustainable future society. The theme of NTT R&D Forum 2024 - IOWN Integral is “Integral,” which can mean both a math integral or “indispensable.” We incorporated these two aspects to symbolize the evolution of IOWN. The “integral” part means that IOWN will be applied to various fields and the pieces will accumulate, and the “indispensable” part means that IOWN will become “indispensable” to the Earth and humanity.
The technology exhibition was divided into three areas: “Research,” “Development,” and “Business,” and featured a total of 122 booths. The “Research” area showcased 49 research results across a wide range of fields, including networks, User Interface/User Experience (UI/UX), sustainability, security, bio/medical, and quantum. In the “Development” area, 52 examples of the latest research and practical applications related to generative AI and space were on display, with IOWN as the central focus. Furthermore, in the “Business” area, 21 initiatives by NTT Group companies were presented, showing the increasing real world implementation of IOWN.
This forum was organized as an invitation-only event by NTT Group companies, and was attended by a total of 19,261 people, exceeding last year’s attendance. The forum closed to great acclaim, with high expectations for the IOWN future.
Here we will report on the NTT R&D Forum 2024 - IOWN Integral event.

  • Talks
  • Exhibitions
  • Archives

Summary of the Talks

Three people took to the stage for the Keynote Speeches: NTT President and CEO Akira Shimada, NTT Research and Development Director Shingo Kinoshita, and NTT Senior Executive Vice President Katsuhiko Kawazoe. In addition, the technical seminar featured a panel discussion on the theme of “Next Generation AI,” bringing together experts from NTT, the University of Tokyo, Sakana AI, and the technology magazine WIRED Japan to discuss the direction in which AI should evolve. They confirmed the importance of collaboration, such as “moving from a single large-scale AI to the combination of multiple specialized AIs.” In addition, under the theme of “Photonics-electronics convergence technology and the future of supercomputers,” a dialogue was held between the representative of Preferred Networks (a company that has received acclaim for its exploration and achievements in deep learning software technology and computing infrastructure technology) and an NTT researcher who aims to solve societal problems using photonics-electronics convergence devices, starting with “reduced power consumption in the age of AI” and touching upon the very essence of computer architecture. Both the Keynote Speeches and the technical seminar were a great success, with attendees exceeding the capacity of the venue.

KEYNOTE SPEECH

Day1Monday, November 25 1:30-2:10PM

Solving real world problems with Industry AI Cloud: Powered by IOWN

Akira ShimadaPresident and CEO

In his Keynote Speech, NTT President and CEO Akira Shimada touched on the rapid spread of generative AI and its impact, while discussing the current state and challenges of AI use in companies, as well as new solutions proposed by NTT.
While more than 90 percent of companies in the United States have adopted AI, in Japan, the figure is still only around 60%. Furthermore, even in companies that have adopted it, it is primarily being used for general-purpose tasks, and fundamental changes such as expanding it to more specialized tasks or creating new services are yet to come.
Given this backdrop, President Shimada proposed the Industry AI Cloud concept as a platform for utilizing AI for highly specialized tasks in each industry. Specifically, he introduced efforts to create a society with zero traffic accidents in collaboration with Toyota, and the creation of a “virtual wholesale market” for agricultural product trading to optimize the entire food and agriculture value chain. In addition, in August 2024, we established a new company, NTT AI-CIX, which aims to achieve industry-wide transformation using AI technology. We have begun collaborating with Trial, a nationwide supermarket chain, to optimize supply chains in the retail and distribution industries, and are working to optimize areas such as shelf layout optimization and automated ordering.
On the other hand, the increased use of AI raises concerns about the issue of electricity. With an increase in power consumption on the horizon, NTT is working to advance its low-power, lightweight AI model “tsuzumi,” and to promote IOWN, which will create a low-power computing infrastructure.
Of particular note, the company has announced that it aims to create a Data Centric Infrastructure (DCI) board that incorporates photonics-electronics convergence devices in IOWN2.0, which will be launched in 2025. At the NTT Pavilion at the Expo 2025 Osaka, Kansai, Japan, we have announced that we will be implementing a server that aims to reduce power consumption to 1/8th of the current level, and will be providing an opportunity for visitors to try it out. In addition, Fujitsu unveiled an ambitious roadmap that calls for a gradual movement toward commercialization in 2026, optical communication between chips in 2028, and optical communication within semiconductor chips from 2032 onwards, ultimately aiming to reduce power consumption to 1/100th of the current level.
The Keynote Speech emphasized NTT’s vision of combining the Industry AI Cloud with IOWN to solve real world problems in a sustainable manner. It presented a concrete and achievable vision of the future, in which AI is promoted in the highly specialized areas of each industry, while providing solutions to the problem of increasing power consumption.

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Day2Tuesday, November 26 11:00-11:50AM

IOWN INTEGRAL

Shingo KinoshitaSenior Vice President

Shingo Kinoshita, Executive Officer and Director of Research and Development Planning at NTT, began his Keynote Speech by presenting an overview of the forum and the IOWN roadmap. The latter in particular demonstrated the gradual adoption of optical technology from IOWN 1.0 in the networking domain to the computing domain. The next version, IOWN 2.0, will implement optical wiring between server boards, IOWN 3.0 will implement it between packages, and IOWN 4.0 will implement it inside chips, tracing a steady path of evolution.
He also reported on the progress of All-Photonics Network (APN) in the current IOWN 1.0. He says the company has upgraded its APN service (was launched in March 2023) to guarantee bandwidth of up to 800 Gbit/s, the world's highest standard, expand its interface, and significantly reduce power consumption. Additionally, a proof-of-concept experiment demonstrated a low latency of just 17 ms over a long-distance connection of approximately 3,000 km between Japan and Taiwan. He also mentioned ultra-fast data backup using APN and the realization of highly efficient remote production through APN. He also revealed that in the future, they aim to achieve unparalleled transmission capacity and power efficiency through “on-demand optical path control,” which will enable multiple wavelengths to coexist within a single APN without colliding with each other.
In addition, Director Kinoshita also introduced the advances in NTT’s version of a Large Language Model(LLM) "tsuzumi." While maintaining its light weight and ability to run on one GPU and one CPU, the system has steadily improved in performance, including multi-modal support and improved contextual understanding. Of particular note is that it has been adopted by Microsoft Azure and Salesforce platforms, marking the first step towards global expansion. He also touched on examples such as the “AI agent” function for controlling a PC on behalf of the user, and demonstrated part of a vision for coexistence with AI where “tsuzumi” is utilized, including the implementation of an "AI constellation" that combines multiple LLMs to solve real world problems.
To conclude the Keynote Speech, he quoted the words of Goro Yoshida, the first director of NTT Laboratories: “Let us draw from the fountain of knowledge, conduct research, and commercialize it in order to provide concrete benefits to the world.” He emphasized the importance of a consistent approach across research, development, and real world implementation, and laid out three commitments: to establish its position as one of the world’s best research institutions, to ensure the commercialization of IOWN, and to achieve meaningful real world implementation.

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Day3Wednesday, November 27 10:50-11:30AM

Unlimited Innovation for a Global Sustainable Society by IOWN

Katsuhiko KawazoeSenior Executive Vice President

NTT Senior Executive Vice President Katsuhiko Kawazoe gave a presentation in English about NTT’s current status as a global company and its key technologies. He explained how the NTT Group has evolved into a global corporation with over 900 companies worldwide, with 45% of its employees working overseas, and that it has 17 research laboratories and 2,300 researchers engaged in cutting-edge research and development.
He noted that while enhancing ICT technology is essential in light of the crises modern society faces, particularly in light of climate change, natural disasters, and a divided world, there is also a new challenge: a sharp increase in electricity consumption due to an explosive increase in Internet traffic. He also predicts that data center power consumption will increase 13-fold by 2030. Vice President Kawazoe emphasized that IOWN is NTT’s concept for overcoming this limitation, and optical technology is the key. In 2019, we succeeded in developing the world’s first optical transistor, and this invention became the origin of the IOWN concept.
Vice President Kawazoe highlighted several use cases as examples of new capabilities that IOWN will bring. One of these is the use of AI to combat new cybersecurity threats. In particular, against attacks that combine botnets and advanced AI, he proposed a new form of defense in which multiple AIs work together in the IOWN APN to respond immediately.
He also touched on his efforts to create a society with zero traffic accidents in collaboration with Toyota. He made it clear that they aim to build a safe mobility society by combining three core technologies: real-time data collection, constant connectivity achieved through distributed computing infrastructure, and learning from diverse data using a mobility AI platform.
In addition, he also unveiled their vision for expanding IOWN’s capabilities from the ground to space. He said that by collaborating with SKY Perfect JSAT, they aim to build an independent network system in space and create an integrated space computing network that can instantly process and analyze data from observation satellites in space.
To conclude the Keynote Speech, he spoke about the capabilities that IOWN opens up for humanity, illustrated by a project to support the work of a DJ with ALS (amyotrophic lateral sclerosis). “Human potential is infinite,” he said, sharing with the audience his thoughts on creating a sustainable society.

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TECHNICAL SEMINAR

Day4Panel Discussion

Thursday, November 28 1:00-2:00PM

Next Generation AI

Susumu TakeuchiComputer and Data Science Laboratories
Senior Research Engineer, Supervisor

Yoichiro MiyakeProject Professor, Institute of Industrial Science, The University of Tokyo

Ren ItoCo-Founder and COO, Sakana AI

Michiaki MatsushimaHead of Educational Content, WIRED JAPAN

Moderated by WIRED Japan Editor-in-Chief Michiaki Matsushima, the panel discussion included the University of Tokyo Professor Yoichiro Miyake, Sakana AI COO Ren Ito, and Susumu Takeuchi, Senior Research Engineer at NTT Computer & Data Science Laboratories, in which they engaged in a lively discussion about the limitations of current LLMs and their future prospects.
At the beginning of the session, Mr. Matsushima framed the discussion with the question “how is it possible to live in a complex world while maintaining complexity,” using the term “technodiversity” proposed by Hong Kong philosopher Yuk Hui. In response, NTT Senior Research Engineer Takeuchi, based on the premise that a “silver bullet” technology probably does not exist, touched on the possibility that NTT could find new ways to utilize AI by using “reasonable LLMs with expert knowledge” that are superior in terms of computational costs and power consumption, and by creating “AI constellations” that allow different companies’ LLMs to discuss with each other.
Next, Mr. Ito expanded on the discussion, proposing the construction of “evolutionary model merging,” which he described as "embodiment of the concept of AI constellations," that connects Small Language Models (SMLs) to achieve performance comparable to LLMs. The method, called “Frankenstein merging,” combines existing models, by selecting the top 10 from 10,000 possible combinations and then repeating the process over multiple generations. Amazingly, they achieved performance equivalent to GPT-3.5 in just 24 hours and with $24. He presented technology that automates human workflows based on these techniques, such as examples of its use in writing academic papers. They succeeded in automating the entire process, from crafting an idea to proof, paper writing, and peer review. This was the first AI-based achievement to be featured in Nature magazine, attracting a great deal of attention.
From the perspective of expanding AI models, Professor Miyake presented three important categories based on his experience developing game AI. There is the “meta AI” that controls the game as a whole, the “character AI” that acts as the brain of the character, and the “spatial AI” that assists with real-space recognition. What is particularly noteworthy is that these techniques go beyond simple uses within games; they also contain implications for urban design and the creation of smart cities. For example, a cyclical approach in which information from real space is collected and analyzed using a digital twin, and the results are then fed back into real space, should strongly boost future urban development.
In the second half of the session, there was an in-depth discussion about the direction AI is evolving in. Mr. Ito pointed to the improvement of “reasoning” abilities (logical thinking and inference) as an important turning point in the current development of AI, and noted that this will be the key to enabling AIs to communicate with each other and perform simulations. He also predicted that the first stage in using AI would be to improve task efficiency, followed by a stage where it would be used as a sounding board to bounce ideas off.
Professor Miyake made an interesting proposal regarding the possibilities of using AI to simulate meetings. He suggested the potential for AI to exhaustively simulate options and branching points that are often overlooked in traditional meetings, supporting better decision-making. He presented the possibility of a new approach, in which AI would hold a meeting before the actual meeting, and then humans would hold a discussion based on the results.
Regarding the future relationship between AI and humans, Senior Research Engineer Takeuchi pointed out its affinity with the Japanese concept of “eight million gods.” He envisioned a future in which AI with a variety of roles will be omnipresent and coexist with humans. In particular, he emphasized that with generative AI technology, system integration that has previously only been discussed theoretically is now becoming a reality with more concrete and advanced services.
What emerged from the discussion among the three panelists was the form that next-generation AI should take. This future will not be dominated by a single large-scale AI. Instead, AIs with a wide variety of expertise will work together to support human creativity and jointly seek solutions that embrace diverse values and perspectives.

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Day5Panel Discussion

Friday, November 29 1:00-2:00PM

The Future of Photonics-Electronics Convergence Technology and Supercomputers

Shinji MatsuoDevice Technology Laboratories / Basic Research Laboratories
Fellow

Toru NishikawaRepresentative Director & Chief Executive Officer, Preferred Networks

In a seminar held by Shinji Matsuo, Fellow at NTT Device Technology Laboratories and NTT Basic Research Laboratories, and Toru Nishikawa, Representative Director & CEO of Preferred Networks, a discussion was held on the direction of technological innovation to address the issue of increasing power consumption.
First, the two men gave presentations based on their companies’ initiatives. Fellow Matsuo pointed out that data centers currently account for 2% of the world’s power consumption and 12% of power consumption in Japan’s Tokyo metropolitan area. He also mentioned that the NTT Group itself consumes approximately 0.7 percent of Japan’s total electricity, emphasizing the need to reduce power consumption. He demonstrated the potential of optical technology as a solution. In particular, he explained that advances in optical communications technology, such as on-chip photonics-electronics convergence technology, will enable “miniaturization, low power consumption, and low cost,” making it possible to significantly reduce power consumption. He presented benefits of introducing inter-chip optical interconnection, including faster data communication speeds while reducing power consumption, ensuring power allocation for computation, and making effective use of computing resources independent of the physical location of the hardware, along with a specific technical path to get there.
Meanwhile, Mr. Nishikawa, who aims to “commercialize cutting-edge technology in the shortest possible time,” spoke about the challenges facing computing infrastructure in the age of generative AI. Citing the example of the “MN-Core” processor they are developing, he explained how a significant improvement in power efficiency was achieved by focusing on the computing unit and on-chip memory and minimizing control circuits. Supercomputers equipped with “MN-Core” have been ranked number one in the world a total of three times in the power consumption ranking “Green500,” and the institute is continuing to further develop its architecture with confidence. In addition, he also revealed their development plans for next-generation processors that will employ different optimal architectures for inference and learning. He stressed the importance of creating a “new computer” by integrating various technologies such as interconnects and chiplets, not just highly efficient AI chips.
In the dialog following the presentation, there was a more specific discussion about computing architecture in the AI era. What attracted particular attention was the potential and challenges of “distributed computing.” While Fellow Matsuo pointed out that optical technology can be used to connect memory up to 2 km away without any loss, he also hinted at physical constraints, stating that some delay is unavoidable. Given that current supercomputers are limited to connections within 10 meters, we asked a fundamental question: “Can a supercomputer that takes up an entire datacenter really be used for AI?”
Mr. Nishikawa responded by proposing a new approach that utilizes AI in the design itself, stating that as supercomputer systems become more complex, they are becoming increasingly difficult for humans to design accurately. However, he also said that it is difficult to design complex circuits from the start, and emphasized the need to develop circuits gradually, starting with small ones.
Opinions were also exchanged about the future of packaging technology. Mr. Nishikawa explained that next-generation processor development requires a high-density, high-efficiency design that separates inference and learning, and he emphasized the particular challenge of dealing with heat dissipation.
At the end of the discussion, both men offered messages to young researchers. Fellow Matsuo stated that “it is important to take into account the entire planet and society as a whole,” and expressed his enthusiasm for “creating a world where energy savings can be achieved through AI”. Mr. Nishikawa concluded by reaffirming the importance of comprehensive research and development such as that by NTT, stating, “Understanding and integrating both hardware and software make it possible to achieve revolutionary innovations that could not be achieved by either one alone.”

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Exhibition Report

Technical exhibits at NTT R&D FORUM 2024 were divided into three areas: “RESEARCH”, “DEVELOPMENT”, and “BUSINESS.” They were arranged thematically on the basement, first, and second floors of the venue site, allowing visitors to view the entire exhibition in a systematic manner. Exhibits were colored blue in the RESEARCH area, green in the DEVELOPMENT area, and purple in the BUSINESS area, allowing visitors to understand the relationship between the areas at a glance.

■ RESEARCH Technical Exhibits

「In the RESEARCH area, 49 exhibits showed NTT’s latest basic research achievements in the fields of Network, UI/UX, Sustainability, Security, Bio/Medical, and Quantum. Exhibits of technologies progressing toward practical application drew the attention of visitors in particular. These included technologies for a novel quantum computer, non-invasive wearable glucose sensor, and active noise cancellation.

Exhibit No. γ08-02

Optical Technologies for Optical Quantum Computing with Continuous Variables

γ08-02 demonstration
Fig. 1 Demonstration of the optical quantum computer linked between RIKEN and NTT.

Progress is being made in the research of quantum computers, which leverage quantum properties to solve computing problems that are difficult to solve with conventional technologies. While there are various methods, superconducting quantum computing and neutral atom quantum computing, considered the most mainstream methods, require an environment cooled to near absolute zero (-273°C) for stable operations. As a result, they face the issue of limited chip scaling because the chips must be cooled.
NTT is engaged in R&D to realize “continuous-variable optical quantum computers.” Using the company’s cultivated high-performance optical device technologies, this quantum computer is capable of large-scale operations at room temperature. Technologies used in optical fiber communication can be applied to many of the elements that make up the continuous-variable optical quantum computer. When new technologies are needed, extending optical device technologies cultivated to date by NTT holds great promise. Integrating optical communication technologies and optical quantum technologies makes it possible to achieve large-scale calculations at a bandwidth 1000 times that of conventional computers, even at room temperature. This achievement heralds the arrival of a new innovator in the field of quantum computing.
For this exhibit, Professor Akira Furusawa of the Graduate School of Engineering at the University of Tokyo, whose lab is collaborating in the development of this quantum computer, participated. A demonstration connecting RIKEN, where the developed computer is installed, and NTT was carried out for the first time (Fig. 1).
The continuous-variable optical quantum computer is expected to be applied to optimization problems, which seek solutions that maximize or minimize the objective function from a vast number of choices while satisfying constraints, and to neural networks. The computer is considered to be particularly advantageous compared with conventional computers for problems that deal with continuous data and systems.
The exhibit also touched on the development of a system that places a cloud between users and the quantum computer. It has the role of sending specified parameters to the quantum computer and sending the results of the job executed by the quantum computer to the user, allowing the creation of a more convenient quantum computing environment.
Applying optical devices developed by NTT, we anticipate realizing a rack-sized optical quantum computer around 2030 and a chip-based optical quantum computer around 2050.

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Exhibit No. γ09-01

Non-invasive Wearable Glucose Sensor Using Microwaves

γ09-01 explain
Fig. 2 Wearable glucose sensor under development to be even smaller.

NTT is advancing R&D in the biomedical field using its sensor and data collection technologies. The goal is the realization of precision medicine, which allows total medical care, including health promotion, preventive medicine, treatments, and prevention of worsening of illnesses, tailored to each individual.
An R&D achievement is a glucose sensor that carries out measurements using microwaves. NTT is aiming to commercialize this technology by FY2028.
Conventionally, a person’s glucose level, which reflects the amount of sugar in the bloodstream, a factor related to diseases such as diabetes, is measured out by sticking a disposable sensor into one’s body with a needle. However, this method is highly burdensome for users, as it brings pain and discomfort. The barrier to its use is an issue.
To address this problem and allow visualization of a person’s glucose level without using needles, NTT is developing a non-invasive sensor in wearable form that makes contact with the skin and carries out measurement using microwaves (Fig. 2). NTT has many equipment for evaluating the response of different microwave frequencies in communication devices, and it has identified frequencies that are highly responsive to glucose.
At present, NTT is conducting trials on glucose measurement while the user is at rest. Going forward, our goal is to allow convenient visualization of changes in the glucose level on a daily and constant basis by researching and developing technologies to suppress error factors. Our glucose sensor technology promises to contribute to supporting appropriate dietary guidance and exercise regimen to prevent an increase in the glucose level.

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Exhibit No. γ05-01

Personalized Sound Zone (PSZ)

Dome-shaped noise-cancelling system
Fig. 3 Dome-shaped noise-cancelling system

NTT is pursuing a variety of R&D initiatives to realize the “ultimate private sound space” where users hear only the sounds they want to hear and allow others to hear only the sounds they wish for them to hear. We are developing and selling earphones and headphones that allow users to hear sounds without the phones blocking their ears. These products provide optimal sound control tailored to each individual with functions such as noise cancellation and benefits such as increasing value at performance venues. NTT seeks to enhance customers’ experience based on sound.
The exhibit at R&D Forum 2024 provided several experiential programs. When guests enter a sound dome, noise is eliminated by several noise-cancelling installed speakers. We envision the use of this system in entertainment venues and general business facilities (Fig. 3). The exhibit depicts a vision of the future where users can simply sit at a particular table and easily converse without environmental noise.
The demonstration of the “Sound SyReal” technology combined sounds in cyberspace and sounds in the real world. Sounds flowing into the participants’ earphones and sounds flowing in the exhibition hall were adjusted in real time using low-latency transmission. Participants experienced the acoustic effect of hearing sounds from behind them, even though no speakers were placed there. Another demonstration presented “acoustic cross reality.” Using the aforementioned open-ear headphones, particular sound effects can be played for only audience members watching a play as well as render real sounds on the stage clearer.
NTT has proposed technologies for “precise control of sound,” allowing users to not only spend time with peace of mind and security in a world where people and noises are mixed, but to also experience increased value in all sorts of venues.

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Exhibit No. γ03-01

Motor-Skill Transfer: Movement Support via Brainwaves

Brainwave-measuring headgear
Fig. 4 Transmitting information to the motor imagery estimation AI through brainwave-measuring headgear.

NTT is also taking on the challenge of R&D in the “brain tech” field, which integrates psychology, neuroscience, and technology to elucidate the physical mechanisms of brain functions, leading to the development of various applications and services. Presenting NTT’s “motor-skill-transfer technology,” the exhibit demonstrated a movement support device that uses brainwaves, which differ in each person.
For the demonstration, the user sits in an electric wheelchair and wears brainwave-measuring headgear. Next, a tutorial similar to that of videogame asks the user to visually imagine moving to the right and to the left. Mentally visualizing the movements causes changes in brainwaves. The “motor imagery estimation AI” analyzes the brainwave patterns and converts them to control commands. This technology allows the user to operate connected devices or an avatar on a screen (Fig. 4). With this technology, users can control equipment such as an electric wheelchair by means of their brainwaves as they visualize movements without moving their bodies.
NTT’s research is strong in the tuning of the “motor imagery estimation AI.” The technology consists of a proprietary deep learning model that incorporates parameters that account for the timing of intentional switching in motor imagery and a weakly supervised learning system that allows the model to be updated sequentially as it adapts to brainwave changes during the use of the measurement headgear. In this way, reduction in estimation accuracy is prevented.
NTT’s research seeks to increase the level of freedom of movement for people with physical limitations, such as those with disabilities, as well as for people who cannot move temporarily. Furthermore, enabling smooth control of avatars in cyberspace will make it possible to eliminate the need for control devices, allowing more people than before to spend life in the metaverse.
The motor cortex, the part of the brain that is responsible for motor commands, has been mapped in detail for locations that correspond to movement commands. Improving the accuracy of the “motor imagery estimation AI” can thus be accomplished by measuring brainwaves in greater detail going forward. Another possible approach for increasing accuracy is to combine brainwave data with different data such as electromyography (EMG), which measures slight changes in the electrical field when muscles contract.

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Exhibit No. γ01-01

Visualizing Motor Skill with a Smartphone

Measuring motor skill using a smartphone
Fig. 5 Measuring motor skill using a smartphone.

Until now, it has been difficult to easily measure the motor skills of hands and feet because traditional assessment of hand and foot dominance uses specialized and expensive equipment. To address this issue, NTT has developed technology that uses smartphones to easily evaluate motor skill.
Measurement of motor skill is done by simply holding a smartphone running a dedicated app with one hand or attached to a foot with a strap, and then tracing the circle drawn on a sheet of paper with the smartphone (Fig. 5). Deviations in circular movements are quantified by NTT’s proprietary algorithm to calculate the level of variability. The algorithm evaluates the user’s repeated movements in a short time by measuring the trajectory of the accelerator sensor. By comparing the level of variability with other users in the same age group, the user’s motor skill can be easily quantified.
Through large-scale acquisition of data on motor skill, which has been difficult until now, it is possible to use the data to see changes in motor skill according to age and to conduct a large-scale survey on the effects of correcting children’s dominant hand. Representative use cases of the technology are assumed to be training and rehabilitation, with the recovery of motor skill in the hands and feet visualizable through regular measurements of the level of variability. Experiments already conducted jointly with sports equipment manufacturers resulted in data showing that the level of variability falls until the mid-teens and increases as one ages. We expect that this technology will be applied in the future to a variety of fields including sports, medicine, and the nursing care industry.

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Exhibit No. γ06-01

Well-being Measurement Technology

Well-being Measurement Technology exhibit
Fig. 6 Well-being Measurement Technology exhibit

Well-being (not only good physical and mental health but also good social and economic conditions) has become a global concern together with SDGs. It is being emphasized not only in individuals’ lives but also in group settings such as companies and schools. To realize a sustainable society, it is necessary to continually measure the actual level of well-being. However, until now it could not be done at low cost and with high accuracy.
At NTT, we are also promoting the enhancement of employees’ experience. To realize this, we are advocating and researching the concept of “social well-being,” which emphasizes the balance between group harmony and individual autonomy. In considering social well-being, in addition to individual well-being, the involvement of individuals in the group to which they belong is critical. It is also essential to evaluate the health of the group.
First, in joint research with the Kanazawa Institute of Technology, integrating the findings of social psychology and educational psychology, NTT has formulated “well-being competencies” composed of practical qualities and abilities needed to live a life of well-being. “Well-being competencies” allow individuals to subjectively understand steps to increase their well-being. As an aid, NTT has also developed technology that combines “well-being competencies” with objective information. For example, NTT’s “text risk assessment technology” evaluates how intimidating text that is posted comes across to other people. By using this technology, it is possible to not only objectively evaluate the effects of an email on its readers, but also highlight intimidating statements expressed in meetings from meeting minutes. NTT has also developed a similar assessment technology for collective well-being (Fig. 6).
By developing technology for measuring and supporting well-being and establishing practical know-how that connect these two areas, NTT seeks to contribute to the realization of a sustainable society by supporting individual and collective well-being in both their subjective and objective aspects.

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Exhibit No. γ04-03

Photonic Cryptographic Circuits for Cryptographic Computation

γ04-03 exhibition
Fig. 7 Magnified view of NTT’s photonic cryptographic circuit under development

Optical communication has become the standard at all kinds of communication sites. However, the computer circuits that drive optical communication are still electrical. If everything from circuits to networks could be implemented optically, significantly low latency and reduction of power consumption could be realized.
As an initiative to achieve this reality, NTT is engaged in the development of photonic cryptographic circuits that carry out cryptographic operations using light. This exhibit presented an algorithm that uses a photonic encrypting circuit that converts electronic bit values to photonic addresses to realize low latency. Also presented was a method of converting a cryptographic circuit into a photonic circuit using NTT’s optical integration technology. NTT has made noteworthy achievements in this area, such as the carrying out the world’s first one round of symmetric key cryptography on a photonic circuit.
Furthermore, NTT is developing an all-photonic chip (Fig. 7). At present, we are at the stage of improving the technology, such as conducting research on suppressing heat generated by reducing the number of switching elements. We aim to establish low-latency and low-power communication systems by deploying this technology in servers and other equipment. The introduction of “optical semiconductors,” which NTT is engaged in, is also expected to give a big boost to the Japanese semiconductor industry.

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Exhibit No. γ10-13

Impact Assessment and Countermeasure Navigation for Network Failures

Example of figure visualizing the analysis
Fig. 8 Example of figure visualizing the failure cause analysis.

When responding to a large-scale network failure, it is essential to analyze the management information of multiple networks. However, because the management of each network is separate, until now it has been difficult to grasp the impact of a failure that spans multiple networks and quickly determine responses.
NTT’s network failure impact assessment and countermeasure navigation technology overcomes these difficulties, enabling faster network recovery. First, when a network equipment failure occurs, information is collected using NTT’s NOIM common data model to identify the failure and impact. This model enables unified management and visualization of various networks, such as RAN, transmission, and core networks. In addition, the use of NTT’s network failure location estimation technology (knowledge-based autonomous failure-event analysis technology for network (Konan)) allows automatic analysis of communication service failures (Fig. 8). After the failure location and impact are identified, the autonomous scenario creation LLM agent is connected to the failure information. The LLM agent references equipment operation manuals and other documentation and carries out repairs and recovery in real time. Instead of carrying out pre-defined responses, NTT’s technology collects and utilizes information appropriate to the failure situation to carry out the appropriate response. What’s more, NTT’s LLM agent provides navigation that is more accurate than what is generally available.
Until now, experienced personnel surmised failure locations from past alerts and action logs, and responses were carried out by looking for the necessary operation manuals and looking up information. NTT’s new network failure impact assessment and countermeasure navigation technology makes it possible to automate the entire process from identifying the network failure to recovering the network using the LLM agent.
We are aiming to refine the technology to accurately and autonomously visualize and navigate network failures for multilayered network infrastructure, which support social services. Our goal is to enable issuing an initial report on the impact of a network failure on services within 30 minutes and achieve network recovery within 60 minutes.

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■ DEVELOPMENT Technical Exhibits

In the DEVELOPMENT exhibition area, 52 exhibits, including exhibits on NTT’s latest IOWN-related research initiatives and practical applications, generative AI, and space technologies were presented. Examples include the collaboration between human beings and AI based on NTT’s evolving LLM “tsuzumi,” “Media Production Digital Transformation (DX),” which realizes a video production facility through IOWN-based network, sharing, and cloud technologies, and innovative technological developments like the NTT Group’s space business brand “NTT CONSTELLATION 89 PROJECT (NTT C89).”

Exhibit No. δ01-01

The Evolution of “tsuzumi”: NTT's Large Language Models

Adapter added to tsuzumi
Fig. 9 New Visual Comprehension Adapter added to “tsuzumi.”

As can be understood from the exhibit’s key message “Empowering Business and Life with a New Level of Comfort through ‘tsuzumi,’” the biggest difference from last year’s “tsuzumi” exhibit is the addition of a technology to leverage “tsuzumi” in practical applications. This technology is the “Visual Comprehension Adapter” (Fig. 9). Documents such as Web pages and PDFs contain not only text but also images and diagrams. Their layout holds meaning. The exhibit presented visual comprehension technology that allows the meaning of a document as a whole to be understood.
As an example of intra-company DX made possible by “tsuzumi,” the exhibit demonstrated “tsuzumi’s” automation of the creation of order slips for desired products. “tsuzumi” successfully created the order slips by referencing internal work manuals while operating the actual system screen.
Many data and IT systems created for human use become difficult to operate due to their age and the technologies used in their creation, becoming burdens in daily life and work. Especially in places such as large corporations and government agencies where large-scale system upgrades require time and capital expenditure, legacy technologies are kept in use through extensions. Against the conventional approach to upgrade enterprise systems, “tsuzumi” shows the way to new business transformation thanks to its ability to understand and perform operations on current systems. What’s more, “tsuzumi” is continuing to evolve as it facilitates collaboration between humans and AI through information acquisition and assimilation by means of natural human dialogue and response and document comprehension.

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Exhibit No. δ03-07

IOWN × Media Production DX

Production of TBS TV information program
Fig. 10 Production of TBS TV information program at the Musashino R&D Center.

In recent years, the proliferation of Internet media has brought about intensified competition among video content companies. “Media production DX” using IOWN APN promises to address the need to develop high-quality contents and improve operational efficiency.
The exhibited technology that uses the IOWN APN to implement a wide-area network spanning multiple locations to connect a large number of shooting sites and production bases. IOWN APN is ideally suited because it features high capacity, low latency, and no jitters. For example, to broadcast live sports, conventionally staff and a production truck loaded with production equipment were dispatched to the event. Using IOWN APN, however, makes it possible to directly transmit source video from the event site to a private cloud and edit the video in real time in a studio at a separate location.
At this exhibit, a media content production environment that may become the new standard was presented. Its capabilities include actually broadcasting a TBS TV information program from the Musashino R&D Center with video switching and mixing (Fig. 10) and activating an international IOWN APN spanning 3,000 kilometers by connecting with Chunghwa Telecom in Taiwan.

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Exhibit No. δ05-09

New Wireless Energy Transmission Technology

Supplying power to a rover
Fig. 11 Supplying power to a rover equipped with a receiver by using lunar sand as the transmission path.

The NTT Group has launched the “NTT C89” brand for its space business and industry. The brand is engaged in creating space services and addressing global issues such as climate change. In recent years, as the cost of launching satellites and rockets fall, businesses and services making use of outer space have increased.
One service is planetary survey by a “rover.” This planetary exploration hardware is indispensable for space exploration. Wide-area surveys by a rover can be carried out either through automation or remote control, making it an important partner in advancing exploration of the lunar surface. However, there is drastic environmental difference between “daytime” on the moon, during which the surface temperature rises to 110℃, and “nighttime,” during which the surface temperature falls to -180℃. This presents a barrier in the utilization of rovers, as it is difficult to use batteries as a power source and costly to transport power cables from Earth.
NTT has thus developed a method to supply stable power wirelessly to the rover, unaffected by the surface temperature or sunlight on the moon. This method transmits highly efficient, contactless energy using materials that can be procured from the lunar surface. Power is sent to a rover equipped with a receiver from the transmitter. The transmitter, which includes a proprietary field resonance antenna that generates strong electric field waves, uses “lunar sand” called regolith as the transmission path (Fig. 11). Compared with conventional methods such magnetic resonance or microwaves, the surface area for transmission is expanded by more than 100-fold and the transmission efficiency by more than 10-fold. Put another way, the technology constructs a “lunar surface power transmission network” using lunar regolith. NTT seeks to apply this technology not only to exploring the moon, but also to provide power to space elevators from 2050 onward.

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Exhibit No. δ02-02

Efficient utilization of accelerators and connection technologies with DCI

Example of server system
Fig. 12 Example of server system using NTT’s DCI controller software

Existing servers consume great amounts of CPU power for GPU control and communication. It is difficult to aggregate GPUs in a remote location because costs and delays in communication are incurred. NTT has therefore developed a technology that makes efficient use of accelerators and realizes low-latency connections in Data Center Interconnection (DCI), contributing to the reduction in data center energy consumption. The exhibit presented a server system using NTT’s DCI controller software (Fig. 12). The controller software issues instructions for photonics-electronics convergence switches and allocates accelerators to the composable server. This allows accelerators to communicate directly with each other at high speed at photonics-electronics convergence switches. At the composable server, accelerators are flexibly allocated in the resource pool in response to changes in the workload. In experiments, applying the DCI contributes to a 34–62% reduction in energy consumption, even in AI analysis of images.
In addition, the use of “low-latency remote connections,” which realizes data copying between memory at remote locations (remote direct memory access (RDMA)) on the APN, allows the construction of an environment where information can be processed even when the “data aggregation” base and the “data ingestion” base are several hundred kilometers apart. As a result, besides a reduction in CPU overhead, latency in transmission and power consumption could be reduced by up to 60%. Going forward, NTT envisions use cases such as security monitoring and behavior analysis using multiple cameras across various locations, which is required for the realization of smart cities and digital twins. In the future, this technology is expected to further reduce costs and save energy by allowing GPUs to be used efficiently through consolidation across remote locations.

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Exhibits No. δ01-10, δ01-11

AI Constellation

Discussion between LLMs using Facilitator AI
Fig. 13 Discussion between LLMs using Facilitator AI

The use of generative AI is being sought not just by businesses for their work sites but also by individuals and local governments. Companies are in fierce competition to provide LLMs, which can create new text by learning textual data and understanding human languages at a high level, as services. However, the output results depend greatly on each LLM’s training data and algorithms. There are cases also where the output is a general solution and cases where the result comes only from a single perspective. NTT is thus engaged in the development of AI technologies based on the philosophy of “AI Constellation.” Instead of depending on a vast monolithic LLM, multiple small LLMs having their own expertise and individuality are linked to improve diversity in results. This AI architecture is inspired by the image of stars connecting to form constellations, hence its name.
One of the technologies that makes this possible is the “Facilitator AI,” which links LLMs to advance discussion. A facilitator is someone who stimulates debate from a neutral standpoint in meetings and group work in order to support mutual understanding and consensus-building among participants. The Facilitator AI plays the exact same role.
For example, in Omuta City in Fukuoka Prefecture, a public participation workshop used AI Constellation, with multiple LLMs and the Facilitator AI, to brainstorm ideas on ways to prevent the need for nursing care in the city (Fig. 13). LLMs were given roles such as that of an internist, occupational therapist, social epidemiologist, dentist, and welfare commissioner. They each presented ideas considered necessary in their field of expertise. The Facilitator AI coordinated these contents and led discussions so that participants could provide diverse perspectives while minority viewpoints were respected. At the workshop, participants experienced how debate could be promoted based on conversations raised by LLMs, similar to conversations among human experts.
NTT is also developing technology that allows AI agents to acquire knowledge from conversations between LLMs and grow autonomously. We envision a future where autonomously growing AIs and humans work together to perform complex tasks with ever increasing precision.

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Exhibit No. δ01-13

Service Robot Control by Generative AI

Demonstration of a service robot
Fig. 14 Demonstration of a service robot

Is it possible to create “smart robots” which, instead of just operating when instructions from humans are received, understand their own tasks and situations and act flexibly on their own?
Spurred by this question, NTT researchers are developing a control technology for service robots that incorporate generative AI. Instead of robots that operate based on predetermined rules and algorithms, the aim is develop robots that act on their own initiative by deriving results that come from combining in the LLM the perspectives of “role and business knowledge,” “one’s own ability,” and “situational awareness.”
The exhibit’s demonstration presumed a nursing home as the setting. The LLM was given the role of “assisting a client in the nursing home.” The following scenario was shown: A man sitting down takes a beverage from a refrigerator nearby but leaves without closing the door. The service robot, which saw what happened, calls out to the man in synthesized speech: “The refrigerator door is open.” When it judges that the man is not returning, it moves toward the refrigerator by itself and closes the door (Fig. 14).
The LLM understands each step taken in the users’ action history, such as “drinking a beverage” and “opening a can.” From this history, it infers “things to keep in mind” and “candidate actions to carry out.” It then determines the action that should be carried out from among the candidates, which is then executed by the service robot.
There is wide room for what service robots, such as the demonstration robot, can do to provide hospitality, even when it comes to social issues such as a declining working population and the need to provide support for the lives of the elderly.

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Exhibit No. δ04-03

In-network Video Processing and Subchannel Circuit Exchange

With and without SCX demonstration
Fig. 15 Demonstration of video streaming with and without SCX technology

Especially since the advent of COVID-19, livestreaming services are facing challenges in providing flexible resources to meet customer needs and achieving real-time streaming without a sense of delay using conventional optical networks. Furthermore, livestreaming is also drawing attention as a business tool. To achieve rich contents using AI processing and other technologies, specialized hardware and staff are employed.
For example, consider a case where a person’s movements are captured by cameras from different locations to produce an avatar in real time through graphics processing and then streamed on a single screen. In such a case, the avatar’s movements may be jittery and appear unnatural due to latency in transmission or processing, resulting in an undesired experience for the user.
NTT has developed a technology for real-time video processing within a network and subchannel circuit exchange (SCX), which allows distributed data centers to be realized. In this exhibit, the streaming of high-quality video by simple equipment was demonstrated. This was made possible by connecting video processing functions implemented in the network with video capture sites using APN.
Even when video from multiple locations is used as input and advanced video processing using AI and other technologies is carried out, a stable communication path could be freely constructed thanks to SCX technology. Redundancy required for video services could thus be realized, as could support for bandwidth change (hitless resizing), thus ensuring that streamed video is synchronized (Fig. 15). This APN-based end-to-end optical video streaming architecture will realize low-latency live streaming that connects multiple locations on demand.

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■ BUSINESS Technical Exhibits

In the BUSINESS area, NTT Group companies showed their initiatives in applying R&D results to actual business through 21 exhibits. Their efforts were divided into three categories: Communication & Computing, CX (Customer Experience) & DX, and Security & Privacy. Socially implemented technologies directly connected with commercialization were introduced, including “Rectification of Urban Road Traffic” using NTT’s “4D Digital Platform®” to reduce social burden and “Trust Technology,” which is closely connected to generative AI technology.

Exhibit No. β01-10

4D Digital Platform® Technologies Boost Society DTC

Overview of the traffic rectification demo
Fig. 16 Overview of the traffic rectification demonstration

The use of “digital twins” as a method for approaching real-world problems is growing. The technology reproduces real-world objects and conditions and monitors and simulates them in the virtual world. NTT has incorporated “digital twin computing (DTC)” into the IOWN concept, and is developing and utilizing its “4D digital platform®” as a supporting technology. The platform includes real-time integration of sensing data with high-precision location and time information in the “Advanced Geospatial Information Database,” which contains rich semantic information, and enables high-speed analysis and prediction.
“Traffic rectification” is drawing attention as methods that make use of the 4D digital platform®. To apply them, it is essential to evaluate and predict the effects of individuals’ behaviors on traffic as a whole under Transportation Demand Management (TDM). At present, NTT Group companies and the Hanshin Expressway Company are jointly studying the effectiveness of urban road traffic rectification. For example, they are conducting traffic simulations that connect a variety of times-series spatial data and providing traffic recommendation information to users on their smartphones. Also being planned is a demonstration of integrated data analysis and usage that includes training for increasing the value of recommendations based on the results of behaviors carried out by users in response to recommendations (Fig. 16).
Improving technologies for linking, integrating, and utilizing diverse time-series and spatial data promises to benefit not traffic rectification but also fields such as mobility and marketing.

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Exhibit No. β03-06

Trust Technology × Multilingual Technology

Multi-lang AI synth demo
Fig. 17 Demonstration of multilingual speech synthesis AI technology.

The use of generative AI in speech synthesis is bringing advancements to technologies such as text-to-speech, which reads written text aloud in a natural tone, and technologies that samples the voices of real people for use in speech synthesis. On the other hand, the practice of training the voices of characters for generative AI without the permission of actors or copyright holders and producing different contents with the trained data is problematic. This has led the Japan Actors Union, which includes voice actors and actresses, to launch a public awareness campaign with a video calling for the necessity of creating rules for the use of human voices for AI. Besides promoting the fair use of training data, a system that provides fair revenue sharing is also being sought.
Combining NTT’s “Multilingual Technology” and “Trust Technology” provides a solution to these issues. First, NTT’s multilingual speech synthesis technology allows a tailor-made speech synthesis model to be constructed by learning the base speech synthesis model together with the speaker’s voice in a session ranging from as short as a few minutes to at most about 10 minutes. In addition, the technology can use this model to achieve cross-lingual speech synthesis in Japanese, English, Chinese, and Korean. NTT’s “Trust Technology” applies blockchain technology’s transparency and tamper-proofing functions, which are also used in cryptocurrencies, to tags attached to voice data, speech models, and speech synthesis so that the authenticity of each data can be verified. This technology also facilities revenue sharing by providing histories of data usage.
At this exhibit, visitors experienced a demonstration where the generative AI learned the voice of a real-life idol or announcer and answered questions with a voice similar to them. The technology also provided responses in multiple languages (Fig. 17).
NTT seeks to create opportunities to use voice contents globally by connecting partners who wish to provide their own voice as intellectual property (IP) with parties who wish to use AI speech in services and goods.

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