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Inside the Black Box: The Potential of Open-Source AI

AI, a controversial topic, has tech enthusiasts praising its abilities while pessimists focus on its risks to the workforce and income inequality.
Open-source AI, championed by tech giants like IBM and Google, offers a way to address concerns and mitigate risks associated with privatized AI.
The open-source philosophy emphasizes collaborative participation, shared responsibility, open exchange, and community-oriented development.
Open-source AI provides transparency, allowing developers to understand and troubleshoot AI tools like large language models (LLMs).
By making AI tools, code, and data accessible to everyone, open-source AI enhances innovation, improves access, and encourages competition.
The transparency provided by open-source AI helps in minimizing risks and biases in AI models, enhancing safety and trustworthiness.
Open-source AI also reduces costs, fosters competition, and avoids vendor lock-in, making AI technology more accessible and affordable.
Some challenges of open-source AI include potential lack of full openness, security risks, and the need for additional troubleshooting and configuration.
Proper assessment and understanding of open-source AI are crucial, considering factors like usage rights, security vulnerabilities, and potential drawbacks.
To leverage the full potential of open-source AI, organizations must adhere to principles of data governance and establish transparent practices.
Open-source AI adoption is on the rise, signaling a shift towards accessible and transparent AI development for the future.

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Medium

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How to Strip Characters From a Python String

Python provides the .strip() method to remove characters from the beginning and end of a string.
To remove characters from only one side of a string, use .lstrip() or .rstrip().
You can pass a string of characters to .strip(), .lstrip(), or .rstrip(). This tells Python what characters to remove.
NOTE: This does not remove the exact sequence “///”. Instead, it removes all instances of the characters '/' from…

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Medium

291

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When Personal Convenience Compromises National Security: The Hidden Dangers of Using Gmail for…

Personal email accounts are vulnerable to phishing attacks, credential theft, and man-in-the-middle exploits.
Mixing personal and professional tools leads to cascading risks and potential security meltdowns.
Gmail's Confidential Mode is not a comprehensive solution for secure communication.
To improve security, measures such as automated archiving, cyber drills, encryption, and zero-trust architecture are recommended.

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PlanetPython

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Python GUIs: Getting Started with Streamlit �� Build your first Streamlit app and explore some basic features

Streamlit is an open-source Python library for creating and sharing custom web apps for machine learning and data science.
Installing Streamlit requires using pip to install; after installation, create a main Python file to write and edit the Streamlit app.
Streamlit allows adding titles, headings, and paragraphs to format text with ease, making it user-friendly for data visualization.
Buttons in Streamlit enable interactivity; examples include basic buttons, download buttons, and radio buttons for options.
Sliders in Streamlit are used to select values by moving a handle along a track; both single-value and range sliders are supported.
Dropdown menus in Streamlit are added using st.selectbox() to provide users with a selection from a predefined list.
A sidebar in Streamlit is an additional panel on the left side of the app for interactive widgets or displaying accessible information.
Creating a web app in Streamlit involves combining concepts like dataset display, sidebar controls, filtered data display, and basic statistics.
This tutorial covers various functions and features in Streamlit, demonstrating how to create interactive web apps for data exploration.
Adapting the provided examples allows for the creation of user-friendly data exploration tools using Streamlit for different datasets.

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Dev

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Microsoft Is the Best (But Slow), IBM Beats Most of OpenAI: What I Found Testing 50+ LLMs

Microsoft's Phi-4 was the most accurate model overall.
IBM's Granite models outperformed many of OpenAI's offerings.
Speed vs. accuracy is a tradeoff, and the best choice depends on workflow.
GPT-4o by OpenAI was the overall winner in terms of balanced performance.

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Medium

300

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Spring Boot Essentials: The Interview Cheat Sheet

The DispatcherServlet is the front controller in the Spring MVC framework, routing incoming HTTP requests to appropriate handlers.
Spring Boot simplifies web application development by providing conventions over configurations and automatic setups.
Layered architecture in Spring Boot separates applications into Controller, Service, and Repository layers for better organization.
Maven aids in dependency management by automating the download and management of project libraries.
Maven follows a lifecycle with various phases, where each phase represents a step in the build process.
The @SpringBootApplication annotation conveniently combines multiple annotations in Spring Boot applications.
@Controller returns view names, while @RestController is used to return data directly as the response body.
@RequestMapping, @GetMapping, and @PostMapping are annotations for mapping HTTP requests to specific methods in Spring controllers.
In Spring Boot, a Bean is a Java object managed by the Spring container and can be defined using annotations or configuration classes.
The Inversion of Control (IoC) container in Spring handles object creation, dependency injection, and lifecycle management.

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Dev

243

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Why Do Devs Spend a Sprint on 20% of the features?

Devs often spend a sprint on 20% of the features due to over-engineering.
Over-engineering can lead to time sinks, slower releases, and growth of tech debt.
Users may not care about the over-engineered features, building a system no one needs.
The market moves on while perfection is sought, allowing others to ship and gain a competitive edge.

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Medium

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Your UI Feels Slow Even If It’s Fast : Design UI That Feels Instantly Responsive

Even a fraction of a second of delay can make a UI feel sluggish.
Acknowledge user actions immediately to make the UI feel responsive.
Optimistically update the UI before receiving the API response.
Reserve space for dynamic content and use skeleton loaders for better user experience.

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Javacodegeeks

374

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Green Cloud Computing Practices 2025: Measuring & Reducing Energy Consumption

By 2025, sustainable cloud practices will be critical for enterprises aiming to reduce energy costs and meet ESG goals.
This guide explores the latest tools for measuring cloud energy use, AI-driven optimization strategies, case studies from AWS, Azure & Google Cloud, and carbon-aware computing techniques.
Key metrics to monitor include kilowatt-hour (kWh) per workload, carbon intensity (grams CO2e per kWh), and PUE (Power Usage Effectiveness) of data centers.
Energy optimization strategies include scheduling workloads for renewable energy, right-sizing underutilized resources, and adopting sustainable architectures.

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Dev

322

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🚀 How to Optimize Your React App for Better Performance

To optimize your React app for better performance, consider the following techniques:
1. Use React.memo() to prevent unnecessary renders.
2. Lazy load components with React.lazy().
3. Optimize images and use lazy loading.

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Dev

260

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Model Context Protocol (MCP) 101: A Hands-On Beginner's Guide!

The Model Context Protocol (MCP) by Anthropic simplifies AI model integration with external data sources and tools, enhancing developers' ability to access real-time data and advanced functionalities.
MCP acts as a universal connector for AI applications, streamlining interactions with various data sources and enabling developers to focus on innovation rather than integration complexities.
MCP addresses challenges faced by Large Language Models (LLMs), such as knowledge limitations, domain knowledge gaps, and non-standardized integrations, by providing a standardized solution for accessing external data.
MCP facilitates communication between AI models and external data/tools through a client-server architecture, comprising hosts, clients, servers, local data sources, and remote services.
Benefits of implementing MCP include standardization, enhanced performance, flexibility in switching between LLMs, and improved security through authentication and access control mechanisms.
Getting started with MCP involves setting up servers to expose tools like 'Get Alerts' and 'Get Forecast'; it offers a standardized approach to AI integration for efficient and secure application development.
MCP's role as a standardized protocol for managing context between LLMs and external systems is exemplified by projects like the SingleStore MCP Server, enabling seamless integration for simplified database operations.
SingleStore's MCP Server allows interactions with SingleStore using natural language through Claude Desktop or compatible MCP clients, offering a unified database for transactional and analytical workloads.
The MCP repository provides installers and servers for projects like SingleStore, making it easier to automate database operations and enhance AI applications' capabilities.

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Medium

313

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How to Detect Outliers in Data Preprocessing? A Guide for Data Scientists ️

As data scientists, it is important to detect and handle outliers in data preprocessing.
Two powerful methods to detect outliers are Z-score and Interquartile Range (IQR).
Z-score measures the number of standard deviations a data point is away from the mean.
A Z-score greater than 3 or less than -3 indicates an outlier.

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Logrocket

371

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Leader Spotlight: Balancing long-term strategy with short-term iterations, with Aslan Sevi

Aslan Sevi, Head of Product at ZEDGE, discusses balancing long-term strategy with short-term iterations in the mobile app industry.
Open communication within globally dispersed teams at ZEDGE is emphasized as a key factor for competitive success.
ZEDGE's ability to adapt quickly in the evolving mobile landscape has been crucial for transitioning into today's smartphone era.
Balancing monetization through advertising subscriptions and virtual tokens at ZEDGE without compromising user experience is a challenging task.
A/B testing framework at ZEDGE allows for effective experimentation and optimization of monetization strategies.
A major redesign at ZEDGE showcased the importance of quickly adjusting strategies based on user feedback and performance data.
ZEDGE prioritizes long-term goals while remaining agile in responding to shifting priorities in the mobile app space.
Testing early and evaluating potential impact versus effort helps ZEDGE determine the worthiness of pursuing new features.
Strategic decisions to kill features at ZEDGE are guided by clear KPIs and data-driven insights, focusing on value and user satisfaction.
Strong alignment and communication among product, marketing, and development teams at ZEDGE ensure everyone remains on the same page amidst evolving roadmaps.

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Medium

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Speculation Fades, but Innovation Lasts: The Future of Web3 Lies in Real Solutions

Web3 represents a shift towards decentralization, security, and user empowerment.
Dmail is a decentralized communication platform leveraging blockchain technology.
Dmail ensures data ownership, security, privacy, and censorship resistance.
Web3's future lies in real solutions, such as Dmail, that enhance user sovereignty.

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Dev

234

Image Credit: Dev

I Will Teach You SQL in 3 Minutes

SQL is a powerful tool for managing and manipulating data in relational databases.
SQL is used in various industries including e-commerce, social media, and data analysis.
Key SQL operations include selecting data, joining tables, and inserting data.
Learning SQL allows you to organize and retrieve data quickly, automate tasks, and make data-driven decisions.

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