The global AI market that no one is watching

The recent publication of a new United Nations report has only furthered this fueled the world’s growing interest in artificial intelligence (AI). Most of this global AI attention has focused across the United States and China, home to many of the world’s leading foundation model developers. Other parts of the planet have also received notable attention – from Europe AI law to the efforts of Saudi Arabia and the Emirates woo new startups to the Gulf.

However, there is one region that has not received as much global attention: Southeast Asia. With the ten different member states of the Association of Southeast Asian Nations (ASEAN) – Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand and Vietnam – Southeast Asia is quietly becoming an emerging hotspot in terms of A.I. Thanks to domestic companies, delicate geopolitics and the entry of foreign players, Southeast Asia’s ongoing AI race offers unique lessons that global policymakers, investors and technologists should keep a close eye on.

Southeast Asia is already one of the most economically important regions in the world. Taken together, this is the GDP of the ASEAN states would being the fifth largest economy in the world. The middle class in the region is composed of about 200 million people – roughly two-thirds of the entire population of the United States. This importance, in turn, will only increase. In 2050, Indonesia is is expected to be the fourth largest economy in the world, while the individual GDP of the Philippines, Thailand and Malaysia are equal be able to exceed $1 trillion.

The region’s economic weight makes it a lucrative market for global technology companies. However, Southeast Asia has unique regional dynamics that make AI adoption more difficult. The region has nine official state languages, including Thai, Malay and Bahasa Indonesia, meaning AI models intended for the region must have strong multilingual capabilities. Despite the need, contextual knowledge and languages ​​from Southeast Asia are underrepresented in the datasets on which many Western AI models are trained.

For example, only 0.5 percent of the training dataset for Meta’s Llama 2 large language model (LLM) includes Southeast Asian languages, despite the region representing 8.45 percent of the world’s population. Due to these limitations, Southeast Asian users have found that when they input Thai or Bahasa Indonesia texts in large language models, many LLMs provide useless answers, often in English.

The result was an opening for homegrown players to build LLMs for the region. Leading the pack is AI Singapore, a national partnership of leading AI research centers in the country. Their debut model, SEA-LION LLM, has 13 percent of its training dataset in Southeast Asian languages, which AI Singapore says makes SEA-LION more culturally attuned. Separately, Thailand’s Jasmine Group, a major communications technology company, is also reportedly in the process of building a Thai LLM. Meanwhile, the Indonesian startup Yellow.ai has built a regional LLM covering 11 languages ​​in the country, building on Meta’s open-source Llama-2 model.

These homegrown players in Southeast Asia are worth watching for several reasons. First, unlike most companies in the United States and China, some of the leading AI players in Southeast Asia are not purely private companies. AI Singapore, for example, is a public-private partnership of AI startups and public research institutions. If these players manage to build state-of-the-art regional LLMs that gain significant traction, they could provide unique lessons for other global policymakers and executives on how to launch useful public-private partnerships to build advanced AI systems .

Second, if these homegrown LLMs gain more traction in the region than American or Chinese LLMs, the result could also encourage the development of similar, culturally-specific models in other parts of the world.

But players from China and the United States are also active in the region. In fact, Southeast Asia has a significant level of business competition between American and Chinese companies to meet demand in the region. Most recently, for example, Alibaba’s DAMO Academy – the Chinese company’s research institute launched SeaLLM, a new model focused on Southeast Asian languages. Meanwhile, Microsoft CEO Satya Nadella and Apple CEO Tim Cook recently visited Southeast Asia, while Amazon Web Services plans to add Malaysia as one of the new regions this year.

Ultimately, this competition is important. Generative AI is a notoriously capital-intensive industry, so the companies that manage to generate more revenue in the region will be better equipped to cover the expensive costs of model development and fund robust improvements in AI capabilities.

In addition to companies, both the US and Chinese governments are also becoming increasingly involved in the AI ​​landscape in Southeast Asia. China has recently started host an annual forum on China-ASEAN cooperation in artificial intelligence, featuring government officials and other key leaders. It has also set up a China-ASEAN AI Innovation Center in Guangxi province has started more than 119 projects in the field of AI. The United States, meanwhile, has launched its digital strategy efforts, including a new partnership between the US Agency for International Development (USAID) and Google to usage AI and other digital tools to map the effects of climate change in the Mekong Delta.

In turn, watching China-US competition in AI in Southeast Asia could provide several valuable lessons. For U.S. and Chinese policymakers, the overlapping relationships could fuel concerns that the region is facilitating the flow of sensitive technology to the other side. The United States is are reportedly already trying to find ways to prevent the sale of sensitive AI chips from Singapore and Malaysia to China.

In the long term, these concerns could lead Washington and Beijing to push Southeast Asian countries and companies to limit their exposure to the other side. However, many in Southeast Asia are opting for neutrality and want to reap the benefits of connections to the two largest AI ecosystems in the world. The way Southeast Asian countries try to mitigate both sides and deal with these risks could also influence how other countries respond to these geopolitical tensions.

In addition to the United States and China, there is another country that is introducing AI into Southeast Asia: Japan. Tokyo has long had significant trade ties with Japanese companies in Southeast Asia being major investors in the Southeast Asian markets. More recently, Japan is poised to expand into AI. In July, Japanese Prime Minister Kishida Fumio spoke launched a public-private partnership to support Japanese companies in developing LLMs for Southeast Asia, including potentially subsidizing companies such as Japan’s Elyza, which is creating a Thai LLM. The Japanese government is consider donating computing resources, such as graphics processing units (GPUs), to help increase the region’s computing capacity. Japanese companies such as Sakura Internet Are It also aims to become major cloud service providers for the region.

Global technologists, investors and policymakers should keep a close eye on Japan’s moves in the region. Numerous countries outside the United States and China, including France, Saudi Arabia and more, are trying to carve out a niche in the AI ​​race by provide supporting domestic AI development, launch new investment funds, and more. If Japan’s efforts help its companies become major players in Southeast Asia’s LLM and cloud markets, then other governments and companies around the world could look to emulate Japan’s efforts to also fuel their own overseas expansion support companies. However, if Japan’s efforts wane, it could reinforce the belief that AI development remains a two-horse race between the United States and China, discouraging other countries and companies from following a similar path.

In many ways, the AI ​​race in Southeast Asia is one to watch. The region provides a unique case for global policymakers, technologists, and investors to observe how homegrown startups seek to compete with global giants, how countries can hedge geopolitical risks in the age of AI, and how countries outside the United States and China are increasing their place in the AI ​​ecosystem. How generative AI adoption plays out in the region will have significant implications for our future.