🔗 Share this article

Around the globe, governments are investing hundreds of billions into the concept of “sovereign AI” – creating national AI systems. Starting with the city-state of Singapore to the nation of Malaysia and Switzerland, states are competing to develop AI that grasps native tongues and cultural specifics.

The Global AI Arms Race

This trend is an element in a larger international race dominated by large firms from the US and China. While organizations like OpenAI and Meta invest massive resources, developing countries are also taking sovereign investments in the AI field.

However given such tremendous investments at stake, can developing nations secure significant gains? According to a specialist from a prominent research institute, “Unless you’re a rich state or a major company, it’s a substantial burden to build an LLM from nothing.”

National Security Considerations

Numerous states are unwilling to rely on overseas AI technologies. Throughout the Indian subcontinent, for example, US-built AI solutions have at times fallen short. An illustrative example saw an AI assistant used to instruct students in a isolated community – it communicated in English with a strong Western inflection that was difficult to follow for native users.

Then there’s the state security aspect. For India’s military authorities, relying on particular foreign systems is viewed not permissible. According to a entrepreneur explained, “It could have some arbitrary learning material that might say that, for example, a certain region is separate from India … Employing that certain AI in a security environment is a big no-no.”

He further stated, I’ve discussed with individuals who are in defence. They aim to use AI, but, disregarding certain models, they don’t even want to rely on American systems because information might go outside the country, and that is absolutely not OK with them.”

National Efforts

In response, several nations are supporting local ventures. A particular such a initiative is underway in India, wherein an organization is working to develop a national LLM with public funding. This effort has allocated about a substantial sum to machine learning progress.

The expert imagines a AI that is less resource-intensive than premier tools from US and Chinese firms. He states that the country will have to make up for the resource shortfall with skill. Located in India, we don’t have the luxury of investing massive funds into it,” he says. “How do we contend versus say the enormous investments that the US is pumping in? I think that is the point at which the key skills and the strategic thinking comes in.”

Native Priority

In Singapore, a public project is supporting machine learning tools trained in south-east Asia’s regional languages. These particular tongues – such as the Malay language, the Thai language, the Lao language, Indonesian, Khmer and more – are commonly inadequately covered in American and Asian LLMs.

I hope the people who are creating these independent AI systems were informed of just how far and just how fast the frontier is moving.

An executive engaged in the initiative notes that these models are intended to complement more extensive systems, as opposed to substituting them. Tools such as a popular AI tool and another major AI system, he says, often find it challenging to handle native tongues and culture – speaking in stilted the Khmer language, for instance, or proposing meat-containing dishes to Malay users.

Developing regional-language LLMs enables local governments to code in cultural nuance – and at least be “informed users” of a advanced tool built elsewhere.

He adds, I am prudent with the term sovereign. I think what we’re attempting to express is we want to be more adequately included and we wish to understand the capabilities” of AI technologies.

International Cooperation

For nations trying to carve out a role in an growing global market, there’s a different approach: collaborate. Analysts affiliated with a prominent institution have suggested a state-owned AI venture shared among a consortium of middle-income states.

They call the project “an AI equivalent of Airbus”, modeled after the European effective initiative to create a alternative to Boeing in the 1960s. This idea would entail the formation of a public AI company that would combine the assets of various countries’ AI projects – for example the United Kingdom, Spain, the Canadian government, Germany, Japan, the Republic of Singapore, the Republic of Korea, France, Switzerland and the Kingdom of Sweden – to create a strong competitor to the American and Asian major players.

The lead author of a report setting out the concept says that the concept has drawn the consideration of AI leaders of at least several nations so far, as well as a number of national AI organizations. Although it is currently focused on “mid-sized nations”, developing countries – the nation of Mongolia and Rwanda among them – have likewise expressed interest.

He comments, Currently, I think it’s an accepted truth there’s diminished faith in the promises of the present White House. People are asking like, is it safe to rely on any of this tech? Suppose they decide to