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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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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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Serverless Computing: Revolutionizing Application Development in the Cloud

Serverless computing is a cloud computing execution model where the cloud provider dynamically manages the allocation and provisioning of servers. In this model, developers can focus solely on writing code without worrying about the underlying infrastructure. This approach is revolutionizing application development in the cloud by offering several advantages and introducing new paradigms. Traditionally, developers had to manage servers, virtual machines, and containers to deploy and run their applications. This required expertise in infrastructure management, capacity planning, and scaling. However, with serverless computing, developers no longer need to provision or manage servers. Instead, they can upload their code to a cloud platform, which automatically handles the execution, scaling, and maintenance of the application. One of the key benefits of serverless computing is its scalability. Applications can automatically scale up or down based on demand, ensuring optimal performance a...

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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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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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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 : ...

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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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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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Javascript interview questions and answers with code

To start a series for the JavaScript interview questions which may help junior to mid level developers. Common JavaScript interview questions with examples. 1. What is let and const in JavaScript? » Let and const are block-scoped declarations in JavaScript, used to declare variables. let allows you to reassign the value of the variable, while const creates a read-only reference to a value. Example: let message = "Hello, World!"; message = "Hello, JavaScript!"; console.log(message); // Output: "Hello, JavaScript!" const PI = 3.14; PI = 3.14159; // TypeError: Assignment to constant variable. 2. What is arrow function in JavaScript? » Arrow functions are a shorthand for anonymous functions in JavaScript. They are also known as “fat arrow” functions. Example: let add = (a, b) => a + b; console.log(add(1, 2)); // Output: 3 let numbers = [1, 2, 3, 4, 5]; let doubledNumbers = numbers.map(num => num * 2); console.log(doubledNumbers); // Output: [2, 4, 6, ...

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Cloud Security Challenges and Encryption, Identity Management, and Compliance

Cloud Security Best Practices: Addressing Key Challenges and Solutions Cloud computing has transformed the way businesses operate, providing scalable resources, cost-efficiency, and flexibility. However, as organizations increasingly move critical workloads to the cloud, ensuring robust security becomes paramount. Below, we explore key cloud security challenges and best practices to address them, focusing on encryption , identity management , and compliance . 1. Encryption: Protecting Data at Rest and in Transit Challenges: Data breaches are among the top concerns in cloud environments. Sensitive information stored in the cloud is vulnerable to unauthorized access, both at rest and during transmission. Ensuring the integrity and confidentiality of data requires robust encryption mechanisms. Best Practices: Encrypt Data at Rest: Use strong encryption algorithms such as AES-256 for data stored in cloud storage. Cloud service providers (CSPs) often offer server-side encryption, ...

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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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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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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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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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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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Java Multithreading: Concurrency and Parallelism

Java Multithreading: Concurrency and Parallelism are essential concepts in modern software development, particularly in Java, a language known for its robust support for concurrent programming. In this article, we'll explore the fundamentals of multithreading in Java, focusing on concurrency and parallelism. 1. Concurrency vs. Parallelism: - Concurrency: Concurrency is the ability of a program to execute multiple tasks simultaneously, seemingly overlapping in time. In Java, concurrency is achieved through threads. Threads allow different parts of a program to execute independently. - Parallelism: Parallelism, on the other hand, involves executing multiple tasks simultaneously, utilizing multiple CPU cores to speed up the computation. While concurrency deals with managing tasks, parallelism focuses on executing tasks concurrently on multiple processors. 2. Threads in Java: - In Java, threads are represented by instances of the `Thread` class or by implementing the ...

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Neuralink’s Brain Computer Interface Understanding First in Human Trials and Future Applications

1. What Is Neuralink’s Brain Computer Interface? Neuralink’s core technology is the N1 implant : a coin sized, wireless device embedded flush with the skull, connected to the brain via up to 96 ultra-thin polymer “threads” carrying over a thousand electrodes. These electrodes record neural spikes and can stimulate specific brain regions. A custom surgical robot places the threads with micron-scale precision, minimizing tissue damage. The implant streams neural data over Bluetooth to an external receiver and is powered wirelessly, eliminating bulky batteries. 2. Timeline of First-in-Human Trials May 2023: FDA grants an Investigational Device Exemption, greenlighting the first clinical trial after addressing safety concerns around batteries and wire migration. September 2023: Recruitment opens for the PRIME study , targeting participants with quadriplegia due to ALS or cervical spinal cord injury . January 2024: The first human patient, later revealed as 30 y...

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Serverless Computing: Revolutionizing Application Development in the Cloud

Serverless computing is a cloud computing execution model where the cloud provider dynamically manages the allocation and provisioning of servers. In this model, developers can focus solely on writing code without worrying about the underlying infrastructure. This approach is revolutionizing application development in the cloud by offering several advantages and introducing new paradigms. Traditionally, developers had to manage servers, virtual machines, and containers to deploy and run their applications. This required expertise in infrastructure management, capacity planning, and scaling. However, with serverless computing, developers no longer need to provision or manage servers. Instead, they can upload their code to a cloud platform, which automatically handles the execution, scaling, and maintenance of the application. One of the key benefits of serverless computing is its scalability. Applications can automatically scale up or down based on demand, ensuring optimal performance a...

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Comparative Analysis of File Systems: NTFS vs. FAT32 vs. exFAT in Operating Systems

File systems play a crucial role in organizing and managing data on storage devices within an operating system. In this comparative analysis, we'll explore three commonly used file systems: NTFS (New Technology File System), FAT32 (File Allocation Table 32), and exFAT (Extended File Allocation Table). We'll examine their features, advantages, limitations, and suitability for various use cases. NTFS (New Technology File System): NTFS is the default file system for modern Windows operating systems. It offers several advanced features, including: Support for large file sizes and partitions: NTFS can handle individual file sizes up to 16 exabytes and partitions up to 256 terabytes. File and folder permissions: NTFS supports access control lists (ACLs), allowing fine-grained control over who can access and modify files. Journaling: NTFS uses a journaling mechanism to track changes made to the file system, enhancing reliability and facilitating faster recovery in case of system cras...

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