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"We believe that a capture of Swift, an attempted capture of Swift, is very much in the cards."

Fenix Flexin is best known as a member of Shoreline Mafia, a rap duo from Los Angeles. But he's recently found solo success with the track "Rubberz," which has climbed to number 58 on the Billboard Hot 100. Almost immediately, though, questions were raised about the song's origins, with many speculating that it was largely, […]

The Social Media Victims Law Center accused the companies of creating addictive and dangerous platforms.

OpenAI's CEO seemed excited to share a "cool use case" for parents.

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A bootleg of Spider-Man: Brand New Day was up on X for over seven hours before eventually being pulled. During that time, it reached over 5.9 million accounts and accumulated over 143,000 likes. Other accounts have reposted the leaked film, but none have lasted particularly long, as Disney now seems to be on top of […]

Apple's CarPlay is a convenient way to listen to music or safely use navigation, but it can be a finnicky system that requires the occasional troubleshooting.

"A Heap doesn't stay useful because everything is sorted. It stays useful because every parent follows one simple rule." In the previous article, we learned that a Heap is built for continuous decision-making. Whether it's assigning the nearest driver, scheduling the next process, or selecting the most urgent support ticket, the system always needs one thing: The next best candidate But that raises an interesting question. How can a Heap always know the best candidate without sorting everything? The answer lies in one simple rule: The Heap Property. This single rule is what gives a Heap its power. The Biggest Misconception About Heaps Many beginners imagine a Heap like this. 100 95 90 82 76 64 51 Everything perfectly sorted. It feels logical. If the largest element should always come first, shouldn't every element be arranged in order? Surprisingly, no. A Heap solves a much smaller problem. It only guarantees that the best element is always easy to reach . Everything else only needs to follow one simple relationship. Imagine a Company Hierarchy Think about the structure of a company. CEO ↓ Engineering Director ↓ Engineering Manager ↓ Software Engineer The CEO doesn't directly manage every employee. Instead, each manager is responsible only for the people immediately below them. The entire organization works because every manager fulfills their local responsibility. A Heap works in a very similar way. Every node only needs to maintain the correct relationship with its immediate children. It doesn't need to know about every other node in the structure. The Heap Property Let's look at a Max Heap. 100 / \ 90 80 / \ / \ 75 60 70 50 Notice the pattern. Every parent has a value greater than or equal to its children. That's the Heap Property. Parent ≥ Children That's it. There is no rule saying that every node must be greater than every other node in the Heap. Only the parent-child relationship matters. What About a Min Heap? Some systems want the smallest value first. For

While struggling to understand channels in go, I would try out many things in my sandbox repository. I encountered deadlock errors and stuff about go routes being asleep. I came to understand that the order of execution played a role and that with unbuffered channels you need a sender and a receiver ready at the same time (kind of). I wrote a short article on my blog site about the experience The Unbuffered Channels In Go Lesson I Think Has Finally Clicked for Me 🤷🏽‍♂️

"A HashMap helps you find what you already know. A Heap helps you decide what should happen next." In the previous article, we discovered that not every software problem is about finding a specific object. Sometimes, the system already knows exactly what it's looking for. Find User ID = 1024 ↓ Return User Other times, the system doesn't know the answer in advance. Instead, it has to repeatedly answer questions like: Which task should run next? Which driver should be assigned? Which customer should be served first? Which alert is the most critical? These are fundamentally different problems. Instead of retrieving an object, the system is making a decision. This is where a Heap comes in. A Heap Is Built for Decisions, Not Searches Imagine you're managing a hospital emergency room. Patients keep arriving throughout the day. Patient A Minor Injury Patient B Heart Attack Patient C Broken Arm Patient D High Fever Should doctors treat patients in the order they arrived? Probably not. Instead, they ask one question. Who needs treatment first? Notice something important. The hospital isn't searching for a particular patient. It's choosing the highest-priority patient. A Heap is designed for exactly this kind of problem. A Different Way of Thinking When beginners hear "data structure," they often think about storing data. Experienced engineers think differently. They ask: "What operation does my system perform repeatedly?" If the answer is: Find User Find Order Find Product that's a lookup problem. But if the answer is: Choose Highest Priority Choose Nearest Driver Choose Earliest Deadline that's a decision problem. A Heap is optimized for continuous decision-making. What Exactly Is a Heap? A Heap is a data structure that keeps the most important element immediately available. Depending on the system, "most important" can mean different things. For example: Highest priority Lowest cost Earliest deadline Highest score Closest driver Most urgent ticket The Heap doesn't decide w

Welcome back to the React Mastery Series ! In the previous article, we explored React Rendering and Component Lifecycle . We learned: What causes a component to re-render How React reconciliation works The difference between rendering and DOM updates How lifecycle behavior is handled using Hooks Now let's learn how React applications respond to user interactions. Every modern application depends on events: Clicking buttons Typing into forms Selecting options Submitting data Dragging and dropping elements Keyboard shortcuts React provides a powerful event system to handle all these interactions. What is Event Handling? Event handling is the process of responding to user actions in an application. Examples: User Action | ↓ Event Triggered | ↓ Event Handler Executes | ↓ State Updated | ↓ UI Re-renders Example: A user clicks the "Transfer Money" button: Click Button | ↓ Handle Click Event | ↓ Validate Data | ↓ Call API | ↓ Update UI Events in Traditional JavaScript vs React Traditional JavaScript const button = document . getElementById ( " save " ); button . addEventListener ( " click " , saveData ); You manually: Find the DOM element Attach event listeners Manage updates React React attaches events directly inside JSX. < button onClick = { saveData } > Save </ button > React manages the event registration internally. React Event Syntax React events use: camelCase naming JSX expressions Function references HTML: <button onclick= "save()" > Save </button> React: < button onClick = { save } > Save </ button > Notice: onclick ❌ onClick ✅ Handling Click Events Example: function Button () { function handleClick () { console . log ( " Button clicked " ); } return ( < button onClick = { handleClick } > Click Me </ button > ); } When the user clicks: Click | ↓ handleClick() | ↓ Execute Logic Passing Functions vs Calling Functions A very common beginner mistake. Incorrect < button onClick = { handleClick () } > Save </ button > This executes immediately during rendering. Correc

The automaker is gearing up to make some big changes to its EV line in the near future. Here's what to expect.

"Finding something quickly and finding the best thing quickly are two completely different engineering problems." So far in this series, we've explored one of the most common behaviours in software systems: Fast lookup. Whenever a system already knows what it's looking for—a User ID, Product ID, Order ID or Session ID—a HashMap becomes an excellent choice. But not every software problem works this way. Imagine you're building a ride-sharing application. A rider requests a cab. The system doesn't already know which driver to assign. Instead, it must answer a different question: "Out of all available drivers, who is the best choice?" Now consider a task scheduler. Hundreds of jobs are waiting to run. The scheduler doesn't ask: "Find Job #123." It asks: "Which job should run next?" Or imagine a gaming platform. Thousands of players are competing. Nobody asks: "Find Player ID 1057." Instead, users ask: "Who are the top 10 players?" These problems are fundamentally different from fast lookup. They're not about finding a specific object . They're about finding the best object according to some priority. This shift in thinking introduces another important design behaviour. Fast Lookup vs Best Selection Let's compare two different requirements. Requirement 1 Customer ID = 1052 ↓ Retrieve Customer The system already knows exactly what it needs. The challenge is retrieving it efficiently. Requirement 2 Available Drivers ↓ Find Nearest Driver ↓ Assign Ride The system doesn't know the answer yet. It must compare multiple candidates before making a decision. These two behaviours may look similar. In reality, they solve completely different engineering problems. Every Software System Doesn't Search the Same Way Consider these questions. Find Order #50231 versus Find the highest priority order. Or: Retrieve Product ID = P1042 versus Recommend the most popular product. Or: Find Employee ID = 2107 versus Find the employee with the highest sales this month. The first question always

Christopher Nolan's impressionistic remix of Homer's epic poem finds the man behind the myth.

The Model Context Protocol is an open standard, introduced by Anthropic in November 2024, for connecting AI models to the tools, data, and systems they need to be useful. The easiest way to understand it is through the metaphor most people in the space now reach for: MCP is "USB-C for AI." Before USB-C, plugging a device into a computer meant hunting for the right proprietary cable. MCP solves the equivalent problem for AI — before it existed, every AI application that wanted to talk to an external tool (a database, a calendar, a codebase, a CRM) needed a custom, one-off integration built specifically for that pairing. That sounds like a minor inconvenience until you do the math. If you have ten AI applications and a hundred tools they might each want to use, the naive approach requires up to a thousand separate integrations — and every new tool or every new AI application multiplies that number further. Integration complexity was scaling quadratically just as the number of both AI agents and business tools was exploding. MCP replaces that tangle with a single, standardized interface: a tool built to speak MCP can be plugged into any MCP-compatible AI application, and an AI application that speaks MCP can reach any MCP server, without bespoke wiring in either direction. Structurally, MCP defines a client-server relationship. An "MCP server" exposes a set of capabilities — tools it can call, data it can retrieve, prompts it can offer — through a standardized protocol. An "MCP client," typically embedded in an AI application, discovers and uses those capabilities on the model's behalf. The protocol itself has kept evolving: its governance now sits with the Linux Foundation's Agentic AI Foundation, giving it a vendor-neutral home, and a new specification — covering a more stateless protocol core, formal extensions, long-running tasks, and hardened authorization — is set to finalize in late July 2026. Why Every AI Startup Is Talking About MCP The short answer is that MC

Welcome back to the React Mastery Series ! In the previous article, we learned about State in React and how state changes make our applications interactive. Today, we will understand one of the most important concepts for every React developer: How does React render components? Many developers know how to write React code, but understanding when and why React renders is what separates a beginner from an advanced React developer. A strong understanding of rendering helps you: Build faster applications Avoid unnecessary re-renders Debug performance issues Use optimization techniques correctly Let's dive in. What is Rendering in React? Rendering is the process where React: Takes your component code Creates a representation of the UI Updates the browser DOM when necessary A simple way to visualize it: Component Code | ↓ React creates Element Tree | ↓ Reconciliation Process | ↓ Browser DOM Update Rendering does not always mean updating the browser DOM . React may render a component, compare the result, and decide that no DOM changes are required. Initial Render When a React application starts, the first rendering process happens. Example: function App () { return ( < h1 > Hello React </ h1 > ); } The flow: index.html | ↓ main.tsx | ↓ <App /> | ↓ React creates UI | ↓ Browser displays content This is called the initial render . What Causes a Re-render? A component re-renders when: 1. State Changes Example: const [ count , setCount ] = useState ( 0 ); setCount ( 1 ); When state changes: State Update | ↓ Component Re-renders | ↓ UI Updates 2. Props Change Example: < User name = "Siva" /> If the parent changes: < User name = "John" /> The child component receives new props and re-renders. 3. Parent Component Re-renders When a parent component renders, React also re-renders its children by default. Example: function Parent () { return ( <> < Child /> </> ); } If Parent updates, Child also gets rendered again. Later, we will learn how React.memo can prevent unnecessary child re

Uber has partnered with — and in some cases made direct investments in — about 30 autonomous vehicle companies over the past two years. Here's the list and the latest on the partnerships.

If you've got a drawer or box full of old cables, here are some things you can do to thin them out. You don't need that many.

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A number of major Chinese smartphone makers have adopted silicon carbon batteries in their handsets, and now Samsung has embraced it in the new Fold lineup.