To succeed at AI, we need a whole-of-nation approach involving deep-tech startups, enabling industrial policy and pre-commercial publicly-funded research.
When the Biden Administration released its AI Diffusion Executive Order a few weeks back restricting GPUs to countries, it became clear that having strategic autonomy in AI was of paramount importance to India.
Just being the use-case capital for AI wasnโt the right way to go.
India doesnโt wish to be a trade colony of China or the technology colony of the US.
What makes AI different is that it needs a whole-of-nation approach. To win at AI we need deep-tech startups, enabling industrial policy and pre-commercial publicly-funded research. It is only when all three come together that magic can happen.
Our resistance to the whole-of-nation approach is understandable. After all, our IT Services and SaaS industry came up without the whole-of-nation approach. So, many people thought that the same playbook would apply to AI.
China has proved with DeepSeekโs R1 and Moonshot AI [another Chinese companyโs] Kimi k1.5 that a whole-of-nation approach can have big payoffs. In India, this approach has worked for cryogenic engines, 4G/5G telecom equipment and India Stack. We do remarkable things when we set our mind to it!
Yes, we have lost some time due to the use-case captial camp. But all is not lost. The field is still young and many areas like neurosymbolic AI are very much open.
The Biden AI Diffusion order, and Chinese success has given new vigour to the whole-of-nation camp within government, private sector and civil society. The debate is now over: You will see some good developments become visible in the coming months #AI #StrategicAutonomy