Infinity CS
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Exploring the world of CS, AI, and ML 🧠. Sharing high-quality resources, tools, and interesting tech breakthroughs daily. Join us to learn and build together!
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In today’s fast-changing online media world, yt-dlp remains the leading open-source tool for downloading video and audio. Even as streaming platforms add stronger protections, this command-line tool is still trusted by developers.


The most significant evolution is how yt-dlp handles platform security. To bypass modern bot-detection and encrypted signatures, yt-dlp now supports external JavaScript runtimes. While it remains a Python-based tool, it uses engines like Deno or Node.js to solve complex server-side puzzles in real-time. This helps it access high-quality content, including 4K and 8K videos, which many basic tools cannot download.


yt-dlp is not just a downloader. It helps users keep control over their content. Since online media can be removed or locked behind paywalls at any time, yt-dlp allows users to save and manage their own copies. For users who are comfortable with terminal tools, it remains a powerful tool between online content and local storage.


✍️ @TheInfinityAI
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Article 31: Policy Gradients and Actor-Critic – The Direct Strategy 🎭

Sometimes, calculating the value of every action is too hard. Instead of it, the agent learns the policy directly. We call it as Policy-Based learning.

1. Policy Gradients (Learning the Probability).

In Q-Learning, we pick the action with the highest number. In Policy Gradients, a Neural Network outputs a probability distribution.

The workflow;

The network says there is a 70% chance that jumping is good and a 30% chance that running is good.

The agent picks an action based on these percentages.

If the action leads to a high reward, the machine increases the probability of that action for the future.

If the action leads to a penalty, it decreases the probability.


2. The Actor-Critic Architecture

Policy Gradients can be noisy and slow. To fix this, we combine Value-Based and Policy-Based methods. This is the Actor-Critic model.

Think it as a movie set:

The Actor - this is a neural network that learns the Policy. It decides which Action to take.

The Critic - This is a second neural network that learns the value. It watches the actor and critiques the action. It tells to the actor if the action was better or worse than expected.


3. Advantage Function (A)

The critic uses a special math tool called the advantage function to help the Actor.

A(s, a) = Q(s, a) - V(s)

V(s) - This is the average reward we expect from this state.

Q(s, a) - This is the actual reward we got from a specific action.

Result - If A is positive, the action was better than average. The actor learns to do it more. If A is negative, the actor learns to do it less.


Summary 📝

Policy Gradients teach the agent a strategy (probabilities) directly. Actor-Critic models use two brains; one to act (Actor) and one to give feedback (Critic). The Advantage Function helps the agent understand if an action is better than the average choice. 🙊😁.

In the next article (Article 32), we enter Phase 9: Deep Learning, where we study the secrets of Neural Networks and Backpropagation!
🧠 🙊😁

✍️ @TheInfinityAI
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Which library is used for basic plotting in Python?
Anonymous Quiz
24%
NumPy
26%
Pandas
44%
Matplotlib
6%
Tensorflow
Data breach Alert ☠️

ශ්‍රී ලංකාවේ රාජ්‍ය පරිපාලන, පළාත් සභා සහ පළාත් පාලන අමාත්‍යංශයේ නිල වෙබ් අඩවිය (pubad.gov.lk) සහ එහි පද්ධතිවලට එල්ල කරලා තියෙන සයිබර් ප්‍රහාරයක් හේතුවෙන් රාජ්‍ය සේවකයන් දහස් ගණනකගේ සංවේදී දත්ත අන්තර්ජාලයට මුදාහැර ඇති බවට වාර්තා වෙනවා. wh6am නැමති Threat Actor විසින් මේ දත්ත Dark Web අඩවි හරහා අලෙවි කිරීමට උත්සාහ කරන බවට තොරතුරු Dark web Intelligence වාර්තා කරනවා.

මේ විකුණන්න තියෙන Data අතර,
▪️ Full names (first and last, initials)
▪️ Email addresses (personal and work)
▪️ Phone numbers (mobile, office, home)
▪️ Physical addresses (home and work)
▪️ National ID numbers (NIC)
▪️ Job titles and designations
▪️ Employer names and department details
▪️ Usernames and hashed passwords
▪️ User registration dates and last activity timestamps
▪️ Internal government circulars and service minutes (PDF files)


වගේ දේවල් තියෙනවා. මේක තවම unconfirmed. නමුත් Source කීපයකින්ම මේක වාර්තා කරනව. මෙ තොරතුරු Dark Web හරහා ඩොලර් 200 වැනි සුළු මුදලකට අලෙවි වෙනවා. රාජ්‍ය සේවකයින් ඉදිරි කාලවලදී Phishing Attack වලට අහු වෙන්න පුළුවන් මේ නිසා. (Targeted Phishing, Identity Theft, Social Engineering)

Sources
▪️ Source 01
▪️ Source 02
▪️ Source 03

✍️ @TheInfinityAI
Which activation function is most commonly used in hidden layers of deep neural networks? ✴️
Anonymous Quiz
28%
Sigmoid
17%
Tanh
28%
ReLU
26%
Softmax
Part_3_n8n_Course.zip
1.5 GB
Complete n8n Workflow Automation Course 🚀

Learn how to build powerful, self-hosted AI workflows and automate your daily tasks without writing complex code! n8n is the ultimate open-source alternative to Zapier.

🎯 Download, extract, and start building your first automation today!


@TheInfinityAI
2
Which neural network architecture is primarily used for image classification tasks?
Anonymous Quiz
11%
RNN
37%
CNN
24%
Transformer
27%
Autoencoder
Graph_Databases.pdf
9.9 MB
Graph Databases (2nd Edition)

Highly recommended for anyone working with connected data. This edition covers everything from the basics of graph theory to building high-performance applications with Neo4j. An essential resource for modern database architecture. 📚


Authors
: Ian Robinson, Jim Webber, and Emil Eifrem

#GraphDatabases #NoSQL #DataScience #DatabaseDesign #Resources
Deep Learning A Comprehensive Overview.pdf
2.2 MB
Need a big picture view of Deep Learning? 📊

This comprehensive review by Iqbal H. Sarker is the perfect starting point. It moves from the history of artificial neural networks to modern breakthroughs, helping you understand how DL models learn from data to drive automation. Whether you are a researcher or a developer, this paper serves as an excellent guide to the state-of-the-art in DL modeling.


#DeepLearning #ArtificialIntelligence #MachineLearning #Industry40 #ResearchPapers
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What could happen? LOL.

From idea to final render, all in one place. Claude + Higgsfield MCP is the ultimate creative powerhouse for agents and creators. 🔗⚡️


#ClaudeAI #Higgsfield #AIProduction
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Breaking_the_Sorting_Barrier_for_Directed_Single_Source_Shortest.pdf
371.2 KB
Need the latest advancements in graph theory? 📈🔍

This research paper, titled "Breaking the Sorting Barrier for Directed Single-Source Shortest Paths," presents a new, faster deterministic algorithm for finding the shortest paths from a single source in directed graphs with non-negative real edge weights. 🚀 By introducing a recursive partitioning technique to manage the frontier of vertices, the authors have developed a method that surpasses the traditional time complexity limit set by Dijkstra’s algorithm for sparse graphs. 📉 This work represents a significant milestone, showing that Dijkstra's algorithm is not optimal for this fundamental problem and offering a faster alternative for researchers and developers working on graph optimization. 🛠📊


@TheInfinityAI #GraphTheory #Algorithms #ComputerScience #ResearchPapers #SSSP
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Forwarded from The Hacker News
🛑 ALERT - A Chrome ad blocker with 10 MILLION+ installs has a dormant risk.

Experts say the extension can be remotely configured to run arbitrary JavaScript across websites, without an extension update or store review.

Read the full analysis: https://thehackernews.com/2026/06/chrome-ad-blocker-with-10m-installs.html
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🇮🇳 | Indian Government orders Meta to halt WhatsApp username rollout, seeks response within 3 days 🚫📱

The Indian government has directed Meta to immediately suspend the rollout of WhatsApp’s upcoming Username feature in India 🇮🇳🛑.

According to reports by Reuters 📰, India’s Ministry of Electronics and Information Technology has sent an official notice to Meta regarding the matter. The new feature would allow users to communicate without revealing their phone numbers 🔒📞. However, Indian authorities have raised concerns that this could significantly increase online financial fraud 💸, impersonation, and cybercrime 🕵️‍♂️.

Officials warn that criminals may exploit the feature by creating fake accounts under the names of government institutions or public figures to deceive the public 🎭.

As a result, Meta has been asked to provide a detailed explanation of its security measures within 3 days 🗓️, and to avoid launching the feature in India until discussions with the government are completed 🤝🏛️.

Responding to the issue, a WhatsApp spokesperson stated that the feature has not yet been activated 🛑, and that the company plans to reserve usernames related to government entities, public figures, and verified accounts in advance to prevent misuse .

India remains WhatsApp’s largest market 📈, with over 500 million users 👥. Previously, apps like Telegram and Signal have also faced scrutiny from Indian authorities over features that allow users to hide phone numbers 🕶️📱.
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Mastering Cloud-Native Integration: A Comprehensive Overview of Ballerina Language 🌐☁️

In the modern software engineering landscape, building cloud-native systems often feels like assembling a puzzle with pieces that do not quite fit. We live in a world dominated by microservices, distributed architectures, and countless API endpoints. Developers traditionally use languages such as Java, Python, and Go to build distributed systems. However, these languages often treat networking as an additional feature that depends on external libraries, configuration files, and frameworks. To address this challenge, WSO2 develops Ballerina, an open-source, cloud-native programming language specifically designed for network applications, microservices, and system integration. This guide explains what Ballerina is, explores its core concepts, and demonstrates how it simplifies cloud-native application development.

🤔 Why Ballerina?

Unlike legacy programming languages that treat network interactions as basic I/O (Input/Output) operations, Ballerina treats the network as a first-class citizen. In Ballerina, concepts like clients, services, protocols (HTTP, gRPC, GraphQL), and data formats (JSON, XML) are fundamentally built into the language grammar itself.

Key Pillars;

Network-Aware Syntax - Developers create services and clients without relying on large external frameworks.
Visual Representation - Every Ballerina program can be visualized as a sequence diagram, helping architects and developers understand application flow.
Cloud-Native Support - The compiler generates deployment artifacts for Docker and Kubernetes.
Structural Typing - Ballerina works naturally with JSON and XML, making data integration simple.


🧱 Core Building Blocks


Ballerina provides several built-in concepts for cloud-native development.
Listeners - receive network requests.
Services - expose application functionality.
Resource Methods - map directly to HTTP methods such as
GET, POST, PUT, and DELETE.
Remote Methods - support communication through protocols such as gRPC and WebSocket.


🌍 Simple REST Service Example

The following example shows how easily Ballerina exposes a REST endpoint.

import ballerina/http;

service /music on new http:Listener(8080) {
    resource function get tracks() returns json {
        return [
            {id: "1", title: "Shape of You"},
            {id: "2", title: "Blinding Lights"}
        ];
    }
}


This example demonstrates several important features:

The HTTP listener is created with a single statement.
The service automatically exposes the
/music/tracks endpoint.
Ballerina converts the returned records into JSON without additional configuration.


☁️ Cloud-Native Deployment

One of Ballerina's strongest advantages is its built-in cloud support. Instead of manually creating Dockerfiles and Kubernetes manifests, developers simply compile the project. During compilation, Ballerina analyzes the application and generates deployment artefacts, including Docker images and Kubernetes configuration files. This process reduces manual work and simplifies cloud deployment.

🔄 Data Integration

Ballerina includes native support for JSON, allowing developers to create and return structured data with minimal code.

resource function get summary() returns json {
    return {
        totalTracks: 2,
        systemStatus: "Healthy"
    };
}


Because JSON is a built-in language type, developers do not need additional libraries for serialization or deserialization.


🎯 Conclusion

Ballerina is a programming language designed specifically for cloud-native software development. It combines networking, data integration, and cloud deployment into a single language, reducing the need for external frameworks and boilerplate code. Its built-in support for services, APIs, JSON, Docker, and Kubernetes makes it a practical choice for building modern microservices and distributed applications. For developers who regularly create APIs or integration services, Ballerina offers a clean and efficient development experience.

@TheInfinityAI
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