India’s success in the global artificial intelligence (AI) race depends on open data, open compute, and open models, according to industry representatives and experts. While Indian startups are already developing AI solutions in various sectors such as agriculture, healthcare, and education, they are still largely dependent on models developed in the West. Debjani Ghosh, president of Indian IT industry apex body NASSCOM, emphasizes the need for high-value open datasets and calls on the government to drive the development of large and open-source foundational models, which would require significant investment due to the costs involved and the compute power required.
The Indian government recognizes the importance of AI and has taken steps to support AI companies. It plans to establish supercomputing and quantum computing hubs through public-private partnerships, allocating up to Rs 10,000 crore (approximately $1.3 billion) for the initiative. Additionally, a 30,000 GPU cluster will be created to provide high-performance computing to startups, micro, small, and medium enterprises (MSMEs).
However, funding for Indian AI startups remains a challenge. Ghosh highlights the disparity in funding between Indian and US startups, with Indian startups typically receiving $5-10 million compared to $30-50 million in the US. To address this, she suggests the need for deep and patient capital and calls on the government to incentivize investment in AI startups, particularly for small and medium companies.
While concerns have been raised about the risks of AI, such as deepfakes, industry leaders believe that regulation should focus on enabling innovation rather than imposing separate regulations for AI. Existing frameworks can adequately address the potential harms of AI technology.
Ultimately, the key to India’s AI success lies in openness, with the government investing in the creation of enabling conditions such as open data, open compute, and open models. By supporting AI startups, providing funding, and prioritizing sectors for AI deployment, India can boost productivity, enhance global competitiveness, and drive economic growth.
FAQ Section:
Q: What is the key to India’s success in the global AI race?
A: According to industry representatives and experts, India’s success in the global AI race depends on open data, open compute, and open models.
Q: What sectors are Indian startups developing AI solutions in?
A: Indian startups are developing AI solutions in various sectors such as agriculture, healthcare, and education.
Q: What is the role of the Indian government in supporting AI companies?
A: The Indian government recognizes the importance of AI and has taken steps to support AI companies. It plans to establish supercomputing and quantum computing hubs, as well as allocate significant funding for the initiative.
Q: What is the funding challenge faced by Indian AI startups?
A: Indian AI startups typically face a disparity in funding compared to US startups. Indian startups typically receive $5-10 million, while US startups receive $30-50 million.
Q: What is the suggested solution to address the funding challenge for Indian AI startups?
A: The president of NASSCOM suggests the need for deep and patient capital and calls on the government to incentivize investment in AI startups, particularly for small and medium companies.
Q: What is the suggested approach to AI regulation?
A: While concerns have been raised about the risks of AI technology, industry leaders believe that regulation should focus on enabling innovation rather than imposing separate regulations for AI. Existing frameworks can adequately address the potential harms of AI technology.
Q: How can India boost productivity and economic growth through AI?
A: By supporting AI startups, providing funding, and prioritizing sectors for AI deployment, India can boost productivity, enhance global competitiveness, and drive economic growth.
Definitions:
1. AI – Artificial Intelligence, the simulation of human intelligence in machines that are programmed to think and learn like humans.
2. Open data – Data that is freely available for use, reuse, and redistribution by anyone.
3. Open compute – The use of open-source hardware designs and interfaces to enable collaborative development and innovation.
4. Open models – Machine learning models that are publicly available for use and modification by others.
Suggested Related Links:
NASSCOM – Official website of NASSCOM, the apex body of the Indian IT industry.
India.gov.in – Official website of the Government of India.
NITI Aayog – Official website of NITI Aayog, a policy think tank of the Government of India.
Analytics India Magazine – A platform covering developments in artificial intelligence, data science, and analytics in India.
The source of the article is from the blog shakirabrasil.info