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What Is Quantum Computing? A Beginner’s Guide to the Quantum Revolution

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Introduction

Imagine a computer so powerful it can perform calculations that would take today’s fastest supercomputers millions of years — in just seconds. This is not science fiction; it is the promise of quantum computing.

Quantum computing stands at the frontier of a technological revolution, poised to redefine how we solve complex problems, from developing life-saving drugs to securing digital information. But what exactly is quantum computing, and why is it so radically different from the computers we use today?

In this guide, we’ll break down the basics of quantum computing in a simple, beginner-friendly way — no advanced physics degree required.


What Is Quantum Computing?

At its core, quantum computing is a new way of performing computations by harnessing the strange, counterintuitive laws of quantum mechanics — the branch of physics that deals with the behavior of the tiniest particles in the universe.

Unlike traditional computers that process information using bits (which can be either a 0 or a 1), quantum computers use qubits. Qubits can exist as a 0, a 1, or both at the same time, thanks to a phenomenon called superposition.

This ability allows quantum computers to process massive amounts of information simultaneously, opening doors to solving problems that are practically impossible for classical machines.


How Quantum Computers Are Different from Classical Computers

To understand why quantum computers are so powerful, it’s essential to first see how they differ from classical computers.

Classical ComputerQuantum Computer
Uses bits (0 or 1)Uses qubits (0, 1, or both at once)
Processes one computation at a timeProcesses many computations simultaneously
Limited by Moore’s Law (transistor miniaturization)Potential to surpass classical limitations
Great for everyday tasksBest for specialized, complex problems

In simple terms, a classical computer might try one solution at a time when solving a maze. A quantum computer could, in theory, try all possible paths at once and pick the best route.

This parallelism doesn’t mean quantum computers are universally faster — they excel in very specific kinds of problems, such as factoring large numbers or simulating quantum systems themselves.


Key Quantum Concepts Behind Quantum Computing

Quantum computing leverages several mind-bending concepts from quantum mechanics. Let’s explore the most important ones:

Qubits

A qubit is the quantum version of a bit.

  • In a classical computer, a bit must be a definite 0 or 1.
  • In a quantum computer, a qubit can be 0, 1, or any combination of both at the same time.

Qubits can be made using a variety of technologies, including superconducting circuits (IBM, Google), trapped ions (IonQ), or even photons (light particles).


Superposition

Superposition is the ability of a qubit to be in multiple states at once.
Think of it like spinning a coin: while spinning, the coin isn’t just heads or tails — it’s a mixture of both.

This property enables quantum computers to explore multiple possibilities simultaneously, dramatically increasing their computational power.


Entanglement

Entanglement is a strange phenomenon where two qubits become connected, such that the state of one instantly affects the state of the other, even if they are light-years apart.

This “spooky action at a distance,” as Einstein called it, allows for powerful quantum operations and information sharing that are impossible in classical systems.


Quantum Interference

Quantum computers use interference to amplify the probability of correct answers and cancel out incorrect ones.
Interference is why quantum algorithms can find solutions more efficiently than classical ones.


Why Quantum Computing Matters

Quantum computers are not just “faster” computers — they are different kinds of machines that can solve certain problems qualitatively better than classical computers.

Here are a few areas where quantum computing could be revolutionary:

  • Cryptography: Quantum computers could break many current encryption methods but also enable new, ultra-secure communication systems.
  • Drug Discovery: Simulating molecular interactions at a quantum level could accelerate the development of new medicines.
  • Materials Science: Designing new materials like superconductors that work at room temperature.
  • Optimization Problems: Solving complex logistical problems (e.g., supply chain management, traffic flow) faster and more efficiently.

Importantly, for everyday tasks like browsing the web or editing documents, quantum computers would not replace classical computers — they are specialized tools for specific, incredibly hard problems.


Current State of Quantum Computing

Despite the hype, quantum computing is still in its early stages.

Most current quantum computers have relatively few qubits (between 50 and 400), and their operations are prone to errors due to decoherence — the tendency of quantum information to degrade when interacting with the environment.

Some major players leading quantum research include:

  • IBM: Building superconducting quantum processors and offering cloud access through IBM Quantum.
  • Google: Achieved “quantum supremacy” in 2019 by completing a calculation faster than the world’s fastest supercomputer.
  • IonQ: Focused on trapped-ion technology for more stable qubits.
  • D-Wave: Specialized in quantum annealing, a different model suited for optimization problems.

While significant progress has been made, practical, large-scale quantum computing is still a work in progress.


Challenges in Quantum Computing

Several technical hurdles must be overcome before quantum computing can fulfill its full potential:

  • Decoherence: Qubits lose their quantum state very quickly, requiring extreme cooling and isolation.
  • Error Correction: Quantum information is fragile, making error correction extremely challenging and resource-intensive.
  • Scalability: Building quantum computers with millions of reliable qubits is an enormous engineering challenge.
  • Cost: Quantum computers are currently extremely expensive to build and maintain.

Researchers around the world are working tirelessly to overcome these obstacles, and new breakthroughs happen regularly.


The Future of Quantum Computing

The future of quantum computing is incredibly promising — but it’s a marathon, not a sprint.

In the next decade, we may see quantum computers:

  • Achieving quantum advantage in real-world applications (not just lab demos).
  • Transforming industries like pharmaceuticals, finance, logistics, and cybersecurity.
  • Merging with AI technologies to create even more powerful systems.

However, practical, large-scale quantum computers that outperform classical ones across the board may still be 10–20 years away.

Early adopters and companies investing now could be among the major beneficiaries of this technological revolution.


Conclusion

Quantum computing is not just a faster version of today’s computers — it’s a fundamentally different way of processing information, built upon the mysterious principles of quantum mechanics.

While challenges remain, the possibilities are breathtaking. Quantum computing could revolutionize how we discover medicines, solve complex problems, and even understand the universe itself.

At Xeb Labs, we are committed to helping you navigate this exciting frontier. Whether you’re a curious beginner or an aspiring quantum engineer, this is just the start of your quantum journey.

Today in History – 1 May

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today in history 1 may

today in history 1 may1867

Sri Kasinadhuni Nageswara Rao Pantulu, great freedom fighter, journalist, nationalist, politician, pioneer in library movement and litterateur, was born at Elakurru village in Gudivada Taluk, District Krishna.

1879

Swami Vivekanand established Ramkrishna Mission.

1886

May Day was first observed in Chicago, USA. Work, Social activities, Rest, for 8 Hours.

1909

Madame Bhikaji Cama secretly left London and went to France where she was wrote and spoke about the cruelty of Britishers.

1915

Rameshwar Shukla ‘Anchal’, modern Hindi poet, novelist and essay writer, was born.

1922

Madhu Limaye, great politician, freedom fighter, writer and national leader, was born at Pune, Maharashtra.

1923

Under the leadership of Singaravelu Chettiar, the first May day was celebrated in India.

1940

Marathi magzine `Digdarshan’ was published.

1947

Congress Working Committee accepts Partition in principle.

1948

Baroda State merged into Bombay Province.

1958

President Eisenhower proclaims Law Day to honor the role of law in the creation of the United States of America. Three years later, Congress followed suit by passing a joint resolution establishing May 1 as Law Day.

1960

Old Bombay province was divided between Maharashtra and Gujrat States.

1964

Ravishankar University was established at Raipur in Madhya Pradesh.

1966

Marathi becomes the official language of Maharashtra.

1972

All fuel coal mines were nationalised.

1973

All non-fuel Coal Mines fields were nationalised.

1977

Janata Party was established.

1983

Amravati University established.

1987

The Bofors Deal.

1993

Narayan Ganesh Goray, socialist stalwart, 86, passed away in Pune.

1994

Political party Shiromani Akali Dal was established.

1995

SAARC endorses South Asia Free Trade Area (SAFTA) and establishes a South Asian Development Fund (SADF) for the economic and technical development of the subcontinent.

1996

International women’s master Anupama Gokhale of Bharat Petroleum becomes the first woman in the history of Indian chess to win an all-India level international rating tournament with her bagging the Mohammed Hassan memorial title.

1998

The Konkan Railway running for 760-km is dedicated to the nation by Prime Minister Atal Bihari Vajpayee. This was an extention from Ratnagiri.

1998

India and Peru sign agreements on space technology and agriculture during the visit of Indian President K. R. Narayanan there.

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Datafication – All you need to know!

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Datafication as digital representative image

In today’s digital age, data has become the lifeblood of organizations across industries. The process of datafication, which involves the collection, analysis, and transformation of various aspects of the world into data, is revolutionizing the way businesses operate. By harnessing the power of data, companies can gain valuable insights, make data-driven decisions, and drive digital transformation. In this article, we will explore the concept of datafication, its significance, and the opportunities and challenges it presents.

Table of contents
1. Understanding Datafication
2. The Benefits of Datafication
3. Challenges and Considerations
4. Future Trends in Datafication
5. Conclusion

Understanding Datafication

Datafication is the process of converting diverse forms of information, behaviors, and activities into structured and quantifiable data. It involves capturing data from various sources such as social media, online transactions, sensors, and more, and transforming it into a digital format that can be analyzed and utilized.


The Benefits of Datafication

Insights and Decision Making: Datafication enables organizations to extract insights from vast amounts of data. By analyzing patterns, trends, and correlations, businesses can make informed decisions and drive innovation.

Personalization: Through datafication, companies can understand customer preferences, behavior, and needs, allowing them to deliver personalized experiences and tailored offerings.

Efficiency and Optimization: Data-driven processes and automation can optimize operations, improve efficiency, and reduce costs.

Innovation and New Opportunities: Datafication opens doors to new business models, products, and services by uncovering untapped market opportunities and identifying emerging trends.

Read more: ChatGPT threat and benefits

Challenges and Considerations

Privacy and Ethics: The extensive collection and use of personal data raise concerns about privacy and ethical considerations. Organizations must ensure proper data governance, transparency, and compliance with privacy regulations.

Data Quality and Security: Ensuring data accuracy, integrity, and security is crucial to maintain trust and reliability in data-driven decision-making processes.

Skills and Infrastructure: Effective datafication requires skilled professionals, robust infrastructure, and advanced analytics tools to handle the complexities of data collection, storage, analysis, and interpretation.

Future Trends in Datafication

Internet of Things (IoT): The proliferation of connected devices will generate massive amounts of data, further accelerating the datafication process.

Artificial Intelligence (AI) and Machine Learning (ML): AI and ML algorithms can unlock deeper insights and automate data analysis, driving more intelligent decision-making.

Data Collaboration and Sharing: Collaboration between organizations and sharing of non-sensitive data can lead to more comprehensive insights and mutually beneficial outcomes.

Datafication is reshaping the business landscape, offering organizations unprecedented opportunities to unlock valuable insights, drive digital transformation, and deliver enhanced customer experiences. However, it also demands responsible data governance, ethical considerations, and robust security measures. By embracing datafication and leveraging data strategically, businesses can stay competitive, innovate, and thrive in the data-driven era.

The Advancements and Threats of AI: Analyzing the Benefits and Risks of ChatGPT and GPT-4

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an ai powered robot trying to fix the world

Artificial Intelligence (AI) has become increasingly popular in recent years, with new technologies such as ChatGPT and GPT-4 revolutionizing the field. These language models can interact with natural language input, providing a more human-like experience and creating new opportunities for businesses and consumers alike. However, with any new technology, there are both benefits and risks to consider. In this article, we will explore the advantages and disadvantages of AI advancements, with a particular focus on ChatGPT and GPT-4.

Benefits of AI Advancements

  1. Enhanced Efficiency and Productivity One of the most significant benefits of AI is its ability to automate repetitive and time-consuming tasks, freeing up employees to focus on more important work. ChatGPT and GPT-4 allow businesses to use natural language processing to communicate with customers and automate customer service interactions, saving time and resources while improving the customer experience.
  2. Improved Personalization One of the key advantages of AI is its ability to provide personalized experiences. ChatGPT and GPT-4 can use natural language processing to understand customer needs and preferences, allowing businesses to offer personalized recommendations and targeted marketing campaigns. This can improve customer engagement and drive sales.
  3. Better Decision Making AI can analyze vast amounts of data quickly and accurately, providing businesses with insights and recommendations that humans may not have identified. With ChatGPT and GPT-4, businesses can use natural language processing to interpret customer feedback and identify trends, helping them make informed decisions.
  4. Improved Healthcare Outcomes AI advancements have the potential to revolutionize healthcare, from improved diagnoses to more personalized treatments. ChatGPT and GPT-4 can help healthcare providers understand patient symptoms and provide personalized treatment plans. This can lead to better health outcomes and more efficient use of resources.
  5. Increased Safety and Security AI can enhance safety and security in various industries, including transportation, defense, and finance. For example, self-driving cars and drones can use AI to analyze data and make decisions in real-time, reducing the risk of accidents. In addition, AI can detect and prevent fraud and cyber attacks, protecting sensitive information and assets.

Risks of AI Advancements

  1. Job Displacement One of the most significant risks of AI advancements is the potential for job displacement. As AI technology improves, it may replace jobs that were previously done by humans. This could lead to significant job loss in certain industries, particularly those that rely heavily on manual labor or repetitive tasks. However, some argue that AI will also create new jobs and opportunities, particularly in fields such as data analysis and programming.
  2. Bias and Discrimination AI algorithms can reflect the biases of their creators or the data they are trained on. This can lead to discrimination against certain groups of people, such as women and minorities. In addition, AI can perpetuate existing societal biases and reinforce stereotypes, potentially leading to unfair treatment. To mitigate this risk, it is essential to ensure that AI is trained on diverse and representative data and that algorithms are regularly audited for bias.
  3. Privacy Concerns AI advancements can collect vast amounts of personal data, raising concerns about privacy and the potential for misuse of this information. With ChatGPT and GPT-4, businesses may collect and store customer conversations, potentially exposing sensitive information to data breaches or cyberattacks. To address this risk, it is essential to ensure that data collection and storage practices are transparent and that adequate security measures are in place.
  4. Lack of Accountability As AI becomes more autonomous, it can be difficult to determine who is responsible for its actions. This can raise ethical concerns and create legal challenges. In addition, AI can make decisions based on data and algorithms that may not be transparent or easily understood by humans, making it difficult to hold anyone accountable for potential mistakes or harmful outcomes. To address this risk, it is crucial to establish clear guidelines and regulations for the development and deployment of AI technology, as well as to prioritize transparency and accountability in AI decision-making.
  5. Security Risks While AI can enhance safety and security, it can also create new security risks. As AI technology becomes more advanced, it may be vulnerable to cyber attacks, and malicious actors may use AI to conduct attacks more efficiently and effectively. To address this risk, it is essential to prioritize security in the development and deployment of AI, including regular testing and updating of security protocols.

ChatGPT and GPT-4: Advancements in AI Language Models

ChatGPT and GPT-4 are two recent advancements in AI language models that have garnered significant attention. ChatGPT is a conversational AI model that uses natural language processing to generate human-like responses to user inputs. GPT-4, on the other hand, is a more general-purpose language model that can perform a wide range of tasks, such as language translation, question-answering, and summarization.

Benefits of ChatGPT and GPT-4

  1. Improved Customer Experience ChatGPT can help businesses provide a more personalized and engaging customer experience by responding to customer inquiries in a conversational and natural way. This can increase customer satisfaction and loyalty, leading to increased sales and revenue.
  2. Increased Efficiency Both ChatGPT and GPT-4 can automate repetitive tasks, such as responding to customer inquiries or summarizing documents. This can increase efficiency and productivity, allowing businesses to focus on more strategic activities.
  3. Improved Accuracy AI language models can analyze vast amounts of data quickly and accurately, improving the quality of recommendations and insights. ChatGPT and GPT-4 can use natural language processing to understand customer feedback and identify trends, providing businesses with valuable insights that they may not have otherwise identified.

Risks of ChatGPT and GPT-4

  1. Potential for Misuse As with any AI technology, there is a risk that ChatGPT and GPT-4 could be misused for malicious purposes, such as generating fake news or spreading disinformation. This could have significant social and political implications, and it is essential to ensure that AI language models are used responsibly.
  2. Lack of Transparency AI language models can be difficult to understand and interpret, making it challenging to assess the accuracy and fairness of their outputs. This lack of transparency could lead to bias and discrimination, and it is essential to prioritize transparency and accountability in the development and deployment of AI language models.
  3. Privacy Concerns ChatGPT and GPT-4 can collect and store vast amounts of personal data, raising concerns about privacy and the potential for misuse of this information. To address this risk, it is essential to ensure that data collection and storage practices are transparent and that adequate security measures are in place.

AI advancements such as ChatGPT and GPT-4 have the potential to revolutionize the way we work, live, and interact with each other. However, as with any new technology, there are both benefits and risks to consider. The benefits of AI include enhanced efficiency and productivity, improved personalization, better decision-making, improved healthcare outcomes, and increased safety and security. At the same time, the risks of AI include job displacement, bias and discrimination, privacy concerns, lack of accountability, and security risks. To ensure that AI technology is developed and deployed responsibly, it is essential to prioritize transparency, accountability, and security, as well as to regularly assess and mitigate potential risks. By doing so, we can unlock the full potential of AI while minimizing its potential harms.

As AI technology continues to advance, it is essential to address the risks and benefits associated with it. While AI can provide numerous benefits, such as increased efficiency and productivity, it can also pose risks such as job displacement, bias and discrimination, and privacy concerns. To ensure that AI is developed and deployed responsibly, it is necessary to prioritize transparency, accountability, and security in its use.

Moreover, it is also important to involve a wide range of stakeholders, including policymakers, industry leaders, researchers, and the general public, in discussions about the development and deployment of AI. By working together, we can ensure that AI technology is developed in a way that benefits society as a whole and minimizes potential harms.

The advancements in AI technology such as ChatGPT and GPT-4 have the potential to bring numerous benefits to society, including improved efficiency, productivity, and decision-making. However, as with any new technology, it is essential to address potential risks such as job displacement, bias, and discrimination, and privacy concerns. By prioritizing transparency, accountability, and security in the development and deployment of AI, we can ensure that AI technology is used responsibly to benefit society.

In addition, it is important to address ethical concerns related to the use of AI. The development and deployment of AI systems should be guided by ethical principles such as fairness, accountability, and transparency. This requires careful consideration of the potential impact of AI systems on individuals and society as a whole, as well as the development of frameworks and standards for responsible AI development and deployment.

One of the biggest concerns with AI is the potential for bias and discrimination. AI systems are only as unbiased as the data that is used to train them. If the data used to train AI models is biased or unrepresentative, then the resulting AI system will also be biased. This can lead to discrimination against certain groups of people and perpetuate existing social inequalities.

To address this issue, it is important to ensure that AI systems are trained on diverse and representative data sets. In addition, AI systems should be regularly audited to ensure that they are not exhibiting bias or discrimination. Finally, it is important to establish clear standards for the use of AI in decision-making processes, to ensure that AI systems are not used to perpetuate discrimination or unfairly disadvantage certain groups of people.

Another concern with AI is the potential for job displacement. As AI technology becomes more advanced, there is a risk that many jobs may become automated, leading to significant job losses. While it is true that AI has the potential to make many tasks more efficient and cost-effective, it is important to consider the impact of these changes on the labor market.

To mitigate this risk, it is important to invest in training and education programs that can help workers develop the skills they need to succeed in a world where AI is increasingly prevalent. In addition, policymakers should consider implementing measures such as universal basic income or job guarantees to ensure that workers are not left behind by the rapid pace of technological change.

Finally, AI also raises concerns around privacy and security. As AI systems become more advanced and are used to process more and more personal data, it is important to ensure that this data is protected from unauthorized access and use.

To address this issue, it is important to establish clear standards and regulations around the collection, use, and storage of personal data. In addition, AI systems should be designed with security and privacy in mind, with appropriate safeguards and encryption measures in place to protect sensitive data.

While AI has the potential to bring many benefits to society, it is important to address potential risks and concerns associated with its development and deployment. By prioritizing transparency, accountability, and security, and by involving a wide range of stakeholders in discussions about AI, we can ensure that AI technology is developed and deployed responsibly, to benefit society as a whole.

It is also important to consider the potential long-term impacts of AI on society. As AI technology becomes more advanced, there is a risk that it may become too powerful or too complex for humans to fully understand or control. This could lead to a range of potential risks, from unintentional harm caused by AI systems to the possibility of AI systems taking over decision-making processes from humans.

To address these concerns, it is important to prioritize research into AI safety and ethics. This includes exploring ways to ensure that AI systems remain aligned with human values and goals, and developing mechanisms to prevent AI systems from causing unintended harm. Additionally, it is important to establish clear ethical principles and standards for the development and deployment of AI systems, to ensure that they are developed in a way that is consistent with human values and goals.

Finally, it is worth noting that AI technology is still in its early stages of development, and it is difficult to predict exactly how it will impact society in the long term. As such, it is important to remain vigilant and to continue to monitor the development of AI technology, in order to address potential risks and maximize its potential benefits.

In conclusion, the development of AI technology such as ChatGPT and GPT-4 has the potential to bring numerous benefits to society, from improved efficiency and productivity to better decision-making. However, it is important to address potential risks and concerns associated with the use of AI, including the potential for bias and discrimination, job displacement, privacy and security concerns, and long-term risks related to the power and complexity of AI systems. By prioritizing transparency, accountability, and security, and involving a wide range of stakeholders in discussions about AI, we can ensure that AI technology is developed and deployed responsibly, to benefit society as a whole.

Hockey’s Jadoogar – Dhyan Chand

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major dhyan chand
Major Dhyan Chand

Dhyan Chand popularly known as hockey’s jadoogar. Dhyan Chand was born on 29th August, 1905 at Allahabad. His father was in the British Indian army.

Memorable incident

He started playing Hockey with his friends who used to themselves make Hockey sticks from tree branches and balls from ragged clothes. At the age of 14 years he visited a Hockey match with his father, where one team was down by 2 goals. He insisted his father to play from the losing side, and when an Army Officer let him do so, Dhyan scored 4 goals for the team. Impressed by his skills, the Officer offered him to join the army.

Turning point

Dhyanchand joined the army at the age of 16 in the year 1922 and took serious to hockey, this proved a turning point of his carrier. Subedar-Major Bhole Tiwari of Brahmin Regiment became Dhyan’s mentor inside the Army and taught him the basics of the game. Pankaj Gupta was the first Coach of Dhyan Singh who predicted that one day he would shine like the Moon, called Chand in Hindi. Hence, Dhyan Singh came to be known as Dhyan Chand. After that Dhyanchand rose in the hockey field like a meteor. This became an important milestone of his carrier. In the year 1926, he was selected for the Indian hockey team slated to tour New Zealand.

As soon as Dhyan Chand joined the army, his tryst with hockey began. After that there was no looking back for this magician of Indian hockey, popularly known as hockey’s jadoogar. His exciting stick-work encouraged the army to allow him to concentrate on the game. Dhyan Chand took part in the inter-provincial hockey championship and made an immediate impact on the national hockey scene. From the very outset Dhyan Chand showed a lot of promise and the day was not far away when he joined the ranks of the Indian hockey.

Monumental role

In the year 1934, Dhyan Chand was appointed the captain of the Indian hockey and subsequently captained the gold winning team at the Berlin Olympics in 1936. At the age of 43, he led the hockey team to the tour of East Africa in 1947. In this tour Dhyan Chand scored 61 goals in 21 matches that India played. After an illustrious carrier of 30 years, Dhyan Chand bid adieu to international hockey in 1949. He retired as Major and was also the Chief Hockey Coach at the National Institute of Sports. For his extraordinary achievements, the Indian government awarded him the Padma Bhusan in 1956. Throughout his carrier, He scored over 1000 goals in his career, from 1926 to 1948 .

Achievements

Players like Dhyanchand become a synonym of the game; he is not a hero; he has become the parameter of hockey by which other player’s caliber is measured. Dhyan Chand helped India in winning gold medals in hockey in 3 successive Olympics games- Amsterdam Olympics (1928), Los Angles Olympics (1932) and Berlin Olympics (1936). He was the captain of the gold medal winner Indian Hockey team in the historic 1936 Berlin Olympics. Dhyan Chand scored 101 goals at the Olympic Games and 300 goals in other international matches. Dhyan Chand’s birthday (Aug 29) is observed as the national sports day. The Indian Postal Service issued a postage stamp in his memory, and the Dhyan Chand National Stadium at New Delhi has been named after him.

However, the last days of Dhyan Chand were not very happy, as he was short of money and was badly ignored by the nation. Once he went to a tournament in Ahmedabad and they turned him away not knowing who he was. He developed liver cancer, and was sent to a general ward at the AIIMS, New Delhi. He died on the 3rd of December 1979.

Dhyan Chand
Major Dhyan Chand