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Worldwide, states are investing hundreds of billions into what's termed “sovereign AI” – developing their own AI models. From the city-state of Singapore to the nation of Malaysia and the Swiss Confederation, states are vying to build AI that grasps local languages and local customs.

The International AI Battle

This trend is an element in a larger international race led by large firms from the United States and China. While organizations like OpenAI and a social media giant invest substantial funds, developing countries are also making their own gambles in the AI field.

But with such tremendous investments at stake, can smaller states achieve significant benefits? As noted by a specialist from a prominent research institute, If not you’re a wealthy nation or a large corporation, it’s a significant burden to create an LLM from the ground up.”

National Security Concerns

Numerous states are unwilling to use foreign AI technologies. Across India, for example, American-made AI systems have occasionally been insufficient. An illustrative case saw an AI agent deployed to instruct students in a isolated community – it spoke in the English language with a strong US accent that was nearly-incomprehensible for regional students.

Furthermore there’s the national security dimension. In the Indian security agencies, relying on specific international AI tools is seen as inadmissible. Per an founder noted, There might be some unvetted training dataset that may state that, oh, a certain region is separate from India … Using that certain AI in a security environment is a big no-no.”

He continued, I’ve consulted experts who are in defence. They want to use AI, but, setting aside specific systems, they prefer not to rely on Western systems because data might go abroad, and that is completely unacceptable with them.”

Domestic Initiatives

In response, some nations are backing national ventures. A particular such effort is in progress in India, wherein an organization is working to develop a domestic LLM with public backing. This project has dedicated approximately 1.25 billion dollars to machine learning progress.

The founder imagines a system that is significantly smaller than top-tier tools from American and Asian corporations. He explains that the country will have to offset the financial disparity with talent. Based in India, we lack the option of pouring huge sums into it,” he says. “How do we contend against for example the enormous investments that the United States is devoting? I think that is where the fundamental knowledge and the intellectual challenge is essential.”

Regional Priority

Throughout the city-state, a public project is backing language models educated in local regional languages. Such tongues – including the Malay language, Thai, Lao, Indonesian, Khmer and more – are commonly poorly represented in American and Asian LLMs.

I wish the experts who are building these national AI models were informed of how rapidly and the speed at which the leading edge is progressing.

An executive involved in the program explains that these models are created to complement bigger models, as opposed to displacing them. Tools such as a popular AI tool and another major AI system, he comments, commonly find it challenging to handle native tongues and local customs – interacting in awkward Khmer, for instance, or proposing pork-based meals to Malay users.

Developing local-language LLMs permits national authorities to include cultural sensitivity – and at least be “informed users” of a advanced tool developed overseas.

He continues, I am cautious with the concept national. I think what we’re trying to say is we wish to be more accurately reflected and we aim to understand the abilities” of AI technologies.

Multinational Partnership

Regarding countries trying to carve out a role in an growing global market, there’s another possibility: collaborate. Experts associated with a well-known university recently proposed a government-backed AI initiative allocated across a consortium of middle-income countries.

They refer to the project “a collaborative AI effort”, in reference to the European productive strategy to create a competitor to Boeing in the 1960s. Their proposal would see the formation of a public AI company that would pool the capabilities of various countries’ AI projects – including the UK, the Kingdom of Spain, Canada, Germany, Japan, Singapore, South Korea, the French Republic, the Swiss Confederation and the Kingdom of Sweden – to develop a strong competitor to the US and Chinese giants.

The lead author of a study outlining the concept states that the concept has gained the attention of AI officials of at least a few countries so far, along with multiple sovereign AI organizations. While it is presently targeting “developing countries”, less wealthy nations – Mongolia and Rwanda included – have likewise shown curiosity.

He explains, In today’s climate, I think it’s an accepted truth there’s diminished faith in the promises of the existing White House. Experts are questioning for example, can I still depend on any of this tech? In case they decide to