The recent release of a new United Nations report has only powered the world’s growing interest in artificial intelligence (AI). Most of this global attention on AI has concentrate on the United States and China, home to many of the world’s leading foundation design developers. Other parts of the planet have also received special attention – from European governments. AI Law to Saudi and Emirati efforts to woo new startups in the Gulf.
There is, however, one region that has not generated as much global interest: Southeast Asia. Encompassing the 10 member states of the Association of Southeast Asian Nations (ASEAN) – Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand and Vietnam – Southeast Asia is becoming an emerging hot spot in AI. . Indeed, through its homegrown businesses, tricky geopolitics, and entry of foreign players, Southeast Asia’s ongoing AI race offers unique lessons that global policymakers, investors, and technologists should monitor closely.
Southeast Asia is already one of the most economically important regions in the world. If we aggregate, the GDP of the ASEAN States would be become the fifth largest economy in the world. The region’s middle class is compound of some 200 million people, or about two-thirds of the total population of the United States. This importance, in turn, will only grow. By 2050, Indonesia East expected to become the world’s fourth largest economy, while the individual GDPs of the Philippines, Thailand and Malaysia can exceed 1,000 billion dollars.
The region’s economic weight makes it a lucrative market for global technology companies. However, Southeast Asia experiences unique regional dynamics that make the use of AI more challenging. The region has nine official state languages, including Thai, Malay and Bahasa Indonesia, meaning AI models for the region must have strong multilingual capabilities. Despite this need, Southeast Asian contextual knowledge and languages are underrepresented in the datasets on which many Western AI models are trained.
For example, only 0.5% of the training dataset for Meta’s Llama 2 Large Language Model (LLM) includes Southeast Asian languages, although the region represents 8.45% of the world population. Due to these limitations, users in Southeast Asia have found that when they to input When texting in Thai or Bahasa Indonesia in large language models, many LLMs return unhelpful responses, often in English.
The result was an opportunity for local stakeholders to create LLMs for the region. Leading the pack is AI Singapore, a national partnership of the country’s leading AI research centers. Their first model, SEA-LION LLM, has 13% of its training dataset is written in Southeast Asian languages, which AI Singapore says makes SEA-LION more culturally responsive. Additionally, Thailand’s Jasmine Group, a major communications technology company, East is also said to have worked on the creation of a Thai LLM. The Indonesian startup Yellow.ai, for its part, built a regional LLM for 11 languages in the country, building on Meta’s open source Llama-2 model.
These local Southeast Asian players are worth watching for several reasons. First, unlike most companies in the United States and China, some of the major AI players in Southeast Asia are not purely private companies. For example, AI Singapore is a public-private partnership bringing together AI startups and public research institutes. If these players succeed in creating cutting-edge regional LLMs that gain popularity, they could offer unique lessons to other policymakers and global leaders on how to launch beneficial public-private collaborations to create advanced AI systems .
Second, if these local 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.
However, Chinese and American actors are not sitting idly in the region either. In fact, Southeast Asia is experiencing strong growth at the business level. competition between American and Chinese companies to meet the region’s demand. For example, Alibaba’s DAMO Academy – the Chinese company’s research institute – recently spear SeaLLM, a new model focused on Southeast Asian languages. Meanwhile, Microsoft CEO Satya Nadella and Apple CEO Tim Cook recently visit Southeast Asia, while Amazon Web Services plans to add Malaysia among its new regions this year.
At the end of the day, this competition matters. Generative AI East This is a notoriously capital-intensive industry, so companies that manage to generate greater revenues in the region will be better equipped to cover the high costs of model development and fund powerful advances in AI capabilities.
Beyond companies, the U.S. and Chinese governments are also becoming increasingly involved in Southeast Asia’s AI landscape. China recently started accommodation an annual forum on China-ASEAN cooperation on artificial intelligence, bringing together government officials and other key leaders. It also established a China-ASEAN AI innovation center in Guangxi province, which has has launched more than 119 AI projects. The United States, meanwhile, has launched its digital strategy efforts, such as a new partnership between the United States Agency for International Development (USAID) and Google to to use AI and other digital tools to map the effects of climate change in the Mekong Delta.
In turn, observing how Sino-US AI competition plays out in Southeast Asia could offer several valuable lessons. For U.S. and Chinese policymakers, the overlapping relationship could fuel fears that the region will enable the flow of sensitive technology to the other side. United States East reportedly previously tried 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 encourage Southeast Asian countries and businesses to limit their exposure to the other side. However, many in Southeast Asia are opting for neutrality, wanting to reap the rewards of ties with the world’s two largest AI ecosystems. How Southeast Asian countries attempt to placate both sides and manage these risks may also influence how other countries respond to these geopolitical tensions.
Beyond the United States and China, another country is making an AI breakthrough in Southeast Asia: Japan. Tokyo has long had significant commercial ties in Southeast Asia with Japanese companies. be major investors in Southeast Asian markets. More recently, Japan is poised to embrace AI. In July, Japanese Prime Minister Kishida Fumio spear a public-private partnership to help Japanese companies develop LLMs for Southeast Asia, including potentially subsidizing companies like Japanese company Elyza, which is doing a Thai LLM. The Japanese government East consider donating computing resources, such as graphics processing units (GPUs), to help strengthen the region’s computing capacity. Japanese companies like Sakura Internet are also aiming to become major cloud service providers for the region.
Technologists, investors and policymakers around the world should closely monitor Japan’s actions in the region. Many countries outside the United States and China, including France, Saudi Arabia and others, are trying to carve out a place in the AI race by provide support for local development of AI, launch new investment funds, and more. If Japan’s efforts make its companies major players in Southeast Asia’s LLM and cloud markets, then other governments and companies around the world may try to emulate Japanese efforts to support expansion as well. abroad of their local companies. However, if Japan’s efforts falter, it could reinforce the belief that AI development remains a two-horse race between the United States and China, dissuading 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 policymakers, technologists and investors around the world to observe how local startups try to compete with global giants, how nations can hedge geopolitical risks in the AI era and how countries outside the United States and China can find solutions. their place in the AI ecosystem. How the adoption of generative AI plays out in the region will have important consequences for our future.
