India in the Global AI Race: Opportunities & Challenges of OpenAI & DeepSeek

Context:

Honorable Prime Minister Narendra Modi called for collective efforts to establish a global framework for AI that upholds shared values, addresses risks, builds trust and ensures access to all, especially the Global South.

Recently, Chinese startup DeepSeek has launched AI models that compete with top U.S. models at a much lower cost.
In December 2024, the company revealed that training its DeepSeek-V3 model cost less than $6 million using Nvidia H800 chips.

What is Artificial Intelligence (AI)?

Artificial intelligence (AI) is the theory and development of computer systems capable of performing tasks that historically required human intelligence, such as recognizing speech, making decisions, and identifying patterns.
AI is an umbrella term that encompasses a wide variety of technologies, including machine learning, deep learning, and natural language processing (NLP).

artificial intelligence technology landscape

What is the history of AI?

Mention different types of AI?

There are three kinds of AI based on capabilities:

Types of AI	Analysis
Narrow AI	Artificial Narrow Intelligence, also known as Weak AI (what we refer to as Narrow AI), is the only type of AI that exists today. It can be trained to perform a single or narrow task, often far faster and better than a human mind can. However, it can’t perform outside of its defined task. Siri, Amazon’s Alexa and IBM Watson® are examples of Narrow AI. Even OpenAI’s ChatGPT is considered a form of Narrow AI because it’s limited to the single task of textbased chat.
General AI	Artificial General Intelligence (AGI), also known as Strong AI, is today nothing more than a theoretical concept. With more resemblance to human capabilities, general artificial intelligence is a more advanced form that can involve visual and language processing, contextual understanding, and the ability to adapt to a range of tasks. AGI can use previous learnings and skills to accomplish new tasks in a different context without the need for human beings to train the underlying models. It’s considered to be far off in the future.
Artificial super AI	Artificial superintelligence is still only a theory, but advances in nascent AI are raising interesting and troubling questions for the future of humanity. Super AI is commonly referred to as artificial superintelligence and, like AGI, is strictly theoretical. If ever realized, Super AI would think, reason, learn, make judgements and possess cognitive abilities that surpass those of human beings.

Types of AI

Analysis

Narrow AI

Artificial Narrow Intelligence, also known as Weak AI (what we refer to as Narrow AI), is the only type of AI that exists today.
It can be trained to perform a single or narrow task, often far faster and better than a human mind can.
However, it can’t perform outside of its defined task.

Siri, Amazon’s Alexa and IBM Watson® are examples of Narrow AI. Even OpenAI’s ChatGPT is considered a form of Narrow AI because it’s limited to the single task of textbased chat.

General AI

Artificial General Intelligence (AGI), also known as Strong AI, is today nothing more than a theoretical concept.

With more resemblance to human capabilities, general artificial intelligence is a more advanced form that can involve visual and language processing, contextual understanding, and the ability to adapt to a range of tasks.
AGI can use previous learnings and skills to accomplish new tasks in a different context without the need for human beings to train the underlying models.
It’s considered to be far off in the future.

Artificial super AI

Artificial superintelligence is still only a theory, but advances in nascent AI are raising interesting and troubling questions for the future of humanity.

Super AI is commonly referred to as artificial superintelligence and, like AGI, is strictly theoretical.
If ever realized, Super AI would think, reason, learn, make judgements and possess cognitive abilities that surpass those of human beings.

There are four types of AI based on functionalities:

Types of AI	Analysis
Reactive Machine AI	Reactive machines are AI systems with no memory and are designed to perform a very specific task. Since they can’t recollect previous outcomes or decisions, they only work with presently available data. Reactive AI stems from statistical math and can analyze vast amounts of data to produce a seemingly intelligent output. Examples of Reactive Machine AI: IBM Deep Blue: IBM’s chess-playing supercomputer AI beat chess grandmaster Garry Kasparov in the late 1990s by analyzing the pieces on the board and predicting the probable outcomes of each move.
Limited Memory AI	Unlike Reactive Machine AI, this form of AI can recall past events and outcomes and monitor specific objects or situations over time. Limited Memory AI can use past- and presentmoment data to decide on a course of action most likely to help achieve a desired outcome. However, while Limited Memory AI can use past data for a specific amount of time, it can’t retain that data in a library of past experiences to use over a long-term period. Examples of Limited Memory AI: Generative AI: Generative AI tools such as ChatGPT, Bard and DeepAI rely on limited memory AI capabilities to predict the next word, phrase or visual element within the content it’s generating. Virtual assistants and chatbots: Siri, Alexa, Google Assistant, Cortana and IBM Watson Assistant combine natural language processing (NLP) and Limited Memory AI to understand questions and requests, take appropriate actions and compose responses. Self-driving cars: Autonomous vehicles use Limited Memory AI to understand the world around them in real-time and make informed decisions on when to apply speed, brake, make a turn, etc
Theory of Mind AI	Theory of Mind AI is a functional class of AI that falls underneath the General AI. Though an unrealized form of AI today, AI with Theory of Mind functionality would understand the thoughts and emotions of other entities. This understanding can affect how the AI interacts with those around them. In theory, this would allow the AI to simulate human-like relationships. Because Theory of Mind AI could infer human motives and reasoning, it would personalize its interactions with individuals based on their unique emotional needs and intentions.
Self-Aware AI	Self-Aware AI is a kind of functional AI class for applications that would possess super AI capabilities. Like theory of mind AI, Self-Aware AI is strictly theoretical. If ever achieved, it would have the ability to understand its own internal conditions and traits along with human emotions and thoughts. It would also have its own set of emotions, needs and beliefs.

What is OpenAI?

OpenAI is an AI research lab and company that aims to develop AI and steer it in ways that “benefit all of humanity.”
It was created at first as a non-profit organization due to its founders’ concerns about the potential misuse and catastrophe from AI being used “in the wild.”
Several investors pooled together $1 billion to deliver research and resources that remain open to the public.

What is the timeline and history of OpenAI?

OpenAI was founded in 2015 with a focus on developing AI and machine learning tools for various activities.
Its first offering was an open-source toolkit for developing reinforcement learning algorithms (OpenAI Gym), which prompted it to focus on AI research for more general purposes.

Mention about the applications of OpenAI?

Applications	Analysis
It can Be Integrated Into Applications	AI’s primary purpose is to provide the ability to integrate tools into your own apps, so with the help of API, these tools can be integrated, which is why nullifying the requirement to build models from scratch. Even coders can integrate the GPT-based model into their applications using programming languages such as JavaScript or Python.
Virtual Assistants and Chatbots	ChatGPT-3 generates text and performs natural language processing tasks by powering virtual help and chatbots in applications. The best thing about the chatbot is that it can integrate into various applications, from ecommerce to healthcare.
Content Generation	GPT models enable content creation within the applications. In simple terms, it can be used to write apps to generate text per the user’s requirement. Overall, the GPT model allows a faster writing process and enriches the overall quality of content.
Image Generation	Dall. E is a GPT-based model of OpenAI that can be integrated into applications to generate pictures and per-text promptings. If you have an eCommerce platform, this model is suitable for building product images and saves a lot of manpower.
Enables ProblemSolving and Scientific Research	OpenAI makes the work easy by helping scientists and researchers identify patterns and drive new innovations via their discoveries. On the other hand, AI’s smart algorithm allows businesses to optimize complex operations along with energy distribution or traffic flow. Moreover, it is known for predicting outcomes and recommending suggestions in the field of finance or marketing, as well as helping to make better decisions.
Easy AI Accessibility and Affordability	Offering a vast range of APIs and tools, OpenAI can assist in building AI systems and apps. Offering a vast range of APIs and tools, OpenAI can assist in building AI systems and apps.

Mention about the challenges of OpenAI?

Challenges	Analysis
Limited Online Browsing Capabilities	It is obvious that developers and researchers carrying out their tasks using GPT-based models have to face limitations regarding OpenAI’s online browsing capabilities. The reason behind these models is that we can not fully access information on the web in real-time. The inability to browse external sources of information that rely on existing data makes it difficult in order to handle complex queries. However, it provides inaccurate predictions that can be risky.
Potential for Misuse	As the popularity of AI technology is increasing, many individuals or companies may try to use them with malicious intent. It is a cause of concern in warfare or other probabilities. It creates images that look real but fake images can manipulate people or spread illicit information.
Data Privacy and AI Bias	As OpenAI is driven by training based on data, it brings some issues regarding its effectiveness. This technology also brings up concerns related to AI bias and data privacy. If a GPT-based model is fed data showing societal or other types of biases, they may hold those biases to offer further results. On the other hand, AI is known to store large amounts of data and therefore there are higher chances of data misuse or potential privacy violation.
Little Transparency and Accountability	Another drawback of OpenAI is its opaqueness in making decisions and processing data. It creates a hurdle for agencies to determine how or why they came to a specific output. Plus, little transparency can also create issues.

What is DeepSeek?

DeepSeek AI is an advanced Chinese artificial intelligence model designed to perform tasks such as text generation, language translation, and human-like conversation.
It is developed to compete with leading AI technologies from the West, including models from OpenAI, Google, and Meta.
The startup was founded in 2023 in Hangzhou, China, by Liang Wenfeng, who previously co-founded one of China's top hedge funds, High-Flyer.
The company wrote in a paper last month that the training of DeepSeek-V3 required less than $6m (£5m) worth of computing power from Nvidia H800 chips.
The overall cost-effectiveness of DeepSeek is highlighted by its pricing structure, which is reportedly 20–40 times cheaper than equivalent models from OpenAI.

What is the history of DeepSeek?

10.

How does DeepSeek work?

DeepSeek operates through a structured process:

Process	Analysis
Data Collection	Gather data from various sources, including databases, sensors, and online platforms.
Preprocessing	Cleans, normalizes, and organizes data for accurate analysis.
Model Training	Uses deep learning to train neural networks, fine-tuning them for accuracy.
Inference	Analyzes new data to generate insights or predictions.
Continuous Learning	Refines algorithms by incorporating new data over time.

11.

Mention about the applications of DeepSeek?

Application	Analysis
Text generation	Writing different types of content like articles, emails, social media posts, and even creative writing.
Information summarization	Condensing large amounts of text into concise summaries
Question answering	Providing detailed answers to complex questions.
Reasoning and logic tasks	Solving logical puzzles and mathematical problems.

12.

Mention about the challenges of DeepSeek?

Challenges	Analysis
Data Privacy	As a Chinese company, DeepSeek stores user data in China, raising concerns about potential access by the Chinese government and potential data leaks. China’s extensive surveillance infrastructure raises concerns about AI being used for monitoring rather than unbiased decisionmaking.
Bias in Training Data	The model is likely trained on data reflecting a Chinese perspective, potentially leading to biased outputs when dealing with topics sensitive to different cultural contexts.
Lack of Diversity in Development Teams	A homogenous AI development team may overlook potential biases, leading to unintentional discrimination.
Context Mismatch	An AI model trained in one cultural or economic setting may produce inaccurate results when applied in another.
Misuse Potential	The open-source nature of DeepSeek could allow malicious actors to easily access and modify the model for harmful purposes.
Regulatory Restrictions	Due to privacy and security concerns, several countries and organizations have banned DeepSeek, including government agencies in Australia, Italy, and the United States.
Lack of Transparency	Limited information about DeepSeek's development process and data practices can further exacerbate concerns about its reliability and ethical implications.
Regulatory and Ethical Standards	China’s AI governance differs from international standards, raising concerns about fairness, transparency, and ethical compliance.

13.

Enlist various differences between DeepSeek and OpenAI?

14.

What makes DeepSeek AI models different from other global large language models?

Features	Analysis
Size	Despite being developed by a smaller team with drastically less funding than the top American tech giants, DeepSeek is punching above its weight with a large, powerful model that runs just as well on fewer resources. Despite being larger than other AI models, DeepSeek-R1 uses only a fraction of its parameters in each interaction.
Cost Efficiency
Performance	Despite its relatively modest means, DeepSeek’s scores on benchmarks keep pace with the latest cutting-edge models from top AI developers in the United States.
Advanced AI Architecture	DeepSeek's Mixture-of-Experts (MoE) architecture consists of multiple specialized submodels, or “experts,” each trained to handle specific types of tasks or data. When a query is processed, the system intelligently selects and activates only the most relevant experts rather than engaging the entire model.

15.

Why is DeepSeek raising alarms in the U.S.?

While there was much hype around the DeepSeek-R1 release, it has raised alarms in the U.S., triggering concerns and a stock market sell-off in tech stocks.
On Monday, Jan. 27, 2025, the Nasdaq Composite dropped by 3.4% at market opening, with Nvidia declining by 17% and losing approximately $600 billion in market capitalization.

DeepSeek is raising alarms in the U.S. for several reasons, including the following:

Concern	Analysis
Cost disruption	DeepSeek claims to have developed its R1 model for less than $6 million. The low-cost development threatens the business model of U.S. tech companies that have invested billions in AI. DeepSeek is also cheaper for users than OpenAI.
Technical achievement despite restrictions	The export of the highest-performance AI accelerator and GPU chips from the U.S. is restricted to China. Yet, despite that, DeepSeek has demonstrated that leading-edge AI development is possible without access to the most advanced U.S. technology.
Business model threats	In contrast with OpenAI, which is proprietary technology, DeepSeek is open source and free, challenging the revenue model of U.S. companies charging monthly fees for AI services.
Geopolitical concerns	Being based in China, DeepSeek challenges U.S. technological dominance in AI. Tech investor Marc Andreessen called it AI's "Sputnik moment," comparing it to the Soviet Union's space race breakthrough in the 1950s.

16.

Enlist countries that have banned the use of DeepSeek’s AI?

Country	Analysis
Italy	Italy was one of the first countries to ban DeepSeek AI over concerns about the handling of user data and compliance with EU data protection laws. The Italian Data Protection Authority (DPA) investigated DeepSeek's data collection practices and removed the AI platform from app stores in the country.
Taiwan	Taiwan banned the use of DeepSeek AI across all public sector organisations, including public schools, state-owned enterprises, and critical infrastructure. The Ministry of Digital Affairs cited concerns about cross-border data transmission and information leaks as the reason for the ban.
Australia	The Australian government has banned its employees from using the DeepSeek AI chatbot on government devices. Home Affairs Minister Tony Burke stated that a national intelligence assessment found the AI platform to pose an unacceptable security risk.
United States	The American Navy has restricted the use of DeepSeek, and Texas was the first state to ban the Chinese AI app. Several federal agencies have instructed employees against accessing DeepSeek, and "hundreds of companies" have requested their enterprise cybersecurity firms to block access to the app.
India	The Ministry of Finance has banned the use of DeepSeek by its employees. The central government has prohibited its employees from using AI tools and applications such as DeepSeek and ChatGPT on office computers and devices.

17.

Where does India stand in the global AI race?

India is emerging as one of the global leaders in the field of Artificial Intelligence (AI), with the country securing fourth rank in AI development in an assessment by the US-based Stanford Institute for Human-Centered AI (HAI)
The Stanford HAI has released its findings about the AI-led technology ecosystem at a global level, using the Global Vibrancy Tool 2024 developed by the institute.
According to the index, India scores highly in AI research and development, indicated by a good performance in parameters such as AI Journal Publications, AI Conference Publications, AI Journal Citations and AI Conference Citations, alongside having notable AI GitHub projects and scoring well in relative AI skill penetration, AI hiring and AI talent concentration.
However, India lags behind the top three countries in areas such as policy and governance and infrastructure, bringing down its overall weighted score.

18.

What is the history of AI development in India?

19.

What is the impact of Artificial Intelligence on various sectors in India?

Sectors	Impact
Healthcare	AI is revolutionizing the healthcare industry by enabling more accurate diagnoses, personalized treatments, and improved patient outcomes. Machine learning algorithms can analyze medical images, such as X-rays and MRIs, to detect anomalies and assist radiologists in their diagnoses. AI-powered chatbots and virtual assistants are enhancing patient interactions and providing 24/7 support. Additionally, AI-driven predictive analytics can help healthcare providers identify high-risk patients and intervene early to prevent diseases.
Finance	AI is transforming the finance industry by automating repetitive tasks, improving fraud detection, and enhancing customer experiences. AI algorithms can analyze vast amounts of financial data, identify patterns, and make real-time predictions for investment decisions. Robo-advisors are using AI to provide personalized financial advice to investors. AI-powered chatbots and virtual assistants are streamlining customer service, addressing inquiries, and simplifying banking processes. Moreover, AI-based algorithms can detect fraudulent transactions and prevent financial crimes more effectively.
Manufacturing	AI is driving the concept of smart manufacturing by optimizing production processes, reducing downtime, and improving product quality. AI-powered robots and automation systems are taking over repetitive tasks, leading to increased efficiency and productivity. Machine learning algorithms are used to predict maintenance needs and schedule proactive repairs, minimizing unplanned downtime. AI-enabled quality control systems can detect defects in real-time, ensuring products meet the highest standards.
Retail	AI is revolutionizing the retail industry by enhancing customer experiences, improving inventory management, and enabling personalized marketing. Recommendation systems powered by AI algorithms provide personalized product suggestions based on customer preferences and browsing history.
Education	AI is transforming the education industry by personalizing learning experiences, automating administrative tasks, and facilitating adaptive assessments. AI-powered learning platforms can adapt content based on individual student needs, providing personalized education pathways.
Agriculture	AI is revolutionizing the agricultural sector by optimizing crop yields, reducing resource consumption, and improving farming practices. AI algorithms analyze environmental data, soil conditions, and weather patterns to provide farmers with insights on optimal planting times, irrigation schedules, and pest control measures. AI-powered drones and robots can monitor crops, identify disease outbreaks, and automate labor-intensive tasks.

20.

What are the challenges in India’s AI development?

Despite the well-acknowledged potential of AI to drive national growth and prosperity, there are significant hiccups along the way that are hampering a wide scale adoption of AI solutions in India.
The Data Security Council of India (DSCI) has highlighted some of these key challenges in a recently released whitepaper.

Challenges	Analysis
Data security and privacy issues	AI solutions built on ML and DL are based on a huge volume of confidential data, which are often sensitive and personal in nature. Along with automation, AI also brings a range of security and privacy vulnerabilities, which can subsequently exacerbate any organisation's exposure to cyber risk and geopolitical risk. However, India is moving in the right direction with the Personal Data Protection Bill, 2019, and the National Cyber Security Strategy, 2020.
Limited AI expertise and lack of investment to implement AI solutions	AI requires highly trained and skilled professionals, but being an emerging technology, the talent pool is limited. As per McKinsey, “Talent is one of the biggest challenges to AI, no matter how advanced a company’s digital program, it’s perhaps not surprising that companies are leaving no stone unturned when sourcing people and skills.” There are concerted efforts to be seen, in the form of NASSCOM’s FutureSkills Prime initiative, for instance, which aims to bridge the skilling gaps. Furthermore, high implementation cost resists numerous organizations to implement AI solutions. For instance, transforming a manufacturing plant from manual operation to automated operation would require high capital investment to integrate IIoT and other components of industry 4.0.
Lack of AI and cloud computing infrastructure	AI and cloud are inseparable because AI is data hungry and cloud is the only viable solution. There are endless possibilities to scale up AI with its convergence with cloud computing. However, despite the potential, India lacks access to specialised compute and storage facilities which forms the backbone of AI. A beginning has been made with India’s own AIfirst compute infrastructure, AIRAWAT, which is a cloud platform for Big Data analytics with advanced AI processing capabilities.
Lack of data and poor data quality	Data is the backbone of AI, hence easy availability of open-source data is crucial for any country to accelerate AI innovation and adoption. Apart from regulatory restrictions on data, data annotation and labelling are tedious but essential processes to provide useful datasets. The government has very recently opened access to geospatial data and services, a step that is sure to encourage innovation in this area.
Lack of integrity and ethics with AI and ML solutions	With the advent of AI products and algorithms and their increasing role in decision making, ethics and morality have emerged as a major challenge for the AI solution providers. An AI algorithms work based on training given to it, meaning the AI solution predicts instances based on the data being fed into it and based on the self-learning capability. However, in a few instances, the AI algorithm overlooks the correctness of the data and gives an ambiguous result. It is also possible for the results to be skewed due to tampering of the dataset itself.

21.

Mention initiatives taken by India for AI development?

Initiatives	Analyses
IndiaAI Mission	The mission aims to establish a robust AI computing infrastructure in India to support the development and testing of AI systems. The Mission aims to enhance data quality, and develop indigenous AI technologies. The Union Cabinet approved the Rs 10,372 crore for IndiaAI Mission.
National Strategy for Artificial Intelligence	The National Strategy for Artificial Intelligence was launched by NITI Aayog, to position India as a leader in AI for economic growth, social development, and inclusive growth. It emphasizes leveraging AI for societal needs, such as healthcare, education, agriculture, and smart cities.
AI for All	The strategy focuses on ensuring the benefits of AI are accessible to the entire Indian population. It includes developing AI technologies that address language diversity, enhance skill development, and promote ethical AI use.
Budget 2025-26	In the latest Budget session, the government allocated ₹500 crore for setting up a Centre of Excellence in AI for education to improve India’s education system by using AI. This initiative builds on the three AI centres set up in 2023 for agriculture, healthcare, and sustainable cities.

22.

What is the Paris AI summit 2025?

The Paris AI Summit 2025, held on February 10-11 at the Grand Palais, convenes global leaders, tech giants, and experts to discuss AI's future. Co-hosted by France and India, the summit focuses on equitable AI access, environmental sustainability, and establishing international governance frameworks.
This is the third edition of the AI Action Summit, following two previous editions held in the UK in 2023 and a smaller gathering in Seoul, South Korea, last year.
The Paris AI Summit 2025 focuses on several key themes related to the opportunities, benefits, and governance of AI.
These themes include:
AI for Public Good: Exploring how AI can be applied in sectors like healthcare, education, and governance to benefit society.
Future of Work: Examining AI's impact on job automation and the creation of new employment opportunities.
Innovation and Culture: Discussing AI's transformative role in creativity, content generation, and cultural industries.
Global AI Governance: Seeking common ground on ethical AI use, regulations, and global policies.
Trust and Transparency: Addressing concerns related to AI's decision-making processes, biases, and the spread of misinformation.
Environmentally Sustainable AI Solutions: Promoting AI development that is environmentally friendly.

What is the relevance of the topic for UPSC CSE?

For Prelims: Key Recent Breakthroughs in Artificial Intelligence, Applications of AI in Different Sector, Precision farming, Digital banking, Acing Development of Innovative Technologies with iDEX (ADITI) scheme, India Skills Report, Quick commerce, Personal Data Protection Act 2023, FutureSkills Prime initiative.

For Mains: Key Opportunities AI Revolution Brings for India's Economic Growth, Key Challenges AI Poses to India's Traditional Economy

Check Complete UPSC CSE Syllabus

Know about UPSC Civil Services Exam

Some Previous Years Prelims Questions

Q1. Which one of the following words/phrases is most appropriately used to denote “an interoperable network of 3D virtual worlds that can be accessed simultaneously by millions of users, who can exert property rights over virtual items”?(2024)

(a) Big data analytics

(b) Cryptography

(d) Virtual matrix

Ans: (c)

Q2. With the present state of development, Artificial Intelligence can effectively do which of the following?(2020)

1. Bring down electricity consumption in industrial units

2. Create meaningful short stories and songs

3. Disease diagnosis

4. Text-to-Speech Conversion

5. Wireless transmission of electrical energy

Select the correct answer using the code given below:

(a) 1, 2, 3 and 5 only

(b) 1, 3 and 4 only

(d) 1, 2, 3, 4 and 5

Ans: (b)

Check UPSC Prelims Previous Year Question Papers

Some Previous Years Mains Questions

Q1. The application of Artificial Intelligence as a dependable source of input for administrative rational decision-making is a debatable issue. [10 Marks, 2024]

Q2. Introduce the concept of Artificial Intelligence (AI). How does AI help clinical diagnosis? Do you perceive any threat to privacy of the individual in the use of AI in healthcare? [10 Marks, 2023]

Check UPSC Mains Previous Year Question Papers

Some Questions from This Year and Previous Years Interview Transcripts

Board Sheel Vardhan sir:

What is the Difference between Artificial Intelligence (AI) and Machine Learning?
What is artificial about AI?
What is singularity in AI?
I am anxious about AI as a technology.
Are you anxious about AI?

Board Sanjay Verma sir:

What do you mean by intelligence
Now what is artificial intelligence?
Who is intelligent - human intellectual or artificial intelligence?
Where is maths used in AI?

Board B.B. Swain Sir:

Have you heard about Artificial intelligence?

Board BB Swain Sir:

You have worked on Al.
We have seen the proliferation of Al like ChatGPT.
What is GPT in ChatGPT?
Give me examples of Al tools other than ChatGPT.

Board Dinesh Dasa sir:

Tell me will there be job loss by AI ?

Some Questions for QUIZ

Q1. With reference to the Global Partnership on Artificial Intelligence (GPAI) consider the following statements.

1. GPAI is an international initiative to support responsible and human-centric development and use of Artificial Intelligence (AI).

2. India is one of its founding members.

3. GPAI was launched in the year 2023 during the G20 summit.

4. UNESCO has an observer status to GPAI.

5. GPAI is supported by a Secretariat hosted by the OECD.

How many of the above statements are correct?

(a) Only two

(b) Only three

(d) All five