AI expert urges every country to set up own artificial intelligence infrastructure as he anticipates 'huge economic shift'
French startup CEO Arthur Mensch thinks every country should set up its own artificial intelligence infrastructure because of a huge upcoming economic shift.
"It will have an impact on GDP of every country in the double digits in the coming years," said Mensch.
Gross Domestic Product is essentially the total value of everything a country produces. It's a common measure of a country's economy.
The CEO of AI company Mistral warned that if countries don’t get moving on their own AI systems in time, they’ll risk losing money to others who do.
Advert
"100 years ago, if you weren't building electricity factories, you were preparing yourself to buy it from your neighbours, which, at the end of the day, isn't great because it creates some dependencies," he added.
Mensch also pointed out that AI has the power to pass on a country's values and culture and, as such, requires more involvement than electricity.
Mensch, who cofounded Mistral in 2023 with former DeepMind and Meta researchers, explained his theory on a podcast alongside Nvidia CEO Jensen Huang.
Both agreed that AI will soon be used everywhere - from farming and healthcare to national defence - and that’s exactly why each country should create its own strategy and tools to stay in control.
Mistral is known for its work on large language models.
The company recently launched its own AI chatbot, 'Le Chat,' and is now going head-to-head with giants like OpenAI, Anthropic and China’s DeepSeek.
Mistral claims its models are faster than most, and investors seem to believe in the hype.
It was valued at $6.2 billion in June and has backing from big names like General Catalyst, Lightspeed and Andreessen Horowitz.
Mensch says he plans to take the company public instead of selling it off. He openly argued on the podcast that language models should be kept open-source.
On the podcast, he said that progress in AI slowed down when companies like OpenAI moved to closed-source models, which others argue keeps their code private and secure.
"Between 2010 and 2020, there was an acceleration of progress because every lab was building on top of each other and that's something that kind of disappeared with the first large language models from Open AI in particular," Mensch said. "Spinning back that open flywheel of 'I contribute something and then another lab is contributing something else and then we iterate from that' is the reason why we created Mistral."