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On Making AI Research More Lucrative In India

The research work coming out of Indian institutions is impressive. We have a great talent for tackling real-world problems across various domains.

“AI is uniquely positioned as a field where academia and industry are pushing the boundaries of the field together”

Vineeth N Balasubramanian

Over the last two decades, the world has seen a radical transformation in the field of AI research, transforming from a small, relatively niche domain into a sprawling web of groundbreaking innovations. Mapping and measuring this research explosion – and analysing the scenario in India is of prime importance. 

India was recently ranked sixth in Global Vibrancy Ranking 2020 and had the highest relative AI skills penetration rate, as per AI Index Report 2021 by Stanford University.  


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Image: Stanford University

“Being at the forefront of research in AI technologies (both foundational and applied) and enabling a large talent pool engaged in cutting-edge AI research makes India a destination for high-tech investments in the longer run, even though it may not necessarily seem lucrative immediately. This viewpoint is important to consider,” said Vineeth N Balasubramanian, Head, Department of AI, IIT Hyderabad.

India needs to generate over 100 million jobs by 2030, and this is considered one of India’s biggest challenges. The future of work depends on how well humans and AI work together to form augmented hybrid teams. An AI’s strengths include speed, computing, precision, and so on. On the other hand, humans have abilities such as cognition, empathy, and judgement. This position will bring together the strengths of both AI and humans to improve business outcomes. 

Academia and Industry – a perfect combo

Until now, it was considered that the focus of academia remains on basic research, training and education, whereas industry places a greater emphasis on applied research and development only in commercially viable application sectors. In recent years, however, this distinction has eroded in the field of AI. Recently, IIT-Madras set up an industrial consortium to disseminate the output of research work in order to commercialise the idea; IIT-Delhi has signed an agreement with Mirrorsize – a deep tech startup to develop an AI-powered app to provide real-time body measurements, and multiple other initiatives are taking off.

Talking about the near term perspective, Vineeth is of the opinion that AI is uniquely positioned as a field where academia and industry are pushing the boundaries of the field together — more than other fields where research in academia can take years (or even longer) to translate to the industry. “However, to leverage and monetise these developments, we need a more widespread presence of indigenous industries that translate cutting-edge AI research to products and services — these can include automobiles, security, healthcare, agriculture, retail, pharma, oil, power and energy.” 

The access to technologies, including inexpensive cloud computing, pre-trained models for languages, open-source libraries, etc., has opened up a plethora of opportunities for faculty, students and postdocs to start their own startups or find ways to commercialise their intellectual property. 

“The research work coming out of Indian institutions is impressive. We have a great talent for tackling real-world problems across various domains. At the grassroots undergraduate level, something I think could help is further incentivising (course credits, tuition waivers) research and teaching assistantships. This not only gets students engaged earlier on (promoting critical thinking) but fosters diverse perspectives in research projects. I also like the concept of student-led courses, updating of curriculum, to keep up with fast-growing areas of research in this field,” said Praneet Dutta, Research Engineer, Google DeepMind. 

He further added, “Organisations are increasingly seeing the value of AI systems. Having a central forum (similar to NeurIPS, ICML, ICLR, etc.) to discuss specific challenges across different verticals would go a long way in connecting the industry and academic communities.”

Need for Robust Funding and Support 

NITI Aayog has already come up with the National Strategy on Artificial Intelligence to focus on economic growth and ways to use AI to enhance social inclusion and promote research into crucial AI-related concerns, including ethics, bias, and privacy. Additionally, the fund of Rupees 7000 crore to be used till 2024-25 is the right step put forward. However, the sum assured seems minuscule when compared to the likes of China and the US. 

Looking at the startup ecosystem in India, while many AI startups have emerged in recent years, translating cutting-edge AI research to products requires more large-scale investments, especially on compute and talent. “On one hand, we need large corporations to invest in translating such research to products and services in different sectors; on the other hand, we may also need to invest in making large-scale high-end compute accessible to the relevant industries, to enable the medium and small-scale sectors to leverage such AI research for their offerings,” said Vineeth.

Wrapping up

India is uniquely positioned to encash its demographic dividend and demand by enhancing the research culture in India. A large part of students in India goes on to join big tech firms, including Microsoft, Google, IBM, just after completing their graduation, and many teaching staff quit their academic positions to work full-time, majorly due to good pay packages and a better lifestyle. However, we need to introspect and devise ways to make research culture in India more lucrative. 

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kumar Gandharv
Kumar Gandharv, PGD in English Journalism (IIMC, Delhi), is setting out on a journey as a tech Journalist at AIM. A keen observer of National and IR-related news.

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