Aim:
- Establish an ecosystem for AI innovation through public-private partnerships.
- Deploying over 10,000 Graphics processing units (GPUs) for advanced AI computing infrastructure.
- Driving responsible, inclusive growth of India's AI ecosystem through democratization, data quality improvement, and indigenous AI capabilities development.
Ministry: An umbrella programme by the Ministry of Electronics and Information Technology (MeitY).
Funding: To be made available over 5 years through a public-private partnership model.
Implementing agency: 'IndiaAI' Independent Business Division under Digital India Corporation.

Pillars of IndiaAI and Related Schemes
AI in Governance	AI Compute & Systems	Data for AI
BHASHINI - [BHASHa INterface for India] an AI- based language translation tool for Indian languages. Digital India India Stack and AI	AIRAWAT: India’s AI supercomputer installed at C-DAC, Pune. National Supercomputing Mission MeitY Quantum Computing Applications Lab	Data Management Office: Helps in standardisation of data management. India Datasets Program and India Data Platform: Provides access to non-personal datasets for start-ups and researchers.
AI, intellectual property (IP) & Innovation	Skilling in AI	AI Ethics & Governance
Centre of Excellence for Artificial Intelligence MeitY Start-up Hub Proposed National Centre on AI (NCAI)	Future Skills Prime: Joint initiative by Nasscom & MeitY for AI certification programs. Responsible AI for Youth: Program for government making school students AI ready.	RAISE: Responsible AI for Social Empowerment

It refers to computer systems capable of performing complex tasks that historically only a human could do, such as reasoning, making decisions, or solving problems.
It encompasses a wide variety of technologies, including-
- Machine learning (ML): Uses algorithms trained on data sets to create models that enable machines to perform tasks that would otherwise only be possible for humans.
  - Generative AI (GAI), evolved from ML, as a class of algorithms capable of generating new data. It includes Large Language Models (LLMs) like BharatGPT’s ‘Hanooman’ or ChatGPT and Generative Adversarial Network (GAN) used for generating deepfakes.
- Deep learning: Trains computers to process information in a way that mimics human neural processes.
- Natural language processing (NLP): Allows computers to understand human language. E.g., BHASHINI.

A GPT is a type of LLM that uses deep learning to generate human-like text.
They are called-
- "generative" because they can generate new text based on the input they receive,
- "pretrained" because they are trained on a large corpus of text data before being fine-tuned for specific tasks, and
- "transformers" because they use a transformer based neural network architecture to process input text and generate output text.

Safety in Infrastructural Projects: AI can be used for infrastructure monitoring and inspection.
- E.g., Bangalore Metro is using AI-powered cameras to monitor track conditions, detect abnormalities, and raise alerts.
Personalised Assistants: AI can simplify personal and professional tasks.
- E.g., Ola's Krutrim is a personal generative artificial intelligence assistant that will comprehend around 22 Indian languages and generate text in 10 languages.
Improved Governance: AI can help enhance the efficiency of government operations and public service delivery and make government initiatives more inclusive and accessible. Examples-
- Digital Sansad app is an AI-powered platform to transcribe house proceedings at the new Parliament.
- Kisan-eMitra is an AI Chatbot for the Pradhan Mantri Kisan Samman Nidhi (PM-KISAN) Scheme that provides farmers prompt, clear, and accurate responses to their queries.

Lack of trained professionals: According to NASSCOM, India houses a talent base of 416K AI professionals as opposed to the current demand of approximately 629K, a figure expected to surge to 1 million by 2026.
Impact on Jobs: World Economic Forum has estimated that artificial intelligence will replace some 85 million jobs by 2025.
Infrastructural challenges- Physical and Digital: Lack of AI-based infrastructure, such as cloud computing and limited availability of quality and open-source data.
Ethical and Integrity Concerns:
- AI-based decisions are susceptible to inaccuracies, discriminatory outcomes, bias.
- Unequal access to AI for marginalized populations can worsen the digital divide.
Regulatory challenges:
- Lack of universal definition among regulators due to its global nature.
  - Also, keeping up with the evolving nature of AI can be challenging.
- Lack of transparency in AI systems can lead to users being unaware they are interacting with automated systems, impacting trust.
- Liability issues: The black box nature and self-learning ability of AI make it difficult to justify decisions and assign liability for errors.
  - The inability of seeing how deep learning systems make their decisions is known as the ‘black box problem’.

Growing Instances of misuse: AI is being misused for Malicious Intent such as creation of Deep fakes to spread misinformation.

IndiaAI portal: It serves as a one-stop digital platform for AI-related developments in India.
- It is a joint venture by the Ministry of Electronics and Information Technology (MeitY), National e-Governance Division (NeGD) and National Association of Software and Service Companies (NASSCOM).
Global Partnership on Artificial Intelligence (GPAI): It is amulti-stakeholder initiative which aims to bridge the gap between theory and practice on AI by supporting cutting-edge research and applied activities on AI-related priorities.
- Secretariat: Hosted at the Organisation for Economic Cooperation and Development (OECD) in France.
- Membership: 29 international partners, including India.

Incorporate AI into curriculum, boost teaching and learning and encourage AI ventures.
Firms can undertake upskilling of employees.
- As per a LinkedIn's report, nearly 94% of companies in India are upskilling employees due to advancing AI.
Incentivize Indian start-ups to develop home-grown AI applications
Identify suitable policymakers and regulatory institutions for AI governance laws.
Frame appropriate AI laws drawing on existing national technology policies and international frameworks.

INDIA AI MISSION

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