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Best AI Software to Help You Earn Up to $100 Daily: A Humanized Approach to Making Money with AI

ChatGPT can be used for writing blog posts, social media content, and more to earn money on platforms like Upwork and Fiverr.
Jasper AI is ideal for creating marketing copy and ads, offering opportunities to earn through copywriting services.
Teachable allows for the creation and selling of online courses with the help of AI tools, offering a passive income stream.
Platforms like Fiverr and Upwork provide opportunities to offer various services using AI tools for tasks like design, transcription, and coding.
Amazon Mechanical Turk offers microtask jobs where AI tools can assist in completing tasks efficiently to reach $100 a day.
AI-driven platforms like Trade Ideas and CryptoHopper can aid in stock trading, potentially earning over $100 a day with a solid strategy.
Survey sites powered by AI like Swagbucks and Prolific can help you earn money by completing tasks based on preferences and demographics.
AI has revolutionized earning opportunities, emphasizing the importance of consistency, creativity, and leveraging AI tools effectively.
Success in earning through AI requires a combination of effort, trial and error, and utilizing AI as a tool to enhance existing skills.
Strive for consistency and creativity while using AI tools to explore new income streams and boost productivity in the digital age.

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Medium

219

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Please Go. You Can Stay.

An employee shares their experience of being laid off in a confusing manner by their company.
The company wanted to keep two senior developers to transfer to another company, but offered uncertainty about their future job security.
The employee was offered a severance package and had mixed feelings about finding a new job.
The employee also had to train their replacement before receiving the severance payout.

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Medium

434

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Open Source Products — It’s Time

Applying open source methods can revolutionize various industries, not just software.
NodeCosmos offers a holistic view of product components and processes, organizing them into transparent chunks.
Using branches in NodeCosmos allows for collaborative contributions, ensuring continuous improvement.
Open models foster inclusivity, empowering unexpected sources of insights, and future-proof projects in a rapidly evolving world.

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Dev

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Understanding Azure Resource Groups: A Comprehensive Guide

Azure Resource Groups in Microsoft Azure serve as logical containers for organizing and managing related cloud resources within the Azure Resource Manager framework.
Resource groups play a crucial role in centralizing control over resources like virtual machines, storage, databases, and networking elements.
They enable simplified tasks such as deployment, access control, cost tracking, and lifecycle management by grouping resources together.
Resource groups debuted with Azure Resource Manager in 2014, providing a structured way to manage cloud assets through templates and declarative frameworks.
They offer logical resource association, hierarchical management scope, cross-region flexibility, metadata storage, and support for Infrastructure as Code (IaC).
Advantages of Azure Resource Groups include centralized management, granular cost visibility, RBAC enforcement, lifecycle-based governance, and operational flexibility.
Best practices for managing resource groups involve structured naming conventions, resource grouping alignment, metadata tags utilization, workload isolation, IaC implementation, RBAC enforcement, and regional compliance consideration.
Common use cases for Azure Resource Groups include application deployment, environment segregation, cost allocation, disaster recovery, and high availability strategies.
Resource groups function as a strategic framework for structuring and efficiently managing cloud resources, ensuring cost optimization, access control, and compliance.
Mastering Azure Resource Groups is essential for maximizing cloud efficiency, security, and scalability within the Azure ecosystem as cloud computing evolves.

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Dev

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Efficiently handle large datasets, huge files and data streams with PHP generators

Handling large files or data streams in PHP can be challenging without efficient methods like generators.
Comparing the memory-intensive array approach to the memory-efficient PHP Generators for processing large files.
Loading entire files into arrays can lead to high memory consumption and errors, especially for large files.
Generators in PHP allow processing one row at a time without storing the entire dataset in memory.
Generators yield values on-demand, making them ideal for handling huge files or infinite sequences.
Generators offer lower memory usage, improved performance, lazy evaluation, scalability, and work well with infinite sequences.
Best suited for handling large files, streaming data, processing huge datasets efficiently, and generating large sequences.
Generators are not suitable for random access, multiple data processing, sorting, filtering, or advanced operations on the entire dataset.
Generators are recommended for memory-efficient processing in PHP projects, providing benefits in efficiency, performance, and scalability.
Using generators can be a game-changer for handling large datasets and data streams effectively in PHP.

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Dev

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Why I’m Betting on Web Components in 2025

Modern frontend development is fragmented with various frameworks and UI libraries, making it tiresome to rebuild UI components each time.
The author is betting big on Web Components, which are suite of native browser technologies that allow creation of custom, reusable HTML elements that work with any frontend tech.
Web Components face challenges like styling, framework friction, learning curve, and lack of tooling. However, modern advancements have addressed many of these issues.
Web Components offer advantages such as cross-framework compatibility, future-proofing, isolation, interoperability, and performance, making them suitable for micro frontends and polyglot stacks.

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Medium

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Understand More Search Tuning (SPLK-1004 exam preps)

Splunk heavy forwarders can filter and route event data based on various criteria, including event metadata like source, source type, or event patterns.
Routing can be configured through props.conf, transforms.conf, and outputs.conf files, with the ability to index data locally before forwarding or perform selective indexing.
Splunk's search processing language (SPL) supports Boolean operators: AND, OR, NOT, and XOR.
Exclusion searches using NOT tend to be less efficient than inclusive ones.

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Dev

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Stopping the Stream: A Pythonic Guide to Controlling OpenAI Responses

This article discusses a practical approach to providing users with control over stopping AI-generated responses.
The challenge is to stop the stream mid-generation without disrupting the entire application.
The solution involves implementing a StreamController class and an AIResponseGenerator class.
The implementation allows for stopping the stream and includes pro tips for performance and error handling.

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Dev

443

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Python vs. C for Microcontrollers — Which One Wins?

Python with MicroPython and CircuitPython is challenging the dominance of C in embedded systems by offering simplicity and readability.
C excels in performance with compiled code, running faster than Python, crucial for real-time systems.
Python, though interpreted, provides faster development cycles and acceptable latency for many embedded applications.
In memory usage, C offers granular control, allowing for efficient usage in constrained environments.
MicroPython and CircuitPython typically require less memory overhead than C variants, making Python more memory-efficient.
Python enables rapid prototyping and quick iteration, cutting development time by 40–60% compared to C.
Python's readability and community support make maintenance easier, especially in collaborative or educational projects.
C is suitable for real-time systems, low-level hardware interfacing, and resource-constrained devices.
Python is ideal for rapid prototyping, educational projects, and IoT applications with rich libraries.
Hybrid models combining Python for high-level logic and C modules for critical routines are gaining traction in embedded development.

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Medium

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10 Fastest Growing Side Hustles Across The U.S. And Canada In 2025

71% of Americans are searching for secondary income sources through side hustles or second jobs.
The fastest-growing side hustles in the U.S. from 2023 through 2024 are mobile car wash service, selling stock photos online, crypto trading, personal shopping service, food delivery driver, crypto trading strategies, freelancing, sustainable investing strategies, selling digital products, and online tutoring.
Mobile car wash service is the fastest-growing side hustle in America with a search growth of 276% over the past year.
YouTube monetization is the fastest-growing side hustle in six states, including New York, Illinois, and Michigan.

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Dev

381

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Automate Your JavaScript to TypeScript Migration with Typify

Typify is an automated CLI tool for migrating JavaScript projects to TypeScript.
It features smart type inference, zero friction conversion, and readiness for the TypeScript ecosystem.
Typify offers 50+ common patterns detected, context-aware analysis for database connections and API clients, and modern TypeScript features support.
Developers love Typify due to reduced manual typing, compatibility with the TypeScript ecosystem, and faster migration times.

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Medium

336

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Master Structural Directives in Angular 19

With Angular 19’s latest syntax, structural directives like @if, @for, and @switch replace the old *ngIf, *ngFor, and *ngSwitch.
These updates make templates cleaner and more intuitive, while maintaining the power to dynamically shape the UI.
The new control flow syntax enables showing, hiding, or repeating elements based on data, making the templates feel more like familiar logic.
Example of using @if, @for, and @switch in an Angular 19 project to build a dynamic book library app.

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Mjtsai

260

Google Moves Android Development to Internal Branches

Google is moving Android development to internal branches, leaving AOSP for public development.
This shift aligns with recent moves made by Google and reduces the insight into their development efforts for external developers.
The public AOSP branch usually lags behind the privately available Android developments.
This change poses challenges, as merging patches between public AOSP and internal branches becomes more difficult.

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Dev

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Are Desktop Apps Making a Comeback?

Desktop apps are making a comeback, alongside the dominance of web apps.
Desktop apps provide a richer and more seamless experience compared to web apps.
Key reasons for the resurgence of desktop apps include performance, better user experience, offline capability, and security and privacy.
Cross-platform development frameworks allow developers to build apps that work on web, mobile, and desktop with the same codebase.

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Medium

406

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All about Gemini 2.5 Pro in one go..

Google's new AI model, Gemini 2.5 Pro, is a smart and advanced AI brain.
Gemini 2.5 Pro is a large language model that can generate answers, write content, and solve problems.
Unlike other models, Gemini 2.5 Pro reasons through questions internally, resulting in better answers for complex queries.
Gemini 2.5 Pro is considered a big deal in the AI community and is compared with models like GPT-4.5 and Grok.

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