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React interviews questions and answers with code

React Interview Preparation: Best Questions, Best Answers, and Sample Code 1. What are the differences between functional and class components in React? Answer : Functional components are simpler and mainly focus on rendering UI, while class components provide more powerful features like state management and lifecycle methods . In recent versions of React, hooks ( useState , useEffect ) enable functional components to use state and lifecycle features without needing to be classes. // Functional Component function FunctionalComponent(props) { const [count, setCount] = useState(0); return ( <div> <p>Count: {count}</p> <button onClick={() => setCount(count + 1)}>Increment</button> </div> ); } // Class Component class ClassComponent extends React.Component { ...

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Future of Data Centers Sustainable Hyperscale Solutions

1. What are data centers and what does “ hyperscale ” mean? Data center: a facility housing compute servers, storage arrays, networking equipment, power distribution, cooling systems, and physical security all to run, store, and transmit digital workloads. They range from small server rooms to massive campuses. Hyperscale: describes a class of very large, standardized, automated data centers operated by major cloud providers or large enterprises. Hyperscale design emphasizes: Massive capacity (thousands to millions of servers across many sites), Standardized racks and modules for predictable deployment, Heavy automation for provisioning, monitoring, and failure handling, Economies of scale that reduce per-unit costs and enable rapid growth. Hyperscale facilities run the backbone of modern cloud services, streaming platforms, search, social media, and large AI model training . 2. Why sustainability is essential for data centers Scale of impact: As cloud use, stream...

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How Quantum Computing Will Revolutionize Technology

Quantum computing is on the verge of transforming the tech world as we know it. By 2025, this groundbreaking technology is expected to solve problems that were once thought unsolvable, thanks to its unique ability to process vast amounts of data at lightning speed. From healthcare to finance , the impact will be felt across multiple industries, reshaping how we approach complex challenges. While still in its infancy, the potential for quantum computing to revolutionize technology is immense, and the race is on to harness its power. Key Takeaways Quantum computing is set to revolutionize industries by 2025, offering solutions to complex problems that classical computers can't tackle. The technology leverages qubits , which can exist in multiple states, allowing for simultaneous processing of vast data sets. Key industries like healthcare, finance, and logistics will benefit from quantum computing, leading to faster drug discovery, improved financial modeling, and optimized su...

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Generative AI for Scientific Discovery How AI is accelerating breakthroughs

Quick hook. What if algorithms could propose a new drug candidate, predict a protein’s 3-D shape , and run thousands of experiments in an automated lab all in the time it would take a human team to run a few? That is not sci-fi. Generative AI is already part of real scientific workflows in 2025, and this guide explains how , why , what works , what doesn’t , and how you can learn and experiment with these tools. 1. Plain-language definition: what is “generative AI for science”? Generative AI are machine-learning models that create they generate text, images, molecular graphs, 3-D structures, or even experimental plans instead of only classifying or labeling. In scientific discovery these models are used to: propose new hypotheses, molecules or materials; predict structures and behavior (e.g., protein folding); design experiments and optimize conditions; run closed loops with robots that execute experiments and feed back results. These systems don’t replace sc...

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UPI 3.0: How BharatGPT Is Shaping the Next Wave of Digital Transactions

UPI 3.0 Voice Payments: How BharatGPT Drives India’s Digital Transaction Revolution | Atharv GFyan View Chapters ▾ × Table of Contents 1. Introduction to UPI 3.0 UPI 3.0 is the latest version … 2. What Are “Conversational Voice Payments”? “Conversational Voice Payments” let users … 3. Use Cases & Accessibility Visually impaired users … Elderly or first-time smartphone users … 4. Security & Compliance Voice biometrics vs. OTP/UPI PIN … 5. Merchant & Developer Perspectives How IRCTC, banks, and app builders … 6. Future Outlook Expected rollout phases and adoption targets … 7. Merchant Adoption Indian Railway Catering and Tourism Corporation … ...

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TinyML Tutorial 2025: Build Low Power AI Models with TensorFlow Lite Micro

Introduction In recent years, the convergence of machine learning (ML) and the Internet of Things (IoT) has given rise to Tiny Machine Learning (TinyML), a paradigm that enables on-device inference on resource-constrained microcontrollers and edge devices. TinyML shifts intelligence from centralized cloud servers to the very edge of networks, unlocking new possibilities in privacy, latency, and energy efficiency. This article provides a comprehensive, in-depth exploration of TinyML its origins, core frameworks, optimization techniques, real-world applications, challenges, and future directions designed as a standalone primer for developers, researchers, and technology enthusiasts. What Is TinyML? Historical Context and Definition TinyML is broadly defined as the practice of running ML models on microcontrollers and low-power embedded systems, typically operating in the milliwatt (mW) power range or below. Historically, ML inference required significant computational resources, rel...

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A Starter Guide to Data Structures for AI and Machine Learning

Data structures are fundamental concepts in computer science that help organize and store data efficiently. In the context of AI and machine learning, understanding data structures is crucial because these fields often deal with large volumes of data that need to be processed and analyzed quickly. Here's a starter guide to some key data structures relevant to AI and machine learning: Arrays : Arrays are one of the simplest data structures, consisting of a collection of elements stored in contiguous memory locations. In AI and machine learning, arrays are often used to represent datasets, input features, or output predictions. Lists : Lists are similar to arrays but more flexible because they can dynamically resize. In Python, for example, lists can grow or shrink as needed, making them useful for managing datasets of varying lengths. Stacks : Stacks follow the Last In, First Out (LIFO) principle, where the last element added is the first one to be removed. Stacks are commonly used ...

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Programming Languages for Building Operating Systems

Building an operating system is a complex and low-level task, and the choice of programming languages is critical. Here are some of the programming languages commonly used for building operating systems: 1. Assembly Language : Assembly is the lowest-level programming language and is often the primary choice for OS development. It allows for direct control over the hardware and provides a level of detail required for an OS. 2. C: C is widely used in OS development due to its efficiency, low-level system access, and portability. Many parts of popular operating systems, like the Linux kernel, are written in C. 3. C++: While less common than C, C++ is used in some modern operating systems. It offers additional features like object-oriented programming and can be used for certain parts of an OS. 4. Rust: Rust has gained popularity for OS development, particularly for its memory safety features and performance. It provides low-level control without some of the pitfalls of C ...

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Decentralized Stablecoins The Future of Stable Value in DeFi

Decentralized Stablecoins : The Future of Stable Value in DeFi | Atharv Gyan 1. Introduction to Stablecoins Stablecoins are a class of cryptocurrency designed to maintain a stable value by pegs to external assets most commonly fiat currencies like the U.S. dollar, but also commodities or other cryptocurrencies. They emerged to solve the extreme volatility that plagues Bitcoin and many altcoins, enabling crypto‑native applications (especially in DeFi) to transact, lend, borrow, and hedge with minimal price risk. Traditional stablecoins fall into four categories: Fiat‑Collateralized (e.g., USDC , Tether USDT) Commodity‑Backed (e.g., PAXG backed by gold) Crypto‑Collateralized (e.g., MakerDAO ’s DAI on Ethereum ) Algorithmic (e.g., Terra USD , Ampleforth’s AMPL) Decentralized stablecoins are those that avoid reliance on a central issuer meaning no...

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The Future of Augmented Reality

Augmented Reality (AR) is poised to revolutionize education by transforming the way students interact with content, making learning more engaging, interactive, and immersive. Here's a detailed examination of how AR can reshape various aspects of education: Immersive Learning Experiences 1. Enhanced Engagement AR can bring textbook content to life. For example, history students can explore ancient civilizations through interactive 3D models, while biology students can examine the human body in detailed, life-like layers. 2. Real-World Applications AR bridges the gap between theoretical knowledge and practical application. Engineering students can use AR to visualize and manipulate complex machinery, while medical students can practice surgical procedures in a risk-free virtual environment. Virtual Labs 1. Safe and Cost-Effective Traditional science labs require expensive equipment and materials, and safety can be a concern. AR provides virtual labs where students can conduct experim...

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React interviews questions and answers with code

React Interview Preparation: Best Questions, Best Answers, and Sample Code 1. What are the differences between functional and class components in React? Answer : Functional components are simpler and mainly focus on rendering UI, while class components provide more powerful features like state management and lifecycle methods . In recent versions of React, hooks ( useState , useEffect ) enable functional components to use state and lifecycle features without needing to be classes. // Functional Component function FunctionalComponent(props) { const [count, setCount] = useState(0); return ( <div> <p>Count: {count}</p> <button onClick={() => setCount(count + 1)}>Increment</button> </div> ); } // Class Component class ClassComponent extends React.Component { ...

Read Explanation ⨠

Generative AI for Scientific Discovery How AI is accelerating breakthroughs

Quick hook. What if algorithms could propose a new drug candidate, predict a protein’s 3-D shape , and run thousands of experiments in an automated lab all in the time it would take a human team to run a few? That is not sci-fi. Generative AI is already part of real scientific workflows in 2025, and this guide explains how , why , what works , what doesn’t , and how you can learn and experiment with these tools. 1. Plain-language definition: what is “generative AI for science”? Generative AI are machine-learning models that create they generate text, images, molecular graphs, 3-D structures, or even experimental plans instead of only classifying or labeling. In scientific discovery these models are used to: propose new hypotheses, molecules or materials; predict structures and behavior (e.g., protein folding); design experiments and optimize conditions; run closed loops with robots that execute experiments and feed back results. These systems don’t replace sc...

Read Explanation ⨠

UPI 3.0: How BharatGPT Is Shaping the Next Wave of Digital Transactions

UPI 3.0 Voice Payments: How BharatGPT Drives India’s Digital Transaction Revolution | Atharv GFyan View Chapters ▾ × Table of Contents 1. Introduction to UPI 3.0 UPI 3.0 is the latest version … 2. What Are “Conversational Voice Payments”? “Conversational Voice Payments” let users … 3. Use Cases & Accessibility Visually impaired users … Elderly or first-time smartphone users … 4. Security & Compliance Voice biometrics vs. OTP/UPI PIN … 5. Merchant & Developer Perspectives How IRCTC, banks, and app builders … 6. Future Outlook Expected rollout phases and adoption targets … 7. Merchant Adoption Indian Railway Catering and Tourism Corporation … ...

Read Explanation ⨠

Future of Data Centers Sustainable Hyperscale Solutions

1. What are data centers and what does “ hyperscale ” mean? Data center: a facility housing compute servers, storage arrays, networking equipment, power distribution, cooling systems, and physical security all to run, store, and transmit digital workloads. They range from small server rooms to massive campuses. Hyperscale: describes a class of very large, standardized, automated data centers operated by major cloud providers or large enterprises. Hyperscale design emphasizes: Massive capacity (thousands to millions of servers across many sites), Standardized racks and modules for predictable deployment, Heavy automation for provisioning, monitoring, and failure handling, Economies of scale that reduce per-unit costs and enable rapid growth. Hyperscale facilities run the backbone of modern cloud services, streaming platforms, search, social media, and large AI model training . 2. Why sustainability is essential for data centers Scale of impact: As cloud use, stream...

Read Explanation ⨠

TinyML Tutorial 2025: Build Low Power AI Models with TensorFlow Lite Micro

Introduction In recent years, the convergence of machine learning (ML) and the Internet of Things (IoT) has given rise to Tiny Machine Learning (TinyML), a paradigm that enables on-device inference on resource-constrained microcontrollers and edge devices. TinyML shifts intelligence from centralized cloud servers to the very edge of networks, unlocking new possibilities in privacy, latency, and energy efficiency. This article provides a comprehensive, in-depth exploration of TinyML its origins, core frameworks, optimization techniques, real-world applications, challenges, and future directions designed as a standalone primer for developers, researchers, and technology enthusiasts. What Is TinyML? Historical Context and Definition TinyML is broadly defined as the practice of running ML models on microcontrollers and low-power embedded systems, typically operating in the milliwatt (mW) power range or below. Historically, ML inference required significant computational resources, rel...

Read Explanation ⨠

The Future of Augmented Reality

Augmented Reality (AR) is poised to revolutionize education by transforming the way students interact with content, making learning more engaging, interactive, and immersive. Here's a detailed examination of how AR can reshape various aspects of education: Immersive Learning Experiences 1. Enhanced Engagement AR can bring textbook content to life. For example, history students can explore ancient civilizations through interactive 3D models, while biology students can examine the human body in detailed, life-like layers. 2. Real-World Applications AR bridges the gap between theoretical knowledge and practical application. Engineering students can use AR to visualize and manipulate complex machinery, while medical students can practice surgical procedures in a risk-free virtual environment. Virtual Labs 1. Safe and Cost-Effective Traditional science labs require expensive equipment and materials, and safety can be a concern. AR provides virtual labs where students can conduct experim...

Read Explanation ⨠

DSA to Development: A Complete Guide

Transitioning from a career in Data Structures and Algorithms (DSA) to software development can be a rewarding journey. Here's a complete guide to help you make the shift: Contents 1. Assess Your Current Skillset : - Evaluate your proficiency in DSA and coding skills. - Identify the programming languages you are comfortable with. 2. Choose a Development Path : - Decide whether you want to focus on web development, mobile app development, data science, or another area of software development. - Research the skills and technologies required for your chosen path. 3. Learn Programming Languages : - If you aren't already proficient, learn languages commonly used in your chosen field. For web development, this could be JavaScript, HTML, and CSS. 4. Version Control : - Understand version control systems like Git, which are essential for collaborative software development. 5. Build Projects : ...

Read Explanation ⨠

Programming Languages for Building Operating Systems

Building an operating system is a complex and low-level task, and the choice of programming languages is critical. Here are some of the programming languages commonly used for building operating systems: 1. Assembly Language : Assembly is the lowest-level programming language and is often the primary choice for OS development. It allows for direct control over the hardware and provides a level of detail required for an OS. 2. C: C is widely used in OS development due to its efficiency, low-level system access, and portability. Many parts of popular operating systems, like the Linux kernel, are written in C. 3. C++: While less common than C, C++ is used in some modern operating systems. It offers additional features like object-oriented programming and can be used for certain parts of an OS. 4. Rust: Rust has gained popularity for OS development, particularly for its memory safety features and performance. It provides low-level control without some of the pitfalls of C ...

Read Explanation ⨠

Decentralized Stablecoins The Future of Stable Value in DeFi

Decentralized Stablecoins : The Future of Stable Value in DeFi | Atharv Gyan 1. Introduction to Stablecoins Stablecoins are a class of cryptocurrency designed to maintain a stable value by pegs to external assets most commonly fiat currencies like the U.S. dollar, but also commodities or other cryptocurrencies. They emerged to solve the extreme volatility that plagues Bitcoin and many altcoins, enabling crypto‑native applications (especially in DeFi) to transact, lend, borrow, and hedge with minimal price risk. Traditional stablecoins fall into four categories: Fiat‑Collateralized (e.g., USDC , Tether USDT) Commodity‑Backed (e.g., PAXG backed by gold) Crypto‑Collateralized (e.g., MakerDAO ’s DAI on Ethereum ) Algorithmic (e.g., Terra USD , Ampleforth’s AMPL) Decentralized stablecoins are those that avoid reliance on a central issuer meaning no...

Read Explanation ⨠

Quantum Computing and its real world applications

Quantum computing, a revolutionary advancement in computational technology, promises to solve problems that are beyond the capabilities of classical computers. This article will delve into the complexities of quantum computing, its real-world applications, and how it could reshape various industries. From finance to pharmaceuticals, artificial intelligence to cryptography, quantum computing has the potential to dramatically change the landscape of technology and human problem-solving. Table of Contents Introduction to Quantum Computing What is Quantum Computing? Key Concepts: Qubits, Superposition, and Entanglement How Quantum Computing Differs from Classical Computing Fundamental Principles of Quantum Computing Quantum Bits (Qubits) Superposition and Interference Quantum Entanglement Quantum Gates and Circuits Quantum Algorithms Shor’s Algorithm Grover’s Algorithm Quantum Error Correction The Future of Quantum Algorithms Quantum Hardware and Systems Types of Quantum Computers: Superco...

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