Mohandas Pai Explains Why India Doesn’t Have a Mistral AI Yet
The fact that creating an LLM from scratch requires tons of money is well established now. It is one of the primary reasons why India only has a couple of them, which are also much smaller compared to those built in the US, China, or Europe – the AI regulation capital of the world. Even in the whole of Europe, there is only Mistral from France which is building LLMs to compete with the likes of OpenAI and Anthropic. While speaking with AIM, several industry leaders agreed that there was no point in trying to compete in building the largest LLM as it is necessary to focus on the vertical applications of AI, not the horizontal. The reason is simple – lack of capital. “Who will give $200 million to a startup in India to build an LLM?” said Mohandas Pai, head of Aarin Capital and former CFO of Infosys, when asked about the lack of innovation from Indian IT. “Why is nothing like Mistral coming from India,” he asked rhetorically. “There is nobody,” he answered. “Creating an LLM or a big AI model requires large capital, time, a huge computing facility, and a market. All of which India does not have,” said Pai. Though we have startups like Sarvam, TWO, and Krutrim building products, the impact that they have created when compared to something like ChatGPT is miniscule. To put things into perspective, Mistral recently raised $640 million in a Series B round, raising its valuation to $6 billion. This was after it raised the largest seed round of $112 million last year. Compare this to the $50 million round that Krutrim raised, which is the highest-ever funding for an Indian AI startup. Another big reason is the availability of Indic data, which is very small when compared to English for US and European AI startups. This is what most of the Indian startups are looking to solve. “Indian software companies are service companies, not product companies.” Pai also believes that even if they have enough capital, expecting Indian IT companies to build an LLM is not the right approach for India. Instead of services companies, Indian startups and product companies should invest more into R&D, which he agrees is also difficult because investors do not put in so much money. Most Indian AI startups are powered by jugaad, not VC money, which makes it harder for them to put those funds into R&D. Why are Product Companies Not Building Great LLMs? AIM had previously explored why Perplexity AI wasn’t built in India and the reason was the same. Nobody is ready to invest in research and development startups, even if that would just cost around $10 million to get started. Pai advocates for a large government fund to foster innovation in India. This is something similar to what France did with its France Innovation Fund, which has a total size of $36 billion, and is actively supporting Mistral through it. Arthur Mensch, the CEO of Mistral, also works closely with the French government for regulations and policies around AI. While speaking at Cypher 2024, Pai called on the Indian government to significantly increase its investment in AI. He pointed out that although the Government of India spends INR 90 lakh crore annually, only INR 3,000 to INR 4,000 crore is allocated for innovation, a sum he referred to as “peanuts”. “The Government of India should invest INR 50,000 crore in AI. They need to support AI startups by providing grants and enabling them to invest in and develop solutions like ChatGPT,” he said. Furthermore, he said that India is the third largest digital power in the world. “Out of 6 million software professionals in the US, 1 million are Indians. Among the 10 million working for American companies globally, 4 million are Indians,” said Pai. Things are Slowly Changing Pai is miffed at the repeated conversations about why there is no Google, Microsoft, or Apple from India. “There is only one Apple in the world, and that’s in the US. Even Japan and Europe don’t have it even when they have the capital,” Pai shrugged. Meanwhile, CP Gurnani, the co-founder of Tech Mahindra, told AIM that India should move beyond being the “use case capital of the world”, and he believes that something like NVIDIA can be born out of the country. “I am convinced that the next NVIDIA will be born in India as the semiconductor industry develops,” said Gurnani, adding that within five to seven years, India won’t be relying on someone else. Though, on the optimistic side, Pai said that even though people were not investing in AI startups till now, things are changing. And the biggest reason for that is the government’s push for computing facilities through its IndiaAI Mission, which is about onboarding GPUs and building Indian AI clouds. Moreover, most of the companies and startups in India are focused on building vertical and specialised AI models such as using smaller language models and implementing them for healthcare, legal, insurance, and similar sectors. “They have got their models, they are implementing them and they would be the major players in this market,” added Pai. This approach has been working well for Indian AI companies, inspired by Nandan Nilekani’s idea of building ‘Adbhut India’ or in other terms, “the AI use case capital of the world”. The only problem with that is that we might have all the Krutrims of the world, but India will not have a Mistral AI to call its own.
Nobody is ready to invest in research and development startups, even if that would just cost around $10 million to get started.
The reason is simple – lack of capital. “Who will give $200 million to a startup in India to build an LLM?” said Mohandas Pai.
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["AI", "ChatGPT", "OpenAI", "Anthropic", "Aim", "R", "Go", "Git", "API", "GPT"]
Mohit writes about AI in simple, explainable, and often funny words. He's especially passionate about chatting with those building AI for Bharat, with the occasional detour into AGI.