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Around the globe, nations are investing hundreds of billions into the concept of “sovereign AI” – building domestic AI technologies. Starting with Singapore to the nation of Malaysia and the Swiss Confederation, countries are competing to develop AI that understands regional dialects and local customs.

The International AI Competition

This initiative is an element in a larger international competition dominated by major corporations from the US and China. While firms like a leading AI firm and a social media giant invest enormous capital, mid-sized nations are also taking sovereign investments in the AI landscape.

But amid such huge amounts at stake, can developing countries achieve meaningful advantages? As stated by a analyst from an influential policy organization, If not you’re a wealthy state or a large company, it’s quite a burden to create an LLM from scratch.”

National Security Issues

Numerous states are unwilling to depend on overseas AI technologies. In India, as an example, American-made AI tools have at times been insufficient. A particular instance saw an AI tool employed to teach learners in a isolated village – it spoke in English with a strong American accent that was difficult to follow for regional users.

Then there’s the state security aspect. In India’s military authorities, using particular external models is seen as inadmissible. Per an founder noted, It's possible it contains some arbitrary data source that could claim that, oh, Ladakh is not part of India … Using that specific model in a defence setup is a major risk.”

He added, I’ve consulted individuals who are in the military. They aim to use AI, but, setting aside certain models, they prefer not to rely on Western systems because information could travel abroad, and that is totally inappropriate with them.”

National Initiatives

In response, some states are funding local initiatives. One such effort is in progress in India, wherein a firm is striving to create a national LLM with state support. This effort has dedicated approximately a substantial sum to machine learning progress.

The founder foresees a model that is significantly smaller than top-tier tools from US and Chinese tech companies. He explains that the nation will have to compensate for the funding gap with expertise. Based in India, we do not possess the luxury of pouring massive funds into it,” he says. “How do we vie against say the hundreds of billions that the United States is investing? I think that is the point at which the fundamental knowledge and the brain game plays a role.”

Native Priority

Throughout the city-state, a government initiative is funding AI systems educated in south-east Asia’s regional languages. These particular tongues – for example Malay, the Thai language, the Lao language, Indonesian, Khmer and additional ones – are frequently poorly represented in American and Asian LLMs.

I hope the experts who are creating these national AI systems were informed of how rapidly and the speed at which the cutting edge is progressing.

An executive participating in the initiative says that these tools are intended to enhance more extensive AI, as opposed to replacing them. Platforms such as ChatGPT and Gemini, he says, frequently find it challenging to handle local dialects and cultural aspects – interacting in stilted Khmer, as an example, or suggesting meat-containing dishes to Malaysian consumers.

Creating regional-language LLMs enables state agencies to incorporate cultural sensitivity – and at least be “informed users” of a powerful technology created overseas.

He further explains, I am cautious with the term national. I think what we’re attempting to express is we aim to be more accurately reflected and we want to comprehend the abilities” of AI technologies.

Multinational Cooperation

For countries seeking to establish a position in an growing global market, there’s an alternative: collaborate. Experts affiliated with a respected institution recently proposed a government-backed AI initiative shared among a consortium of developing nations.

They refer to the proposal “Airbus for AI”, drawing inspiration from Europe’s effective play to create a rival to a major aerospace firm in the 1960s. Their proposal would involve the creation of a government-supported AI organization that would merge the resources of various states’ AI initiatives – such as the United Kingdom, Spain, the Canadian government, the Federal Republic of Germany, Japan, the Republic of Singapore, the Republic of Korea, the French Republic, the Swiss Confederation and Sweden – to create a competitive rival to the American and Asian giants.

The primary researcher of a report outlining the proposal notes that the concept has drawn the consideration of AI ministers of at least three countries to date, along with multiple state AI firms. Although it is now targeting “developing countries”, developing countries – Mongolia and the Republic of Rwanda for example – have also shown curiosity.

He explains, “Nowadays, I think it’s an accepted truth there’s reduced confidence in the commitments of the existing American government. Individuals are wondering for example, should we trust any of this tech? In case they decide to