As the world becomes increasingly digitized, the development of artificial intelligence (AI) technology has become a global race. In the last 2 years, it almost felt that the center of gravity for tech would shift from the United States to India and Asia, which have thriving startup ecosystems and are way advanced in terms of Fintech tech (like UPI).
China was leading the AI race for a long time – to a point that Eric Schmidt warned the US govt on this.
Schmidt wants the government to implement his sweeping blueprint to fight what he considers an existential threat to democracy posed by China’s AI plans, an effort that could also bolster his own commercial AI interests.
Without some type of unified, broad adoption of an AI foundation for the entire department, DOD will soon reach a tipping point after which it will be unable to catch up to its competitors,” Schmidt said in 2018 while testifying before the House Armed Services Committee. Schmidt spoke in a personal capacity, but was chair of the Pentagon’s Defense Innovation Board and on Alphabet’s board at the time.
He says the U.S.’s national security and economic leadership are dependent upon spending billions to procure smarter software, bolster AI research, and build the country’s computer science talent pool.
From a 2021 article / Via
But then, OpenAI came and democratized the entire AI landscape!
You own LLMs. You own the (AI) world.
LLMs are critical components in natural language processing (NLP) and form the backbone of AI-powered products like virtual assistants, chatbots, and translation services. These models require vast amounts of data, computing power, expertise (AND PATIENCE) to develop, and the current owners of LLMs are primarily US-based companies like Google, Microsoft, and OpenAI.
This dominance means that the rest of the world will be primarily consumers of these technologies, rather than creators.
The absence of access to LLMs and NLP technology could mean that opportunities to create globally dominant tech giants like Google or Microsoft may be lost (?) for India and Asia.
What’s the way out?
Of course, you can AI technologies that do not rely on LLMs and NLP technology but those may not create mass scale change (at the rapid speed of LLMs adoption).
Your thoughts?
[Written in partnership with AI]
