By Karun Tadepalli, CEO & co-founder, byteXL TechEd Private Limited
The AI revolution is here, and it’s reshaping the world faster than we can comprehend. It’s supposedly a race and there are two superpowers – the US and China – vying to get somewhere. Indian public discourse is one that’s been marked either by panic or a practiced ‘we’ll get there’ attitude.
Realistically though, let me place the options here. Should India follow the U.S. model? Or should it take a different path, one that leverages its vast engineering talent and aligns with its pressing social needs?
In the U.S., AI innovation is dominated by tech giants like OpenAI, Microsoft, Google, Nvidia, and Meta. These companies have built powerful AI systems, but they are tightly controlled, proprietary, and expensive. Small businesses, startups, and even entire countries are left scrambling to keep up, unable to afford access to cutting-edge AI tools especially the new-age hardware needed (NVIDIA chips). While China has leapfrogged into the microprocessor chips arena with Huawei’s ‘7 nano’ chips, the Indian efforts, on the other hand, continue to grapple with regulatory hurdles.
For India, it appears as of now, we’ve missed the bus as far as copying the Silicon Valley model is concerned. In March 2024, the Government of India’s IndiaAI Mission set aside a corpus of ₹10,372 crores to build nearly 10,000 graphic computing units (GPU). While this was welcome, China’s Deepseek, built on a budget of mere 50 crore rupees (though debatable as we don’t have concrete evidence on R&D and infra costs), but utilising all things open source has to offer, has marked a paradigm shift in the way the world approached AI.
With over 1.5 million engineering graduates every year, India’s greatest asset is its people. Proprietary AI systems would leave most of this talent pool sidelined, unable to contribute meaningfully to the AI revolution. Each year, we seem to be letting several students fall through the cracks. We now know that 90 percent of our engineering students are unemployable, and this number will only worsen as automation becomes more and more pervasive. Yet, there’s hardly any initiative to build a foundational model in India.
On 30 January, a week after Deepseek’s R1 sent tremors through Silicon Valley – even decorating 465 billion dollars from NVIDIA’s market cap – Abhishek Singh, CEO of IndiaAI invited proposals to build foundational models. As welcome as the invitation is, are our education institutions even close to meeting the skill demands building such a model requires? At this point, the answer is a simple no. Our IITs and other premier institutes are barely there; let alone smaller colleges.
Instead, what if India can look to models that prioritize collaboration and inclusivity over profit maximization?
China’s approach to AI offers a fascinating contrast to the U.S. model. While the Chinese government has invested heavily in AI, it has also encouraged open innovation. For example, Baidu, one of China’s tech giants, open-sourced its deep learning platform, PaddlePaddle, to compete with TensorFlow and PyTorch. This move wasn’t just about altruism – it was a strategic effort to build a robust AI ecosystem that could rival the West.
The Chinese government also launched the “New Generation Artificial Intelligence Development Plan,” which emphasizes collaboration between academia, industry, and the state. By fostering an open ecosystem, China has been able to rapidly scale its AI capabilities, leveraging its massive population and engineering talent. Incredibly, the Chinese competition has only encouraged Silicon Valley to get more creative; they take contests and races very seriously.
However, India can learn from these wildly different models. Imagine if Indian tech companies and academic institutions collaborated on open-source AI projects, with government support. This would create a fertile ground for innovation, allowing India’s engineering graduates to contribute to global AI advancements.
If China’s approach is about strategic competition, the Nordic model is about societal well-being. Countries like Finland and Sweden have embraced open-source technologies to promote transparency, inclusivity, and public trust. In Finland, where prisons are more correctional facilities than mere punishment centers, inmates are playing a crucial role in AI annotation tasks, such as labeling and classifying data, as part of their rehabilitation.
Similarly, Finland’s “Elements of AI” initiative is a free online course designed to educate citizens about artificial intelligence. By making AI knowledge accessible to all, Finland is ensuring that its population is prepared for the AI-driven future. Similarly, Sweden has invested in open-source AI projects that focus on sustainability and social good, such as using AI to optimize energy consumption in cities. Sweden and Finland have adopted a model where, as a policy, they ensure no citizens are left behind, not even the supposed “undesirables” spending time in jail for crimes.
A Case for India
India’s demographic profile presents both challenges and opportunities. With a population of over 1.4 billion people, India is home to a staggering diversity of languages, cultures, and socio-economic conditions. This diversity is both a strength and a challenge. On one hand, it creates a vast market for localized solutions; on the other hand, it complicates the task of delivering scalable, inclusive technologies.
India’s linguistic diversity is one of its most pressing challenges. With 22 officially recognized languages and hundreds of dialects, communication barriers are a significant hurdle in education, healthcare, and governance. AI has the potential to bridge these gaps, but only if it is developed with local languages and contexts in mind.
Open-source AI can play a crucial role here. By making AI tools and datasets freely available, India can empower local developers to create solutions tailored to regional needs. For example, an open-source AI platform for natural language processing (NLP) could enable the development of educational apps in regional languages, making quality education accessible to millions of students. Similarly, AI-driven translation tools could improve access to government services for non-English speakers.
Why Open Source is India’s Best Bet
The sheer number of India’s engineering graduates is its secret weapon in the AI race. But to fully harness their potential, the country needs an ecosystem that supports open innovation. The Indian engineering ecosystem – government, start-ups, investors, educational institutions – should take a page from China’s playbook and invest in open-source AI initiatives. This could include funding research, organizing hackathons, and creating incentives for companies to contribute to open-source projects. Overhauling the engineering education system – think resetting colleges at an administrative level – would be the second thing to do. For instance, while the IITs get the required infrastructure and boosts from the government, can we also look at providing similar help to the other 9,000-odd engineering colleges in India?
Indian tech companies and universities should work together to integrate open-source AI into curricula and research programs. For instance, students could contribute to open-source projects as part of their coursework, gaining hands-on experience while advancing the field. India’s startups, known for their ingenuity and resourcefulness, can also play a pivotal role. By encouraging startups to build on open-source AI platforms, India can create a vibrant innovation ecosystem. For one, can our EdTech companies play a major role with some special R&D budgets for research, instead of running behind revenues?
Open source thrives on collaboration, and India should foster a vibrant AI community by organizing meetups, conferences, and online forums. This will create a space for developers, researchers, and enthusiasts to share ideas and work together on projects.
The real power of open-source AI lies in its ability to democratize access to technology. Unlike proprietary systems, which are controlled by a few corporations, open-source AI is transparent, accountable, and accessible to all. This is particularly important in a country like India, where trust in technology is crucial for widespread adoption.
Moreover, open-source AI can help address India’s most pressing challenges. For example, an open-source AI platform for crop prediction could help farmers optimize their yields, while an AI-driven educational tool could improve learning outcomes for underprivileged students.
India stands at a crossroads. It can either follow the U.S. model of wealth maximization, which risks leaving its vast talent pool untapped, or it can chart its path by embracing open-source AI. The latter is not just a strategic imperative – it’s a moral one.
By learning from the Chinese and Nordic models, India can build an AI ecosystem that is inclusive, collaborative, and focused on the public good. This is the way to leverage the vast number of engineering students India produces each year. It’s a stretch but imagine for a moment, the scale of our indigenous AI ecosystem, if Indian engineering students all over India are made to participate in data annotation tasks. Imagine for a moment the future, if we adopted ‘no student left behind’ as a centralized policy.
The time to act though, is now.