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Worldwide, nations are investing hundreds of billions into what is known as “sovereign AI” – creating national artificial intelligence technologies. From the city-state of Singapore to Malaysia and the Swiss Confederation, states are racing to build AI that grasps native tongues and cultural nuances.

The International AI Battle

This trend is an element in a broader global contest dominated by major corporations from the United States and China. While organizations like OpenAI and a social media giant invest substantial funds, developing countries are additionally making independent investments in the artificial intelligence domain.

But amid such vast investments involved, is it possible for smaller countries achieve significant gains? According to a analyst from an influential policy organization, “Unless you’re a rich nation or a big firm, it’s quite a burden to develop an LLM from nothing.”

National Security Concerns

Many nations are unwilling to depend on overseas AI models. Across India, for instance, US-built AI tools have sometimes fallen short. One instance featured an AI agent deployed to educate pupils in a remote area – it interacted in the English language with a pronounced Western inflection that was hard to understand for regional listeners.

Furthermore there’s the national security aspect. In India’s security agencies, employing specific foreign models is seen as inadmissible. According to a founder noted, “It could have some unvetted training dataset that might say that, for example, a certain region is separate from India … Utilizing that certain system in a security environment is a big no-no.”

He added, I’ve consulted people who are in the military. They wish to use AI, but, forget about certain models, they prefer not to rely on Western systems because details could travel overseas, and that is absolutely not OK with them.”

Domestic Initiatives

In response, several countries are funding national initiatives. An example such initiative is underway in India, in which an organization is working to build a domestic LLM with government backing. This effort has committed about 1.25 billion dollars to machine learning progress.

The developer foresees a model that is significantly smaller than premier systems from American and Asian tech companies. He explains that the country will have to make up for the resource shortfall with expertise. “Being in India, we don’t have the advantage of pouring billions of dollars into it,” he says. “How do we compete with say the enormous investments that the US is investing? I think that is the point at which the fundamental knowledge and the strategic thinking is essential.”

Native Emphasis

In Singapore, a public project is backing AI systems educated in local regional languages. These languages – including Malay, the Thai language, the Lao language, Bahasa Indonesia, Khmer and others – are commonly inadequately covered in Western-developed LLMs.

I hope the individuals who are creating these independent AI tools were conscious of the extent to which and how quickly the frontier is advancing.

A leader involved in the project says that these models are designed to supplement larger systems, rather than displacing them. Platforms such as a popular AI tool and another major AI system, he says, commonly struggle with local dialects and local customs – interacting in awkward the Khmer language, as an example, or recommending non-vegetarian recipes to Malay individuals.

Creating native-tongue LLMs permits national authorities to include cultural nuance – and at least be “informed users” of a sophisticated system developed elsewhere.

He further explains, I am cautious with the word independent. I think what we’re aiming to convey is we want to be better represented and we want to understand the capabilities” of AI systems.

International Collaboration

Regarding states seeking to carve out a role in an intensifying international arena, there’s a different approach: team up. Researchers associated with a prominent institution recently proposed a government-backed AI initiative shared among a consortium of emerging states.

They call the initiative “Airbus for AI”, modeled after Europe’s effective strategy to build a competitor to a major aerospace firm in the 1960s. Their proposal would entail the creation of a government-supported AI organization that would merge the assets of different nations’ AI projects – such as the UK, Spain, Canada, Germany, the nation of Japan, Singapore, South Korea, France, Switzerland and Sweden – to develop a competitive rival to the US and Chinese leaders.

The primary researcher of a study outlining the proposal notes that the idea has gained the attention of AI officials of at least three countries so far, along with several state AI firms. While it is now focused on “middle powers”, less wealthy nations – Mongolia and Rwanda for example – have likewise shown curiosity.

He comments, “Nowadays, I think it’s just a fact there’s diminished faith in the commitments of this current US administration. Experts are questioning such as, is it safe to rely on these technologies? What if they decide to