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Meta Data Breach 2025: What Was Stolen and Why It Matters

A massive data breach in early 2025 involving Meta and other major platforms exposed over 16 billion login credentials from more than 30 breached databases.
Stolen data includes accounts from platforms like Facebook, Instagram, Gmail, Snapchat, Roblox, government portals, and banking services, with a majority of the data being recent, intensifying the seriousness of the situation.
Cybercriminals obtained usernames, email addresses, plaintext passwords, session cookies, authentication tokens, metadata like IP addresses, device identifiers, browser fingerprints, and timestamps.
Experts recommend changing passwords on important accounts, avoid password reuse, enable two-factor authentication using apps or passkeys, monitor accounts for suspicious activity, and consider using a password manager.
This breach represents a significant cybersecurity threat with billions of up-to-date login records stolen, potentially impacting users of Facebook, Instagram, Gmail, and similar platforms.
Users are urged to take immediate action by changing passwords, implementing stronger authentication measures, and staying vigilant to reduce their exposure to the breach.

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Medium

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Andrej Karpathy Just Revealed the Biggest Shift in Software History (And It Changes Everything)

Andrej Karpathy, former Director of AI at Tesla and co-founder of OpenAI, revealed a major shift in software history.
Karpathy indicated that the current transformation in software is the most significant since the invention of programming itself.
The revelation in his latest talk is not just altering software development but also changing the rules of technology creation and possibilities.
This shift blurs the lines between human intention and digital execution.
Karpathy's framework divides the history of software into three eras, each marking a fundamental change in how computers are instructed.

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Dev

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My Experience with Hyperlane（1750424727496500）

Hyperlane is a high-performance, lightweight, and developer-friendly Rust Web framework, emphasizing speed and modern development.
It boasts impressive benchmark results, outperforming other popular frameworks in both wrk and ab tests.
Hyperlane offers thoughtfully designed abstractions like Context and streamlined route macros, making coding more intuitive.
The middleware onion model provides efficient request processing and clear middleware sequencing.
WebSocket support in Hyperlane is well-defined, allowing for effortless real-time chat implementation.
Dynamic routing with regex parameters adds flexibility, reducing the need for manual parsing.
Performance testing showed Hyperlane's exceptional speed, outperforming Gin in QPS.
Evolutionary improvements in Hyperlane versions have addressed issues and enhanced functionality.
Hyperlane's balance between performance and ease of use makes it ideal for student developers and newcomers to Rust.
The author recommends Hyperlane for Rust web projects, highlighting its enjoyable coding experience and reliability in deployment.

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Medium

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Navigating Through C++ maps: An In-Depth Guide

C++ map is an essential data structure for efficient data management and access.
This article provides an in-depth guide on C++ maps, covering mechanics, applications, and best practices.
A map in C++ stores elements as key-value pairs, allowing fast data retrieval based on the key.
Each element in a map is uniquely identified by its key, preventing data duplication.
Elements in a C++ map are automatically arranged in a specific order, usually ascending, based on the key.
The ordering of elements in maps enables quick data retrieval and organized storage.
Maps offer a more flexible and dynamic data access compared to arrays.
Understanding C++ maps is beneficial for both beginners and experienced programmers.
This comprehensive guide enhances skills in utilizing map C++ effectively in coding.
C++ maps are efficient for applications that require associative arrays or dictionary-like functionality.
The structured organization of data in maps aids in optimized data retrieval and management.
Maps in C++ are commonly used in scenarios where data lookup speed is crucial.
Regular practice with C++ maps can improve programming proficiency and data handling skills.
Incorporating map C++ can lead to more streamlined and robust code implementations.
The article delves into the nuances of map C++, suitable for developers aiming to elevate their programming abilities.
Exploring and mastering map C++ can significantly benefit programming projects and software development.
The guide serves as a resource for maximizing the potential of map C++ in various programming tasks.

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Dev

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💥 C# for Newbies: A Solid Start or a Trap in Disguise?

Choosing a first programming language, like C#, is comparable to picking a starter Pokémon, sparking varied opinions.
Recent discussions have questioned whether C# is truly beginner-friendly or if it only appears so initially.
A narrative highlights a designer turned developer's dilemma of starting with Python or the more 'serious' C#.
C# is noted for its modernity, readability, and versatility, utilized in enterprise apps, game development, and web projects through .NET.
Pros of commencing with C# include robust typing, valuable tooling like Visual Studio, diverse job opportunities, and a supportive community.
However, downsides encompass verbosity, complexity in setting up .NET, challenging error messages, and early exposure to abstract concepts.
A personal anecdote illustrates a developer's initial struggle with C# compared to more immediately intuitive languages like JavaScript.
Exploring JavaScript initially for faster feedback, the developer later returned to C# and found a quicker grasp of the language.
In conclusion, C# is likened to learning to drive in a Tesla—advanced features that may seem overwhelming for beginners but offer scalability for career growth.
While C# can feel daunting for newcomers, the language's scalability and potential make it an investment for those willing to navigate initial challenges.

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Dev

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Health Check setup for .NET application

A Health Check is an indicator of service availability in web applications, showing if the application is Healthy, Degraded, or Unhealthy.
It is often used in Continuous Deployment pipelines to monitor service status and restart if necessary.
To set up a basic health check in a .NET application, you need to register a health check and add a middleware with a defined path.
By default, the /health endpoint will return 200 OK with 'Healthy' as long as the application starts.
Custom health checks can be implemented by using the IHealthCheck interface and then registering them accordingly.
There are various extensions available for databases, message brokers, system info checks, and UI tools for monitoring.
Practical uses of health checks include UI dashboards, Kubernetes/Docker Health Probes, and integration with monitoring tools like Application Insights or Grafana.
Implementing health checks helps ensure service availability and prompt issue detection.

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Dev

287

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Glitch Runner: A Platformer Game with Dynamic Glitch Mechanics Made with Amazon Q CLI

Glitch Runner is a 2D platformer game created using Python, Pygame, and Amazon Q CLI.
The game introduces dynamic glitches that challenge players to adapt to changing situations.
Prompting techniques were used to develop the game's core mechanics and features.
Features were broken down into smaller tasks to improve efficiency.
Iteration with feedback helped in refining game elements like visual effects and gameplay difficulty.
Debugging was carried out using a problem-solution format to address issues like character floatation.
Amazon Q demonstrated modularity by breaking down game components into reusable modules.
AI-generated solutions included functions for screen shake and gravity reversal glitches.
The development process showcased how AI can enhance game creation workflows.
Smart prompts saved time by automating tasks like sprite animation states and audio event wiring.
Glitch Runner's design and gameplay were shaped by the prompt-driven development process.
The project on Github offers the opportunity to experience the game's unique glitch mechanics.

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Dev

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CSE Specializations Explained: AI, Data Science, Cybersecurity & Beyond

Computer Science and Engineering (CSE) at Solamalai College of Engineering offers specializations in Artificial Intelligence (AI), Data Science, Cybersecurity, and more.
Specializations like AI focus on machine learning, neural networks, NLP, and computer vision, leading to opportunities in healthcare, finance, and robotics.
Career paths in AI include AI Engineer, Machine Learning Developer, Data Scientist, and NLP Engineer.
Data Science at Solamalai involves data mining, Python, big data technologies, statistical analysis, and predictive modeling, preparing students for roles like Data Analyst and Business Intelligence Developer.
Cybersecurity specialization covers ethical hacking, cryptography, secure software development, and prepares students for roles like Security Analyst and Ethical Hacker.
Cloud Computing specialization focuses on AWS, Azure, Google Cloud, and offers career paths like Cloud Engineer, Cloud Architect, and DevOps Engineer.
Full Stack Development at Solamalai covers HTML, CSS, JavaScript, React, backend development, database management, and prepares students for roles like Full Stack Developer and Web Developer.
Hands-on experience, industry tie-ups, internships, and technical clubs at Solamalai help students explore and excel in their chosen specialization.
Faculty support, guest lectures, workshops, and innovation cells assist students in understanding and selecting the right specialization aligned with their interests.
Exploring specializations beyond the core CSE subjects equips students at Solamalai to chart successful careers in tech.

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Dev

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🏷️ A Practical Guide to TypeScript Custom Types for QA Automation

The article delves into using custom types in TypeScript for QA automation, focusing on creating robust, self-documenting, and error-resistant test frameworks.
Topics covered include defining union and string literal types for precise variable definitions, using type aliases to name data structures effectively, and leveraging interfaces to define object contracts.
It explains the distinctions between type aliases and interfaces, highlighting when to use each in QA automation scenarios for API payloads, response models, or Page Object Models.
The article also discusses extending interfaces for creating consistent API response models and using type assertions like 'as' and '!' for type safety and control over data shapes.
While emphasizing the benefits of custom types for bug prevention and code clarity, the article presents a challenge to apply the concepts learned by defining custom types for a product payload and response, and ensuring type safety.

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Dev

1.3k

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Trust Over Throttle: Leveraging o3-Pro for Accurate, Impactful AI

o3-pro model prioritizes reliability and accuracy over raw speed, reducing hallucinations and enhancing depth of reasoning.
Clients report 40–60% better ROI by prioritizing accurate AI outputs.
Strategic model routing: utilize lighter models for simple queries and o3-pro for complex analyses.
Cost vs. value: paying a premium per token for o3-pro can save on error-handling and rework costs.
Enterprises are advised to focus on consistent, trustworthy AI outputs rather than chasing speed records.
Three pillars of model selection for enterprise AI: consistent accuracy, cost-effective inference, and domain-specific solutions.
Comparison between o3-pro and lighter models in terms of hallucination rate, depth of reasoning, latency, cost per token, and ideal use cases.
Real-world ROI: organizations see 40–60% higher ROI on AI investments, reduced support costs, and improved stakeholder confidence with reliability-first approach.
Scenario-based recommendation: choose lighter models for real-time interactions, simple chatbots, and high-volume classification tasks.
Focus on strategy, reliability, cost efficiency, and domain alignment for sustainable gains in AI implementation.

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Analyticsindiamag

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AI Models from Google, OpenAI, Anthropic Solve 0% of ‘Hard’ Coding Problems

A new research study reveals that AI models from Google, OpenAI, and Anthropic have not been able to solve any 'Hard' coding problems, scoring 0%.
The study by multiple universities identified shortcomings in existing coding benchmarks and introduced the LiveCodeBench Pro to evaluate models with challenging problems.
Models excelled in knowledge-heavy and logic-heavy problems but struggled with observation-heavy challenges that require novel insights.
The AI models often made errors related to algorithms, showing room for improvement even with multiple attempts.
Despite claims of surpassing elite humans, the models still lag significantly in tasks demanding unique solutions.
Another analysis by Oxford researcher Toby Ord suggests that AI agents have a declining success rate over longer tasks, posing a challenge for handling complex coding projects.
While AI agents show improvements in handling longer tasks, achieving high-reliability performance still requires significantly shorter task durations.
The timeline for AI to effectively manage intricate coding tasks remains uncertain despite advancements in AI capabilities.
A detailed technical report is available for in-depth information on the research findings.
The article delves into the struggles of AI models in tackling complex coding challenges, emphasizing the need for improvement in reasoning and problem-solving capabilities.

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Medium

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However bash I delete untracked section information from the actual running actor?

Git provides interactive deletion of untracked files to allow users to preview and exclude affected data before actually deleting.
Using the --dry-run option before the actual deletion helps in understanding the changes without executing the operation.
The git clean command with flags like -d can be used to handle bare folders alongside files.
Conditional expressions are essential in programming for decision-making within code.
Python offers a ternary conditional operator for concise conditional assignments.
The ternary conditional operator syntax in Python is value_if_true if condition else value_if_false.
Implementing conditional expressions in Python using the ternary operator simplifies code and improves readability.
Overusing or nesting multiple ternary operators can lead to code that is difficult to read and understand.
Balancing conciseness and readability is key when using the ternary operator in Python.
Python's ternary conditional operator is particularly useful for basic conditional assignments and situations where brevity is essential.
Knowing how to use Python's ternary operator correctly contributes to writing efficient and maintainable code.

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Medium

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AWS Summit Stockholm: Learning from the Leaders in AI

Companies like Booking.com have deeply integrated AI into their products and development processes.
Attendees at AWS Summit Stockholm learned from industry leaders about AI integration.
A demo of Amazon Q Developer operational investigations was presented at the summit.
Amazon Q can automatically investigate alarms and provide key observations for issue investigation.
The feature helps users understand why an alarm was triggered by highlighting key information.
Users can review services inspected, information discovered, and suggestions to fix the issue.
In some cases, runbook suggestions in Systems Manager can resolve issues automatically.
Users are advised to carefully review suggestions before execution.
As models behind detection/resolution get smarter, developers can save time investigating root causes.

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Dev

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CodePen #Challenge: Visualizing McDonald’s Menu with Free Pivot Grid Library 👩🏼‍💻📊🍔

A Software Engineering student and beginner developer created a blog to share their learning journey and participation in #CodePenChallenges.
CodePen Challenges provide a platform to experiment with new technologies and develop professional skills by creating animations, webpages, mini games, etc.
The student participated in a recent challenge focused on food and decided to visualize data from the McDonald's Menu - Comparative Nutrition Values dataset.
WebDataRocks, a free pivot grid library, was used as the main tool to create interactive pivot tables with customization options.
The student shared their workflow for the challenge, starting with loading the dataset and filtering selected categories in the JavaScript pivot grid.
By filtering the dataset before loading, only specific categories like Breakfast, Beef & Pork, and Chicken & Fish were displayed.
The student customized the layout of the pivot table to show sub-levels of hierarchies in separate columns, resembling Excel.
In terms of styling, the student imported the 'Quicksand' font and added burger emojis as the background for better visual appeal.
WebDataRocks offers built-in themes, and the student used the orange theme to enhance the appearance of the pivot table.
The student shared the demo of their pivot table example resulting from the challenge for others to try out and evaluate.
Feedback and questions regarding adding a JS pivot table to web applications are welcomed by the student.

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Medium

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How to Create a Spring Boot Project from Scratch

To create a Spring Boot project from scratch, visit start.spring.io.
Choose the project type (Maven or Gradle), language (Java, Kotlin, or Groovy), and Spring Boot version.
Fill in project metadata like group, artifact, etc.
Select packaging type as JAR and Java version matching your setup.
Add dependencies to your project from the right-hand section.
Generate the project which will download a .zip file containing your project.
Unzip the downloaded file and open it in your preferred IDE like IntelliJ IDEA, Eclipse, or VS Code.
Upon opening the project in your IDE, you will see a pom.xml file with project configuration.
Run the project in your IDE or use 'mvn spring-boot:run' command to start the Spring Boot app on http://localhost:8080.
By following these steps, you'll have a basic Spring Boot project ready to build REST APIs, connect to databases, and more.
Consider creating your first REST endpoint or setting up database connections using Spring Data JPA as the next steps.

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