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Internationally, states are pouring enormous sums into what is known as “sovereign AI” – creating their own artificial intelligence technologies. From Singapore to the nation of Malaysia and the Swiss Confederation, nations are vying to create AI that grasps regional dialects and local customs.

The Global AI Battle

This initiative is a component of a larger international competition led by large firms from the United States and China. While companies like OpenAI and Meta invest massive funds, mid-sized nations are likewise making sovereign investments in the AI field.

However given such vast amounts at stake, is it possible for developing countries secure meaningful gains? As noted by a specialist from a well-known thinktank, “Unless you’re a rich state or a large corporation, it’s quite a challenge to build an LLM from the ground up.”

National Security Issues

Many states are unwilling to rely on overseas AI models. Across India, for instance, US-built AI systems have sometimes proven inadequate. An illustrative case saw an AI tool used to instruct pupils in a distant village – it spoke in English with a pronounced American accent that was nearly-incomprehensible for native listeners.

Then there’s the state security dimension. For India’s security agencies, using specific external AI tools is seen as unacceptable. Per an developer explained, “It could have some arbitrary data source that could claim that, oh, a certain region is separate from India … Using that certain model in a security environment is a major risk.”

He continued, I’ve discussed with people who are in defence. They wish to use AI, but, disregarding particular tools, they prefer not to rely on US technologies because information might go overseas, and that is absolutely not OK with them.”

Homegrown Projects

In response, several states are funding national projects. A particular such initiative is underway in the Indian market, wherein a firm is working to develop a sovereign LLM with government backing. This project has dedicated roughly 1.25 billion dollars to machine learning progress.

The expert imagines a model that is significantly smaller than premier tools from Western and Eastern firms. He notes that India will have to make up for the financial disparity with expertise. “Being in India, we do not possess the luxury of allocating huge sums into it,” he says. “How do we contend with for example the $100 or $300 or $500bn that the United States is pumping in? I think that is the point at which the fundamental knowledge and the brain game plays a role.”

Regional Emphasis

Across Singapore, a government initiative is supporting language models developed in south-east Asia’s native tongues. These dialects – including Malay, the Thai language, Lao, Bahasa Indonesia, Khmer and additional ones – are commonly poorly represented in Western-developed LLMs.

I hope the individuals who are building these independent AI tools were aware of the extent to which and just how fast the cutting edge is advancing.

An executive engaged in the program says that these systems are intended to complement larger models, instead of substituting them. Tools such as ChatGPT and another major AI system, he comments, frequently have difficulty with native tongues and cultural aspects – communicating in stilted Khmer, for instance, or suggesting meat-containing meals to Malaysian consumers.

Building regional-language LLMs enables local governments to code in cultural sensitivity – and at least be “smart consumers” of a sophisticated technology built elsewhere.

He adds, “I’m very careful with the concept sovereign. I think what we’re aiming to convey is we want to be better represented and we wish to grasp the capabilities” of AI technologies.

Cross-Border Collaboration

For nations seeking to establish a position in an intensifying global market, there’s another possibility: collaborate. Analysts affiliated with a respected university put forward a government-backed AI initiative distributed among a group of developing nations.

They call the proposal “a collaborative AI effort”, in reference to the European effective initiative to create a alternative to a major aerospace firm in the mid-20th century. This idea would involve the establishment of a public AI company that would combine the capabilities of various nations’ AI initiatives – including the UK, Spain, the Canadian government, Germany, the nation of Japan, Singapore, South Korea, France, the Swiss Confederation and the Kingdom of Sweden – to establish a competitive rival to the American and Asian major players.

The lead author of a report outlining the proposal states that the proposal has drawn the consideration of AI leaders of at least three countries so far, in addition to a number of national AI firms. While it is presently centered on “developing countries”, emerging economies – the nation of Mongolia and Rwanda among them – have likewise indicated willingness.

He comments, “Nowadays, I think it’s an accepted truth there’s less trust in the commitments of this current White House. People are asking for example, is it safe to rely on any of this tech? What if they opt to