Source – This post on Investing in Artificial Intelligence has been created based on the article “India’s AI ambitions will get a much-needed fillip” and “Investing in AI” published in Live Mint and Business Standard” on 11 March 2024.
UPSC Syllabus – GS Paper 3 – Awareness in IT, Space, Computers, and Robotics
News – The government has allocated Rs10,371.92 crore package for the National AI (artificial intelligence) Mission to promote artificial intelligence in India.
What is Artificial Intelligence?
It is defined as the ability of machines and systems to acquire and apply knowledge and to carry out intelligent behaviour.
It includes technologies like machine learning, Deep Learning, Big Data, Neural Networks, Computer vision, Large Language Models etc.
What is National AI mission?
Objective– The primary objectives of the AI Mission include establishing robust computing powers for AI within India.
What are the steps taken by the government to promote AI?
1) The government has announced 10,371.92 crore package for the National AI (artificial intelligence) Mission.
2) Under the allocated fund, there is viability-gap funding of around 4,500 crores for setting up10,000 high-end graphics processing units (GPUs).
3) There will be establishment of an “AI marketplace”, designed to offer AI as a service and pre-trained model.
4) It will develop foundational models with capacities exceeding 100 billion parameters. It will be trained on datasets covering major Indian languages for sectors such as healthcare, agriculture, and governance.
What are the challenges in realizing full potential of AI in India?
1) Under-investment as compared to other countries– According to Stanford’s AI Index 2023, the US has invested nearly $250 billion in 4,643 companies, China has invested $95 billion invested in 1,337 artificial intelligence (AI) startups. Whereas India has invested only $8 billion in 296 startups since 2013.
2) Lack of sophistication in microchip manufacturing – AI needs chips below 5nm whereas the recently inaugurated chip manufacturing plant will manufacture chips in the size of 28-40 nanometres (nm).
3) Graphics processing units (GPUs)– India lacks Graphics Processing Units (GPUs)that are crucial to train AI models and build indigenous large language models (LLMs) and LMMs. The recently allocated money would only be sufficient to fund only 1,000-1,500 high-end GPUs.
4) Inadequate local large multimodal models (LMMs)– While India has only a handful of local LLMs, China already has at least 130 LLMs, accounting for 40% of the global total.
5) Lack of digital data for Indian language– Out of 22 official Indian languages, most of them do not have digital data. There is a lack of quality non-personal data.
What should be the way forward?
1) There should be more sophistication in microchip manufacturing to meet the demands of AI industry.
2) Policy support– The AI ecosystem needs sensible, clear regulation and legislation, and enabling policy such as-
a) A sensible Customs and tax policy for importing relevant hardware.
b) A push to encourage local manufacture of high-end equipment including semiconductors.
C) Since AI depends a lot on data, there is an urgent need to finetune the processing and storage of both personal and non-personal data.
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