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How I Minted My Own Memecoin and Earned $200 in Hours

Phantom Mint offers a revolutionary way to mint your own digital memecoin and earn real profits.
The system is accessible to everyone, regardless of their experience or background in cryptocurrency.
The opportunity allows individuals to create memecoins that can gain market value in just a few hours.
With no upfront investment required and a step-by-step system, Phantom Mint offers a risk-free opportunity to explore the world of memecoin creation.

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Medium

291

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Why Google’s Engineers Rarely Use else Statements (And Why You Shouldn't Either)

Minimizing else statements improves readability, maintainability, and scalability.
Top tech companies like Google structure their logic for clarity.
Practical JavaScript examples are provided to help write cleaner, more efficient code.
Real-world clean code practices, including the power of early returns, are discussed.

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Medium

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How I Built a Dark Mode Toggle in React (In 5 Minutes)

The author built a dark mode toggle in React in just 5 minutes.
Light mode is considered an abomination and the author wanted to add a dark mode toggle to their React app.
They used useState to store the mode (light/dark) and toggled it with a button click.
The author also added CSS styles to enhance the dark mode experience.

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Medium

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PicoCTF - “Function Ovewrite” CTF Writeup

The PicoCTF 'Function Overwrite' CTF Writeup demonstrates how to exploit an arbitrary memory write vulnerability in a binary program.
By overwriting the check() pointer with the address of the easy_checker() function, the program's security check can be bypassed.
The write is achieved by underflowing the fun variable, which allows arbitrary memory write beyond the buffer boundaries.
The writeup provides both a manual calculation method and a brute-force method to determine the necessary offsets for the exploit.

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Medium

295

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Creating a RAG for a Local LLM

Llama 4 is introducing an industry-leading 10 million token context window, while Llama 3 had a limit of 128,000 tokens.
Despite the increase in context window size, RAG (Retrieval-Augmented Generation) remains valuable in extracting relevant information from large language models.
Creating a simple RAG system using open-source models like GPT 4 and Mistral Saba can enhance locally-hosted Llama or Qwen models to deliver accurate answers.
Using a diverse and interesting dataset of four books from Project Gutenberg, the benefits of the RAG system can be fully appreciated.

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Dev

326

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Dev Terms Explained with Memes 😎

This article provides a cheat sheet for understanding common developer terms with humorous translations and explanations.
Key terms like Agile, SEO, Tech Debt, and more are demystified in a witty manner to help newcomers in the field.
From Agile methodologies like Scrum and Kanban to SEO tactics such as Semantic HTML, the article covers a wide range of jargon.
It also touches on concepts like Tech Debt, Design Systems, Open Source, and API-related terms like REST, GraphQL, and Rate Limiting.
The discussion extends to Docker, CDNs, A/B Testing, and Performance-related topics such as Big O Notation and Optimization.
Acronyms like CRUD, CORS, SSR, and WYSIWYG are also explained in a fun and engaging manner.
Additionally, the bonus section covers terms like Scalability infrastructure, Fork, SAAS, Web 3, and more.
The article concludes with an invitation for readers to suggest more terms for future updates.
Overall, the article serves as an entertaining and informative guide to decode the language of programming and development.

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Medium

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Outdated Skills of Data Engineers in 2025 — What You Should Stop Doing

Outdated skills of data engineers in 2025 and what you should stop doing.
Traditional on-premises tools are becoming outdated as companies shift to the cloud.
MapReduce is outdated as it is slow and difficult to manage; Apache Spark is a better alternative.
Relying solely on SQL is no longer enough; data engineers need to understand data organization for reporting, analytics, and flexibility.

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2 Likes

Medium

304

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Cracking DSA with Real-World Analogies: Because Code Shouldn’t Feel Like Math Class

Data Structures and Algorithms (DSA) can feel like a cryptic temple language.
However, by associating DSA concepts with everyday things, it becomes easier to understand and apply.
Analogies, such as a stack of plates at a buffet representing the Last In, First Out (LIFO) concept, can be helpful.
Other analogies include a queue at a movie theater representing the First In, First Out (FIFO) concept, and a HashMap in action as a key-value pair lookup.

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Medium

186

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Variables and Data Types in Python — Your First Step into Python

Variables in Python can be thought of as containers that hold values.
Python supports various data types such as strings, integers, floats, booleans, and NoneType.
Python is slower in runtime compared to statically typed languages due to determining data types during execution.
Python is an object-oriented language, where even basic data types are objects.

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Dev

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AugMix in PyTorch (12)

AugMix in PyTorch
AugMix is a technique in PyTorch that can be used to perform data augmentation randomly on an image.
It offers flexibility in terms of adjusting the severity of the augmentation and the mixture width.
The alpha parameter can be used to control the strength of the augmentation.

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Dev

400

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🚀 Dependency Management Issues in Spring Boot & How to Fix Them!

Managing dependencies in Spring Boot can be tricky, leading to runtime errors and unexpected behavior.
Common dependency issues include conflicts, unnecessary dependencies, missing dependencies, and incorrect scopes.
To fix dependency conflicts, use dependency management and detect conflicts using tools like Maven or Gradle.
To address unnecessary dependencies, remove them to improve performance and security and use analyze tools for detection.

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Dev

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Stop Writing API Glue Code – Let Protocols Handle It

ReGenNexus is an open-source universal adapter protocol designed to create a seamless communication framework between any digital entity.
Standard Message Format: ReGenNexus provides a consistent structure for all communication, abstracting away the need for API-specific formatting in your application code.
Automatic Discovery: ReGenNexus helps your applications find and identify other available services on the network.
Context Tracking: The protocol maintains the state of conversations, making complex multi-step interactions easier to manage.

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Towards Data Science

321

How to Optimize your Python Program for Slowness

The article explores how to make Python programs run absurdly slower by examining different rule sets and building small Python programs to run for an extraordinarily long time.
Starting with the most permissive rule set of allowing infinite loops, the article demonstrates a simple program using 'while True' that runs forever.
Moving on to rule set 2, the article introduces nested fixed-range loops to run for an impractically long time with a small amount of memory usage.
Rule set 3 introduces a 5-state Turing machine with infinite, zero-initialized memory, running for 47,176,870 steps before halting.
The article progresses to a 6-state Turing machine known to run for over 10^↑↑15 steps, showing a video of its first 10 trillion steps.
Rule set 5 delves into building a Python program to compute 10^↑↑15 steps using increment, addition, multiplication, exponentiation, and tetration functions.
The article emphasizes the impact of Python's immutable int type on performance, advocating the use of gmpy2.xmpz for in-place updates.
By constructing these programs, the article highlights the capabilities of nested loops, Turing machines, and hand-inlined functions to demonstrate incredibly slow program runtimes.
The exploration of tetration unveils a hierarchy of hyperoperations beyond exponentiation, showcasing the potential to express unimaginably large numbers compactly.
The article concludes by providing insights on writing programs that run for an extensive duration, showcasing the importance of efficient coding practices and minimal systems.
The author invites readers to explore the open-source GitHub repository for all the code discussed in the article.

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VentureBeat

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Stanford’s AI Index: 5 critical insights reshaping enterprise tech strategy

The Stanford Institute for Human-Centered Artificial Intelligence (HAI) released its 2025 AI Index Report, offering insights into AI's global development.
The report highlights how high-quality AI has become more affordable and accessible, with training costs decreasing significantly.
There is a performance convergence between closed and open-weight models, making cutting-edge AI capabilities more accessible to organizations.
78% of organizations now use AI, but real business impact lags behind adoption, with limited data on achieving massive ROI at scale.
The report suggests focusing on measurable AI use cases with clear ROI potential and enhancing AI governance frameworks.
AI usage benefits supply chain and service operations functions the most on the cost side, while strategy and corporate finance see significant revenue gains.
AI tools tend to benefit lower-skilled workers more than higher-skilled ones, showing productivity gains across various sectors.
Despite growing awareness of AI risks, organizations show significant gaps in risk recognition and mitigation, posing challenges for responsible AI adoption.
IT leaders are urged to prioritize targeted AI implementations, responsible governance practices, and leveraging AI for enhancing workforce capabilities.
The report signals a trend of broader AI adoption on the horizon, emphasizing the importance of strategic AI deployment.

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Medium

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What If We Could Redefine the Distance Between Texts?

Dynamic Weight Inversion (DWI) is a technique that allows modulating the embedding space in real time based on specific intent or context.
This technique reshapes the semantic space to accurately reflect the user's intent, enabling the system to find what is meant, not just what's superficially similar.
The DWI approach involves calculating a transformation matrix based on the input vector and the target vector representing the desired context.
DWI has been successfully tested on a semantic search engine without retraining the model, showing significant changes in similarity rankings based on different contexts.

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