Why Japan is lagging behind in generative A.I. — and how it can create its own large language models
Japan is known for its futuristic technology. But the nation is lagging behind in the generative AI race and is trying to create its own large language models.
Mr.cole_photographer | Moment | Getty Images
Countries are racing to develop their own generative artificial intelligence algorithms, but high tech Japan is already behind.
Generative AI has been the trendiest topic in tech since OpenAI made waves with its chatbot ChatGPT. Breakthroughs in generative AI possess the potential to fuel a 7% increase in global GDP, or almost $7 trillion, over the next decade, according to Goldman Sachs research.
Key to generative AI development are large language models which underpin the likes of ChatGPT and Baidu’s Ernie Bot, capable of processing vast data sets to generate text and other content. But Japan is currently trailing behind the U.S., China and the EU in developing these algorithms, said Noriyuki Kojima, co-founder of Japanese LLM startup Kotoba Technology.
Chinese organizations, including tech giants Alibaba and Tencent, have launched at least 79 LLMs domestically over the past three years, Reuters reported in May citing research from a consortium of state-run institutes. U.S. corporate powerhouses such as OpenAI, Microsoft, Google and Meta play a significant role in propelling the country’s LLM advancements, said Kojima.
Japan lagging behind in generative AI
Japan, however, lags behind the U.S., China and Europe in the scale and speed of its LLM development.
“Japan’s trailing position in the field of generative AI largely stems from its comparative shortcomings in deep learning and more extensive software development,” said Kojima.
Deep learning requires a “robust community of software engineers” to develop necessary infrastructure and applications, Kojima added. Japan, however, will face a deficit of 789,000 software engineers by 2030, according to the Ministry of Economy Trade and Industry. The nation is now ranked 28th out of 63 countries in terms of technological knowledge, according to the IMD World Digital Competitiveness Ranking.
Japan also faces hardware challenges as LLMs need to be trained using AI supercomputers like IBM’s Vela and Microsoft’s Azure-hosted system. But no private company in Japan possesses its own “world-class machine” with those capabilities, Nikkei Asia reported.
Government-controlled supercomputers like Fugaku therefore “hold the key” to Japan’s pursuit of LLMs, Kojima explained.
“Access to such large-scale supercomputers forms the backbone of LLM development, as it has traditionally been the most significant bottleneck in the process,” he said.
How Japan’s supercomputers can help
Tokyo Institute of Technology and Tohoku University plan to use Fugaku to develop LLMs based primarily on Japanese data in collaboration with the supercomputer’s developers Fujitsu and Riken, Fujitsu announced in May.
The organizations plan to publish their research results in 2024 to help other Japanese researchers and engineers develop LLMs, Fujitsu added.
The Japanese government will also invest 6.8 billion yen ($48.2 million), about half the total cost, to build a new supercomputer in Hokkaido that will begin service as early as next year, Nikkei Asia reported. The supercomputer will specialize in LLM training to promote Japan’s development of generative AI, said Nikkei Asia.
In April, Japanese Prime Minister Fumio Kishida said the country supports the industrial use of generative AI technology. Kishida’s remarks followed his meeting with OpenAI CEO Sam Altman, who said the company is looking to open an office in Japan.
Japanese companies pursuing generative AI
Big Tech players have also joined the fray to boost Japan’s standing in generative AI. In June, SoftBank’s mobile arm said it plans to develop its own generative AI platform, reported local media. This was underscored by SoftBank CEO Masayoshi Son’s announcement that the investment firm plans to shift from “defense mode” to “offense mode” and intensify its focus on AI.
“We would like to be [in] the leading position for the AI revolution,” Son said during a shareholders’ annual general meeting.
SoftBank Group sold its 85% stake in SB Energy to Toyota Tsusho in April and recently agreed to sell its 90% stake in U.S. investment manager Fortress Investment Group, Nikkei Asia reported. Trimming these other investments helps SoftBank free up cash, allowing it to focus largely on AI through its Vision Fund venture capital investment unit.
SoftBank-owned chip design company Arm is also set to pursue a U.S. IPO listing later in the year. “It will be by far the biggest IPO that’s hit the world,” said Amir Anvarzadeh, Japan equity market strategist at Asymmetric Advisors.
The IPO will provide a hefty sum to boost funds at SoftBank, which reported a record 4.3 trillion yen loss at Vision Fund for its fiscal year ending March 31.
Arm originally sought to raise between $8 billion and $10 billion. But with demand for semiconductor chips “through the roof,” Anvarzadeh suggested Arm could raise as much as $50 billion to $60 billion — or “85% of SoftBank’s market cap.”
He said SoftBank’s share price will likely rise, although this does not guarantee the success of its AI efforts.
“Fundamentally, I don’t think SoftBank is going to change Japan’s landscape … they are no savior of Japan’s AI,” he said.
Japanese telecommunications company NTT also announced plans to develop its own LLM this fiscal year, aiming to create a “lightweight and efficient” service for corporations. NTT said it will funnel 8 trillion yen over the next five years into growth areas like data centers and AI, a 50% increase from its previous level of investment.
Local media reported that digital ad company CyberAgent released an LLM in May that enables companies to create AI chatbot tools. The company said it is one of few “models specialized in the Japanese language and culture.”
While it has yet to catch up in the generative AI space, Japan is making its first stride with these private sector efforts. Once a “robust infrastructure” is established, the remaining technical challenges are likely to be “significantly mitigated” by using open-sourced software and data from previous pioneers, Kojima said. Bloom, Falcon and RedPajama are all open-sourced LLMs trained on vast amounts of data that can be downloaded and studied.
However, companies venturing into this field should anticipate competition spanning a “relatively longer timeframe,” Kojima said. Developing LLMs requires substantial capital investment and a workforce highly skilled in natural language processing and high-performance computing, he explained.
“SoftBank and NTT, joining this competition, will not change the AI landscape in the short-term.”
AI regulation in Japan
Japanese tech companies’ increased participation in generative AI development coincides with a positive stance on AI adoption in other sectors. Over 60% of companies in Japan have a positive attitude toward using generative AI in their operations, while 9.1% are already doing so, a survey by Teikoku Databank found.
Hitachi has established a generative AI center to promote employee’s safe and effective use of the technology, it said in May. With the expertise of data scientists, AI researchers and relevant specialists, the center will formulate guidelines to mitigate the risks of generative AI, the conglomerate said.
Japan will even consider government adoption of AI technology like ChatGPT, provided that cybersecurity and privacy concerns are resolved, said Chief Cabinet Secretary Hirokazu Matsuno.
As Japan becomes more open to the use of generative AI, the government should formulate and facilitate soft guidelines regarding its use, while assessing the need for hard regulation based on specific risks, said Hiroki Habuka, research professor at Kyoto University’s Graduate School of Law.
“Without clearer guidance on what actions companies should take when using generative AI, practices may become fragmented,” the professor said.
A Nvidia RTX PRO 6000 Blackwell Server Edition on display during VivaTech 2025 tech conference in Paris, France.
Chesnot | Getty Images
British artificial intelligence infrastructure firm Nscale is raising heaps of cash as it looks to ramp up the deployment of AI data centers across Europe.
Nscale, which is based in London, said Thursday that it has raised $1.1 billion in a bumper Series B funding round. The investment was led by Aker, the Norwegian industrial investment company, with additional participation from a raft of firms including Nvidia, Nokia and Dell.
The investment highlights continued demand for high-powered computing infrastructure, which is required to train and run powerful foundational AI models from companies like OpenAI, Microsoft and Google.
Nscale has become a central player in Britain’s ambition to become a global AI powerhouse. Last week, the likes of Microsoft, Nvidia and OpenAI announced multibillion-dollar projects involving Nscale to build out AI computing infrastructure across the U.K.
“We are creating one of the largest global [infrastructure] platforms of its kind – purpose-built to meet surging demand and unlock breakthroughs at unprecedented scale,” said Josh Payne, Nscale’s CEO and co-founder, in a statement.
“This allows Nscale to provide our customers access to scarce, and highly sought after, compute capacity and rapidly accelerate the build-out of secure, compliant and energy-efficient AI infrastructure,” he added.
Nscale was spun out from Arkon Energy, an Australian cryptocurrency mining firm, in 2023 to address soaring demand for data centers capable of handling AI workloads.
It is working with OpenAI in the U.K. and Norway to build new data centers as part of the ChatGPT maker’s Stargate investment project. Nscale said that part of the Series B funding would go toward “enabling the rapid rollout” of the Stargate data center projects in Europe.
The company is committing $1 billion for the Norwegian project, with the goal of racking up 100,000 Nvidia graphics processing units (GPUs) at the site before 2027. The U.K. site, meanwhile, will house 8,000 GPUs in its first phase early next year, with the option to expand capacity to around 31,000 GPUs over time.
Light uses artificial intelligence to automate companies’ finance and accounting functions.
Light
Danish startup Light is the latest in a series of European tech firms raising cash as venture capitalists search for the next big thing in artificial intelligence.
Founded in 2022, Light develops software that uses AI to automate various functions that exist within businesses’ finance teams, including accounting, bookkeeping and financial reporting.
The Copenhagen-headquartered company told CNBC that it had raised $30 million in a Series A funding round led by Balderton Capital, an early investor in fintech unicorns Revolut and GoCardless.
Atomico, Cherry Ventures, Seedcamp and Entrée Capital also invested in the round, along with angel investors including Hugging Face co-founder Thomas Wolf and Meta board member Charlie Songhurst.
Light plans to use the cash to “double down on the commercial side” of the business, Jonathan Sanders, Light’s CEO and co-founder, told CNBC. The startup recently opened an office in London and says it is planning to open one in New York to meet U.S. demand.
Light isn’t the only startup out there using AI to streamline companies’ finance and accounting processes.
Pigment, a business planning and forecasting platform designed to be more user-friendly than Microsoft Excel, last year raised $145 million at a valuation north of $1 billion. More recently, accounting software startup Pennylane raised 75 million euros ($88.4 million), doubling its valuation to 2 billion euros.
Currently, the market for software that helps companies manage their finances is dominated by industry behemoths like Microsoft, Oracle and SAP. However, these systems can often be cumbersome, requiring specialists to “tinker around the edges for a year or two just to make it work,” according to Sanders.
“We service fast-growing, fast-scaling companies who need a system where they can expand really fast,” Sanders told CNBC. Light’s customers include Lovable, the buzzy Swedish AI firm recently valued at $2 billion, and Sana Labs, which is being acquired by Workday for $1.1 billion.
Sanders said AI can rapidly transform how companies handle their finances. “The future of numbers is text,” he says. For example, rather than sifting through company policies to find a team’s meal allowance, this can be automated by an AI agent that has access to the relevant documents.
Moving forward, Light wants to focus on large, enterprise-level customers that struggle with “broken processes and workflows,” according to Sanders. “No human team can continuously analyze, reconcile and update thousands of pages of policies for coherence,” he told CNBC.
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