When India hosted the AI Summit, it was the first time that discussions about this new technology were held in front of the people who it would actually affect. By democratising access, we could start to have real discussions about how to get this technology out into the world.

This is a link-enhanced version of an article that first appeared in the Mint. You can read the original here. For the complete archive of all my articles please visit my website.

In November 2023, a few governments and technologists gathered at Bletchley Park to discuss artificial intelligence (AI), seeking to come to terms with the technology they were developing. The mood was sombre and fear was the dominant register. This was the first of a series of AI Summits, the most recent of which was held in New Delhi last week.

Unlike Bletchley Park, Bharat Mandapam was not only much larger and more crowded, the mood was also markedly more upbeat. With over 500,000 visitors from 118 countries and over 3,250 speakers, the AI Impact Summit held in New Delhi was far and away the largest AI summit to date. But what distinguished this conference was not its size or spectacle, but a growing recognition that the real challenge is not building intelligence, but spreading it.

Any event of this scale is bound to have its fair share of mishaps and the AI Impact Summit was no exception. While many on social media and in the domestic press spent last week fixating on these fumbles—from a misbegotten robot dog to traffic jams and long walks ordinary citizens had to endure to get home—anyone who has been inside the halls of Bharat Mandapam will testify that the corridors were buzzing.

In terms of tangible outcomes, 80 countries and international organizations adopted the ‘New Delhi Declaration on AI Impact,’ a document that underscored the urgent need to realize AI’s potential to drive economic transformation. The Declaration anchored national commitments across three broad ambitions: widening access, embedding accountability and using AI to drive inclusive growth—through reskilling, research and sustainable infrastructure.

There were also other specific deliverables, such as the Charter for the Democratic Diffusion of AI, Global AI Impact Commons, International Network of AI for Science Institutions and the AI for Social Empowerment Platform. Various ministries and regulators used the Summit to announce new policy initiatives, including the health ministry, which launched SAHI, India’s national framework for AI in healthcare. Many of these documents will serve as signposts for further action after the summit. I hope to engage in some of this work myself through the Expert Engagement Group on ‘A New Deal for Data’ that I chair.

The Summit also served as an occasion to announce India’s entry into the LLM race. Three Indian foundational models were launched last week—Gnani’s text-to-speech model Vachana, BharatGen’s Param2, a 17-billion-parameter multilingual model, and Sarvam’s 30- and 105-billion-parameter models. The latter were especially impressive for their performance on various benchmarks, achieving state-of-the-art results on several criteria relevant to India. Above all, these launches signalled that India intends not merely to adopt global models, but to compete successfully at the foundational layer of AI itself.

For me, the real value of the Summit came from all the many conversations we had. With the who’s who of AI—heads of big AI labs, semiconductor companies and data centre providers, as well as 20 heads of state and 60 ministers—in attendance, the quality of discussions on the big stage as well as along the sidelines of scheduled events was superlative. During the week, over 500 sessions were held on subjects as wide and varied as they were deep and substantive. While the keynotes on the main stage served as an opportunity to make announcements and investment commitments, it was the panel discussions that really offered an opportunity for debate, discussion and healthy disagreement. 

Of the tiny fraction of sessions I was personally a part of, we discussed issues as diverse as the governance of data-sharing networks for AI, how AI could benefit countries and the planet, and the importance of keeping the internet open to truly democratize AI access.

But the highlight of the week was a conversation between Nandan Nilekani and Dario Amodei that I moderated. In those 20 minutes, these two titans of technology managed to perfectly sum up the zeitgeist of the Summit and complexity of the problem before us. Dario Amodei started by conceding that, even though AI models are fast approaching the “end of the exponential,” producing what he calls a “country of geniuses in a data centre” very soon, its real societal impact will take a lot longer. Even if we were to freeze AI development at today’s level of capability, adoption would inevitably be slow, friction-filled and unpredictable.

This lined up perfectly with Nandan Nilekani’s own thesis that diffusion is hard and that it will take countries like India, with its scale of population, diversity of challenges and experience with technology diffusion, to show the world how the pace of AI adoption can be accelerated. Because technology diffusion is both an art and a science, we will need to formulate multiple diffusion pathways if we are to have any hope of ensuring that AI actually delivers on its full potential.

The AI Impact Summit was many things—among them, a diplomatic milestone, an investment forum and a demonstration of India’s institutional confidence. But its true success will be measured not in declarations made, commitments announced or foundational models launched, but in whether it will force the world to confront the hard task that lies ahead of us all: actually getting this miraculous technology into the hands of those who need it most.

When India hosted the AI Summit, it was the first time that discussions about this new technology were held in front of the people who it would actually affect. By democratising access, we could start to have real discussions about how to get this technology out into the world.

This is a link-enhanced version of an article that first appeared in the Mint. You can read the original here. For the complete archive of all my articles please visit my website.

In November 2023, a few governments and technologists gathered at Bletchley Park to discuss artificial intelligence (AI), seeking to come to terms with the technology they were developing. The mood was sombre and fear was the dominant register. This was the first of a series of AI Summits, the most recent of which was held in New Delhi last week.

Unlike Bletchley Park, Bharat Mandapam was not only much larger and more crowded, the mood was also markedly more upbeat. With over 500,000 visitors from 118 countries and over 3,250 speakers, the AI Impact Summit held in New Delhi was far and away the largest AI summit to date. But what distinguished this conference was not its size or spectacle, but a growing recognition that the real challenge is not building intelligence, but spreading it.

Any event of this scale is bound to have its fair share of mishaps and the AI Impact Summit was no exception. While many on social media and in the domestic press spent last week fixating on these fumbles—from a misbegotten robot dog to traffic jams and long walks ordinary citizens had to endure to get home—anyone who has been inside the halls of Bharat Mandapam will testify that the corridors were buzzing.

In terms of tangible outcomes, 80 countries and international organizations adopted the ‘New Delhi Declaration on AI Impact,’ a document that underscored the urgent need to realize AI’s potential to drive economic transformation. The Declaration anchored national commitments across three broad ambitions: widening access, embedding accountability and using AI to drive inclusive growth—through reskilling, research and sustainable infrastructure.

There were also other specific deliverables, such as the Charter for the Democratic Diffusion of AI, Global AI Impact Commons, International Network of AI for Science Institutions and the AI for Social Empowerment Platform. Various ministries and regulators used the Summit to announce new policy initiatives, including the health ministry, which launched SAHI, India’s national framework for AI in healthcare. Many of these documents will serve as signposts for further action after the summit. I hope to engage in some of this work myself through the Expert Engagement Group on ‘A New Deal for Data’ that I chair.

The Summit also served as an occasion to announce India’s entry into the LLM race. Three Indian foundational models were launched last week—Gnani’s text-to-speech model Vachana, BharatGen’s Param2, a 17-billion-parameter multilingual model, and Sarvam’s 30- and 105-billion-parameter models. The latter were especially impressive for their performance on various benchmarks, achieving state-of-the-art results on several criteria relevant to India. Above all, these launches signalled that India intends not merely to adopt global models, but to compete successfully at the foundational layer of AI itself.

For me, the real value of the Summit came from all the many conversations we had. With the who’s who of AI—heads of big AI labs, semiconductor companies and data centre providers, as well as 20 heads of state and 60 ministers—in attendance, the quality of discussions on the big stage as well as along the sidelines of scheduled events was superlative. During the week, over 500 sessions were held on subjects as wide and varied as they were deep and substantive. While the keynotes on the main stage served as an opportunity to make announcements and investment commitments, it was the panel discussions that really offered an opportunity for debate, discussion and healthy disagreement. 

Of the tiny fraction of sessions I was personally a part of, we discussed issues as diverse as the governance of data-sharing networks for AI, how AI could benefit countries and the planet, and the importance of keeping the internet open to truly democratize AI access.

But the highlight of the week was a conversation between Nandan Nilekani and Dario Amodei that I moderated. In those 20 minutes, these two titans of technology managed to perfectly sum up the zeitgeist of the Summit and complexity of the problem before us. Dario Amodei started by conceding that, even though AI models are fast approaching the “end of the exponential,” producing what he calls a “country of geniuses in a data centre” very soon, its real societal impact will take a lot longer. Even if we were to freeze AI development at today’s level of capability, adoption would inevitably be slow, friction-filled and unpredictable.

This lined up perfectly with Nandan Nilekani’s own thesis that diffusion is hard and that it will take countries like India, with its scale of population, diversity of challenges and experience with technology diffusion, to show the world how the pace of AI adoption can be accelerated. Because technology diffusion is both an art and a science, we will need to formulate multiple diffusion pathways if we are to have any hope of ensuring that AI actually delivers on its full potential.

The AI Impact Summit was many things—among them, a diplomatic milestone, an investment forum and a demonstration of India’s institutional confidence. But its true success will be measured not in declarations made, commitments announced or foundational models launched, but in whether it will force the world to confront the hard task that lies ahead of us all: actually getting this miraculous technology into the hands of those who need it most.