AI 1988
Look back at how members viewed the potential of AI in 1988 in this reprint from the ACCJ Journal archives.
Look back at how members viewed the potential of AI in 1988 in this reprint from the ACCJ Journal archives
Artificial intelligence (AI) is becoming more and more widely used in Japan. Companies in this country are coming to realize that if they want to stay internationally competitive, they have to incorporate this technology. Davis is a popular contributor to these pages who specializes in high-technology subjects.
Japan’s large electronics companies are constantly looking for ways to boost the efficiency of their administrative work while searching for new markets so as to diversify their business. AI, a type of sophisticated computer programming that promises to revolutionize many job-related tasks, is catching on among electronics companies and software businesses here, and is also a target of interest among trading houses. All of these enterprises want to establish a foothold in this up-and-coming technical sector so as to enhance their long-term prospects. AI systems in the years to come may make or break certain companies in highly competitive areas of business. It would not be an exaggeration to say that a “mini boom” is being seen today in Japan’s AI sector.
AI systems under development here are intended to address bottlenecks within corporate product-development departments, and they are being marketed to outside customers, sometimes together with special types of data processing equipment. One of the best ways to sell more computer hardware is to market such equipment with an emphasis on higher value-added features, such as the ability to effectively handle AI writing tasks. However, Japanese companies in this field are all well aware that they have to contend with the likes of Symbolics Inc., a Cambridge, Massachusetts, global leader in AI workstations.
Two years ago (in 1986) the Artificial Intelligence Association of Japan was established in Tokyo by electronics companies, telecommunications businesses, software houses, and others interested in new developments in computer programming. The association cultivates exchanges between researchers in various AI-related fields and disseminates technical information to its members. Moreover, the association promotes specialized training of so-called knowledge engineers and other experts needed for the advancement of the new discipline. Establishment of the special association signifies the maturation of the initial commercial phase of AI here.
In contrast to Japan’s AI infrastructure, state-of-the-art American AI work is typically dominated by clusters of small businesses mainly located around major universities. In fact, many Japanese AI specialists have studied at leading US universities. As a result of the difference in the two paradigms, the large electronics enterprises of Japan have tremendous potential resources to devote to AI studies, whereas in the US, venture capital must typically be raised to fund much of the innovative work in AI.
“The global market for AI systems is likely to grow to as large as much as $10 billion per year sometime between 1995 and 2000, according to Japanese electronics industry estimates.”
The Japanese approach to the AI business often relies as much on proximity to leading US universities as it does on relationships with the top Japanese universities. In other words, Japanese universities are not major actors within the immediate sphere of AI business here. The paradigms are not without exception, however, because some smaller businesses in Japan, such as CSK Corp., are doing work in the field as well.
As AI is widely considered a promising growth market within the information processing sector, electronics companies are offering products that will allow users to develop their own AI systems, such as so-called expert systems. This customized programming is developed on the basis of experts’ knowledge; hence expert systems comprise handy tools for novices—so that they may easily draw upon the comprehensive knowledge of specialists to assist them in complicated tasks, such as writing specific types of software programs.
The global market for AI systems is likely to grow to as large as much as $10 billion per year sometime between 1995 and 2000, according to Japanese electronics industry estimates. The leading AI language today is LISP (LISt processor), and it is widely expected to retain its front-running position. Four of the largest AI applications expected in the mid-to-late 1990s are those for integrated circuit design assistance, manufacture planning, financial planning, as well as computer systems diagnosis and maintenance.
An example of a medical application of AI systems is the so-called RINGS program—rheumatology information counseling system—developed recently by Nippon Telegraph and Telephone Corp. and a medical college in Tokyo. The system is used by those suffering from rheumatism to help them in diagnosing minor problems over the telephone. When more serious problems arise, doctors are to be consulted. A variety of other medical-related AI systems are now under development, in part because the medical sector is likely to see rapid growth due to the aging of Japan’s population.
In the area of nuclear power plant operations, a group of Japanese enterprises is developing an expert system to enhance the safety of pressurized water reactors (PWRs). The LISP-based expert system is intended for use in new types of PWRs to be operated by Kansai Electric Power Co., Inc. and three other electric utilities.
Greater safety in operating nuclear plants can lead to enhanced profits for the utility companies, as they will not need to shut down reactors for prolonged periods in order to do repairs, precautionary tests or other types of maintenance.
The most prominent of Japan’s AI-related development programs is the so-called fifth-generation computer project, which is administered by the Institute for New Generation Computer Technology (ICOT). The institute was established in 1981 under funding from the Ministry of International Trade and Industry’s (MITI’s) Machinery and Information Industries Bureau.
“Although today’s AI systems can only cope with surface level knowledge, those of the year 2000 are likely to be capable of dealing with more abstract forms of knowledge. ”
Altogether, there are nine private companies participating in the project. Researchers based at MITI’s Electrotechnical Laboratory (ETL) in Tsukuba, Ibaraki Prefecture, are also involved. Moreover, the ETL, which is administered by MITI’s Agency of Industrial Science and Technology, is doing its own independent work in the field. Six to eight researchers from each of the electronics companies work at the ICOT center in Tokyo, and then only for periods generally ranging from two to four years.
When the project began in 1982, it was the subject of considerable attention throughout the world, due to its bold proposals and the perceived threat that it posed to the American and European computer software industries. However, recently it has not attracted much interest because Americans and Europeans have been less than impressed by the meager results of the project. US interest in the ICOT project led to the establishment of Microelectronics and Computer Technology Corp., a research consortium headquartered in Austin, Texas.
AI systems have a long way to go before they reach a phase of maturity. Although today’s AI systems can only cope with surface level knowledge, those of the year 2000 are likely to be capable of dealing with more abstract forms of knowledge. Advances in the memory capacity of computer microchips, parallel processing capabilities of computers, data processing speeds, and knowledge bases will accelerate the progress of the AI business sector.
Let us hope that people will always be able to keep the upper hand of control on such advanced tools as AI systems, and that the sophisticated tools won’t ever “discard” the humans they are supposed to be helping.
Your Own Private AI
As AI evolves, businesses are turning to custom LLMs to unlock corporate resources.
As artificial intelligence evolves, custom systems unlock business resources
Konosuke Matsushita was one of Japan’s greatest entrepreneurs. As the founder of a light socket company that evolved into Panasonic, he inspired legions of salarymen with his business wisdom. Twenty-five years after his death, the “god of management” was effectively resurrected as an artificial intelligence (AI) model. A chatbot trained on his writings and speeches can produce eerily lifelike Matsushita answers, according to one relative, and will eventually be used to make business decisions. It’s a dramatic example of how businesses are using AI to leverage intellectual property built up over decades.
The past few years have seen an explosion of AI applications based on large language models (LLMs) and tools such as OpenAI’s ChatGPT and Google’s Gemini. They have been used for everyday tasks such as writing text for slide decks, lessons, and articles, as well as synthesizing search results as in Google’s AI Overview that now appears with most searches.
LLMs are based on computational systems using neural network transformers that perform mathematical functions. Measured by the number of parameters they contain, LLMs learn by analyzing vast amounts of text from books, websites, and other sources. During training, the model identifies patterns, relationships among words, and sentence structures. This process involves adjusting millions of parameters—values that help the model predict what comes next in a sequence of words.
A major problem with LLMs and generative AI, however, is that they usually draw entirely from online content and thus are prone to inaccuracies. AI hallucinations, as they are called, occur when LLMs observe patterns in the data that are nonexistent, or at least imperceptible to humans.
One solution is private AI. It brings the power of LLMs inside a company, where queries are secure and limited to the company’s own data, reducing the risk of security leaks and incorrect or misleading responses. Private AI has traditionally been limited to government, defense, finance, and healthcare users, but it’s spreading to a broader spectrum of industries due to fears about intellectual property theft.
“[Private AI] brings the power of LLMs inside a company, where queries are secure and limited to the company’s own data, reducing the risk of security leaks and incorrect or misleading responses.”
Kenja KK, a member of the American Chamber of Commerce in Japan (ACCJ), is opening up the market in Japan to private AI. The Tokyo-based company offers AI solutions for enterprises that include purpose-built expert systems, incorporating a relatively new AI technology called retrieval-augmented generation (RAG).
Bearing a name coined as recently as 2020, RAG relies on a predetermined collection of content to improve the accuracy and reliability of generative AI content. Kenja offers a self-service plan for small and medium-sized businesses and a more comprehensive enterprise plan for businesses.
“Private AI is the next frontier,” said Kenja founder and Chief Executive Officer Ted Katagi, who is also chair of the ACCJ’s Marketing and Public Relations Committee. “All companies face the same issues: you have very sensitive data that you don’t want to make accessible to everybody at the same time. Private not just in terms of someone outside the company, but within the company, too. You may not want HR data to be shared with people in finance, for example. That’s an issue you want to solve, and we solve that.”
Kenja users create so-called rooms where they can upload thousands of documents or other content, organizing this into topic-specific folders. The process can be automated, and Kenja can train and fine-tune the system. For instance, it can be taught to forget certain words or trained to understand a balance sheet in order to do financial tasks such as due diligence.
“You are kind of building a wall around a set of information and telling it to only use what’s in this area,” explained Katagi. “Having 85–90 percent accuracy—which is what current generative AI, such as ChatGPT, Gemini, or Claude, will give you—is not good enough. Private AI models that are fine-tuned and query a closed set of materials can close that gap.”
Private AI is being used in surprising applications. Just as Panasonic has cloned its founder in digital form, Dr. Greg Story is using Kenja to share the teachings of another business luminary, Dale Carnegie. The self-improvement guru from Missouri wrote a book in 1936, How to Win Friends and Influence People, that still counts among the world’s all-time bestsellers. As president of Dale Carnegie Tokyo Japan, Story has been teaching Japanese businesspeople about leadership, communications, and other skills in Dale Carnegie seminars for the past 14 years. Dale Carnegie started in Japan in 1963.
Since learning about the impact of content marketing, he has built up an enormous corpus consisting of white papers, e-books, printed books, course manuals, 270 two-hour teaching modules, as well as video and audio recordings that include hundreds of podcast episodes. He has penned a series of books himself in English and Japanese that includes Japan Sales Mastery, Japan Business Mastery, Japan Presentations Mastery, and Japan Leadership Mastery.
“If you like the cut of our jib and you want a Dale Carnegie point of view and a curated, trustworthy response, we provide that through this AI.”
The material was scattered in different places, and when clients began asking for on-demand training, Story decided to get ahead of the curve by including all his company’s content in AI-curated form, something public chatbots cannot do.
“ChatGPT will give you everything it can scrape together, but it’s everything and therefore nothing,” said Story. “You get generic answers, and you don’t know if they’re trustworthy. But if you like the cut of our jib and you want a Dale Carnegie point of view and a curated, trustworthy response, we provide that through this AI.”
Story thinks the technology can benefit businesses that have substantial bodies of work to draw on, but those that don’t will get thin answers. He adds that using tools such as those from Kenja will not only help his company learn about the benefits of AI, but it will also give it an edge over competitors. He plans to roll out his AI offerings in 2025, delivering customized responses to students’ questions in English or Japanese on topics ranging from sales to diversity, equity, and inclusion.
Could there be a Dale Carnegie version of the Matsushita chatbot one day?
Kenja has begun working with Dale Carnegie’s global team to do just that, and has developed a prototype revival of Dale Carnegie’s voice, avatar, and writing style. The writing style and word generation are done with Kenja RAG AI technology.
“Carnegie became a global superstar in a non-digital world,” noted Story. “There’s no question we can get an AI to read a script generated in his style, in his voice. It’s amazing.”
Strengthening Cyber Risk Management
ACCJ member Ted Sato shares how his new cybersecurity book, written in collaboration with Keidanren, came about and discusses the issues it addresses.
Keidanren collaboration delivers book with practical advice to corporate leaders
As concern about cyber risk grows in Japan, a new book by veteran American Chamber of Commerce in Japan member and Marsh Japan, Inc. Senior Vice President Ted Sato aims to help corporate management find the most effective approach to mitigating risk and effectively responding to events.
Sato authored the book with Toshinori Kajiura, a member of Keidanren (the Japan Business Federation) and a senior researcher for information and communications technology policy at Hitachi. Kajiura was previously chair of Keidanren’s Working Group on Cybersecurity Enhancement.
🔼 Watch the video above for more insights from Sato himself.
Published in February by the Nikkan Kogyo Shimbun, a Japanese industry newspaper, Strengthening Cyber Risk Management: A Keidanren Handbook to Cyber Risk Management is designed to provide corporate managers with practical guidance for dealing with cyber risk.
Not to be confused with cybersecurity, cyber risk is defined by the US Department of Commerce’s National Institute of Standards and Technology as the “risk of financial loss, operational disruption, or damage from the failure of the digital technologies employed for informational and/or operational functions introduced to a manufacturing system via electronic means from the unauthorized access, use, disclosure, disruption, modification, or destruction of the manufacturing system.”
Sato told The ACCJ Journal that the book, which spans more than 200 pages, was written by professionals from the battlefield in easy-to-understand language. “We wanted corporate managers to be able to ask effective questions at the earliest stages of any cyber risk event. That is very important.”
“We wanted corporate managers to be able to ask effective questions at the earliest stages of any cyber risk event. That is very important.”
The idea came after a series of events last May which Sato conceived with Nikkan Kogyo Shimbun. The well-received sessions showed corporate managers how to deal with cyber risk, not solely as a technical issue but to emphasize management and factors related to organizational culture.
Keidanren had been hosting its own events since 2014, working to change the mind-set of corporate management on this critical issue. The organization built on Sato’s efforts to bring together professionals with similar motivation to create the Cyber Risk Management Japan Study Group, which was a supporting contributor to the book.
These efforts were also supported by the late Hiroaki Nakanishi, who was chair of Hitachi and Keidanren and contributed the foreword.
The book’s core advice draws on a 2014 report by the Internet Security Alliance and the National Association of Corporate Directors’ handbook on cyber risk, which recommends a one-team approach to corporate management. Beginning with the importance of expert advice from outside the company, the book advises an “art of science” approach that balances technology, human factor management, and operational excellence to ensure an organization’s readiness, response and recovery, and recurrence prevention.
The book has been well received by reviewers for its practical guidance.
“It is very meaningful to promote cooperation with experienced US firms at this early stage for Japanese companies,” Sato said. “If all goes well, next we plan to make an English version to share in Asia.”
The Case of the Missing Startups
University and government venture funds play a much larger role in Japan than they do in Western countries. Yet we see fewer biotechnology startups here compared with, say, the United States, which is home to eight of the top 10 highest-funded ventures. Why?
Why biotechs find it hard to get going in Japan
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University and government venture funds play a much larger role in Japan than they do in Western countries. Yet we see fewer biotechnology startups here compared with, say, the United States, which is home to eight of the top 10 highest-funded ventures. Why?
I explored this with Dr. Hiroaki Suga, co-founder of biotech company PeptiDream Inc., in a recent episode of my podcast Disrupting Japan. A professor at the University of Tokyo, Suga did his post-doctoral study under Nobel Prize-winning biologist Jack Szostak at Harvard Medical School. As an academic and a researcher, Suga knows well the dynamics at play in biotech development and application in Japan.
With PeptiDream, which has created a platform for the discovery of highly diverse, non-standard peptide libraries that can be developed into peptide-based therapeutics, Suga has taken a different approach to funding. And it has paid off.
Founded in 2006, PeptiDream is now worth more than $3 billion and collaborates with many of the world’s largest pharmaceutical companies, including American Chamber of Commerce in Japan (ACCJ) members Eli Lilly Japan K.K., Bayer Yakuhin, Ltd., AstraZeneca K.K., and Novartis.
Less is More
What I learned from our discussion is that, in this situation, smaller investments may lead to better results.
“If you have $10 million, you will just burn through it,” Suga said, adding that less capital will keep you focused and get results that can lead to bigger things.
In PeptiDream’s seed round, it received $1 million from The University of Tokyo Edge Capital Partners Co., Ltd., a Japan-based seed- and early-stage deep-tech venture capital firm.
With limited funds, “You need to really develop technology that will allow you to collaborate with big pharmaceutical companies,” Suga explained. These companies set criteria, and don’t give you money immediately. “Once you reach [one set of] criteria, you can get money. Then you get to another stage and you get more money,” he said.
This approach carries less risk for pharmaceutical companies, and Suga sees little risk for PeptiDream, because he is confident that they can meet the criteria.
Obstacles
This unusual approach has worked well for PeptiDream, so why don’t we see more biotech startups succeeding this way in Japan?
Suga said there are several reasons.
“Venture capitalists are not investing in risky companies, and biopharmaceutical companies are high risk,” he explained. “If you are developing business software, after six months, you know if it isn’t working. But drug development is a long-term commitment.”
“The first is that venture capitalists are not investing in risky companies, and biopharmaceutical companies are high risk,” he explained. “If you are developing business software, after six months, you know if it isn’t working. But drug development is a long-term commitment. Venture capitalists have to wait, and they may not be able to do so. They may need to wait 10 years to realize the potential, but they are looking for five.”
“The second reason is that Japanese society prefers to go with what’s known,” he continued. In this case, it means that talent heads for the largest pharmaceutical companies, which are seen as stronger and a safe harbor. “For example, all my students go to big pharma. They don’t go to PeptiDream.”
But this isn’t so much a case of risk aversion—often cited as an obstacle to success in Japan—as one of familiarity. Their parents know the names of the big players, but not of small ones such as PeptiDream.
Large Japanese companies tend to have little interest in helping smaller ones. This chasm is one that the ACCJ is attempting to bridge with its Healthcare x Digital initiative, which completed its second annual competition in November.
Spin-off vs. Startup
The third obstacle that Suga cited is the fact that many startups in Japan are research units that have been spun off from large companies that chose to leave Japan. “They had a very good team here, so they decided to spin off. They already have a background from big pharma and continue doing [what they were doing],” he explained. “That means that they aren’t hugely different from the big companies.”
In the end, Suga said that the biggest change that needs to take place for Japan to become more fertile ground for biotech startups must be made at the university level.
“Professors really need to work hard to get technology to be very practical, to be very robust. You really have to put forth effort to get to the end,” he said. “Then, the Japanese government needs to support this type of research. That’s very critical.”
Investing in Smart Agriculture
AI gets a lot of attention these days, but its application to farming is not often in the spotlight. Sagri Co., Ltd. uses AI, machine learning, and mapping technologies to solve social problems. I had the opportunity to talk with CEO Shunsuke Tsuboi about the challenges that agricultural technology startups in Japan face when it comes to funding, as well as the benefits of their technology.
Japan startup Sagri is transforming family farming with AI
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Artificial intelligence (AI) gets a lot of attention these days, but its application to farming is not often in the spotlight.
Recently, I had the opportunity to talk with Shunsuke Tsuboi, chief executive officer of Sagri Co., Ltd., which uses AI, machine learning, and mapping technologies to solve social problems.
On my podcast, Disrupting Japan, Tsuboi and I discussed the challenges that agricultural technology (agtech) startups in Japan face when it comes to funding, as well as the benefits of their technology.
Taking Root
Sagri was founded in June 2018 and uses satellite imaging and data to analyze farmland. The technology scans areas of up to 10 hectares in size, making it particularly suited to Japan, where farms are generally small. The data can be accessed using a smartphone app, and the goal is to help farmers better understand the condition of their soil and identify the best time for harvesting.
The idea for the company took shape in a laboratory at Yokohama National University, where Tsuboi is a mechanical engineering graduate student. His lab is using space-based technology to examine soil, and he and his business partners have been able to apply some of this to their platform, which shares the name of the company.
Applications
If you’ve walked around the Japanese countryside, you’ve probably seen small plots of abandoned farmland. Sometimes these even intermingle with residences in neighborhoods not far outside the capital.
Whether farmland is in use or abandoned makes a difference from a tax perspective, so the government manually checks the status of land each year. The AI behind Sagri’s analysis can determine with 90-percent accuracy whether a field is abandoned, drastically reducing the amount of work required of government staff.
Apart from taxation, the government is also interested in identifying farmland that can be revitalized. Satellite data that provides soil analysis can make that process easier.
Tsuboi noted that a big reason for the abandonment is that the farmers are getting older and are unable to maintain the land. One benefit of the Sagri platform is that machines can receive the data analysis and automatically perform tasks such as applying fertilizer.
Beyond Japan
Agtech is an area in which Japan has a great opportunity to be a world leader, and Sagri is putting its technology to work in India, where there are also many small farms. But getting the financing needed to keep operations going can be difficult. Sagri believes it has a solution.
“Many Indian farmers need loans, but they don’t have the chance to get them,” Tsuboi said. Because there are so many farmers, it is difficult for banks to spread enough money around. To have a better chance of funding, farmers want to show banks that they are a good investment, he explained. Banks cannot get that sort of information using present methods, but the satellite data analysis provided by Sagri can allow them to check the farmland’s condition and potential yields.
Tsuboi sees Africa as the company’s next market, noting potential in countries such as Kenya and Rwanda. Areas of Southeast Asia are also within Sagri’s sights.
Funding
There are not many agtech startups in Japan, but it seems that there should be. With lots of small farms, lots of creative people working on agtech at universities, and venture capitalists (VCs) with money to invest, why don’t we see more?
Tsuboi feels one reason is that VCs and the government both see farmland as low-growth opportunities. And attracting money from abroad, such as from Silicon Valley VCs, is not easy because they are focused on large-scale industrial farming. The farms on which Sagri is focused in Japan and India are too small to attract their interest.
But Sagri has had some success inside Japan, and announced in June that they have secured ¥155 million ($1.4 million) in funding from a group led by Real Tech Holdings Co., Ltd., who was joined by Minato Capital Co., Ltd., Senshu Ikeda Capital Co., Ltd., and Hiroshima Venture Capital Co., Ltd. Also participating is Bonds Investment Group Co., Ltd., whose Hyogo Kobe Startup Fund, established in March, is making its first investment.
Sagri is a great example of a Japanese startup that can assist people at home and also have a much bigger impact—and earn a much bigger profit—abroad. Globally, the company can help millions of small family farms thrive, and they can bring great returns for investors in the process.