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The Three Ages of Software: How Programming is Evolving in the AI Era

Andrej Karpathy, former director of AI at Tesla, discussed a fundamental transformation in software development during a recent talk at Y Combinator.
Software development is evolving in the AI era, creating opportunities for both experienced developers and newcomers.
Three Ages of Software evolution were highlighted: Traditional Programming, Neural Network Training, and Natural Language Programming.
Traditional Programming involves writing explicit instructions in languages like Python, Java, or JavaScript.
Neural Network Training replaces explicit rules with training on data where code becomes the weights and parameters.
Natural Language Programming allows programming in languages like English, with computers understanding and executing instructions.
Large Language Models (LLMs) like ChatGPT are seen as new types of computers impacting various applications.
AI applications today augment human capabilities and are compared to 'Iron Man suits' rather than robots.
Vibe coding enables building software through natural language descriptions, opening programming to non-professionals.
There is a shift towards AI-friendly documentation and designing systems for both human and AI users.
Successful AI applications offer an Autonomy Slider, Visual Interfaces, and Human-in-the-Loop features.
The key to AI collaboration is speeding up the cycle through clear instructions and verification.
The future of computing lies in effective collaboration with AI, amplifying human creativity rather than replacing it.
The transition to Software 3.0 signifies a significant change in software creation and human-computer interaction.
The era of AI computing is compared to the beginning of modern computing, offering endless possibilities with increasing accessibility.
AI has already changed software development, and the focus now lies on leveraging these new capabilities to create innovative solutions.

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Hackernoon

285

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How to Connect an Express Application to Postgres Using Sequelize

PostgreSQL, a widely used database, supports SQL and NoSQL querying.
Connecting a database to a web app through an ORM like Sequelize is common.
This tutorial focuses on integrating Postgres with Express through Sequelize.
It guides on creating a simple task management API.
Prerequisites include Node.js, Express knowledge, and a running Postgres instance.
Setting up the project involves installing necessary packages and configuring files.
Configuring Sequelize includes loading environment variables and creating an instance.
Defining a Task model in Sequelize involves specifying attributes and options.
Creating the Express server involves setting up middleware and defining API routes.
The tutorial concludes with testing the API endpoints and offers further reading resources.

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Medium

386

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Bring Back the Age of Free and Fun Software

Developers are increasingly using subscription models, ads, and predatory in-app purchases in software, stripping away core functionality from free versions.
A new app called Freeze Frame! has been created as a response to this trend, offering a lightweight, free alternative to paid apps.
Freeze Frame! allows users to extract high-quality frames from videos without losing resolution, catering to those seeking clear still images.
The app was developed by the author to combat the prevalence of subscription-based apps, particularly when core features are locked behind paywalls.
The entire Freeze Frame! app was built on an iPad, showcasing the accessibility of app development tools.
The author emphasizes the need to uphold the original spirit of the internet by creating free and functional tools for users.
Freeze Frame! is available on iOS for those looking to avoid the monetization of simple tools.
The app allows users to capture high-quality still images from videos with precision and clarity.
The goal is to provide users with software that works without the need for recurring subscriptions or in-app purchases.
The author encourages users to try Freeze Frame! to experience free and efficient software.
The app was developed as a response to the frustration caused by the trend of apps becoming monetization channels rather than straightforward tools.
Amid the prevalence of subscription-based models, Freeze Frame! aims to bring back the age of free and fun software.
The development of Freeze Frame! indicates the growing accessibility of app development tools, allowing for the creation of user-centric apps.
The creator of Freeze Frame! calls for a return to the original internet spirit of building tools out of passion rather than for profit.
Those weary of subscription-based apps are encouraged to try out Freeze Frame! on iOS for a free and efficient alternative.

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Dev

277

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Voxel Raycaster (Voxlap-style) with baked cubic PBS/PBR lighting C#

A voxel raycaster with baked cubic Physically Based Shading (PBS) and stylized outlines was created from scratch in C# with OpenTK.
The renderer aims to capture the look of games like Jet Set Radio, Wind Waker, and PS1/PS2-era classics.
Key goals include a stylized look, voxel-based 3D rendering, prebaked lighting to simulate advanced shading, post-processing outlines for style, portability, optimization, and compactness.
The voxel texture is generated using procedural shapes like islands and crystals and employs multiple Global Illumination (GI) passes.
Raycasting occurs inside a 3D texture with voxel color and alpha data using a fragment shader.
An outline shader adds thick outlines around color or brightness changes, creating a cel-shaded, 'inked' look.
Technologies used include C#, .NET 6, OpenTK (OpenGL bindings for C#), GLSL shaders (330 core), with no engine or Unity, just raw code.
The project aims to be small, fast, customizable, stylized with an early-2000s console look, and fun to code and draw with.
Future plans involve optimizing GPU performance, data compaction, and rendering tricks.
This kind of project is ideal for those interested in rendering, graphics, or building stylized engines from scratch, requiring math, code, and creativity.

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Dev

155

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Stack and Heap: Memory in Javascript

Memory in JavaScript involves stack and heap memory allocation.
Primitive values are stored in the stack while objects are stored in the heap.
Stack memory is fixed, while heap memory can grow in size.
Changes to variables in the stack memory do not affect other variables.
Variables pointing to objects in heap memory share references, leading to changes reflecting across variables.
Shallow copy only copies references, not the actual object.
Deep copy duplicates the entire object structure including nested objects.
JSON.stringify() and JSON.parse() can be used for deep copying objects.
Serialization and deserialization are crucial for working with APIs, network requests, and data storage.
Understanding memory allocation in JavaScript is essential for effective programming.

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Medium

349

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Linters don’t just prettify code — A Case for Method Parentheses in Ruby

The necessity of a seemingly trivial linting rule in Ruby explained.
Method Parentheses cop helps prevent ambiguity and unintended behavior.
Omitting parentheses can introduce confusion, especially in complex expressions.
Examples show how omitting parentheses alters method call interpretations.
Ruby interprets expressions differently based on parentheses usage.
Problems arise when parentheses are omitted in certain contexts.
Combining different forms can lead to even more complex situations.
Special considerations exist when using parentheses with the super method.

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Medium

405

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What Is SQL and Why It’s Everywhere Today

SQL is a standard programming language for relational databases used in various fields where data management is crucial.
It is an integral part of web applications, mobile apps like Spotify, and social media platforms like Instagram.
SQL stands for Structured Query Language and is considered a fourth-generation language.
Despite the emergence of other languages, SQL remains the most implemented language for databases.
Learning SQL can be beneficial for individuals interested in computer programming or planning to enter the field.

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Medium

416

How to Save Money on Blockchain RPC Provider Costs (My Sincere Apologies to RPC Provider Companies!)

A Blockchain RPC Provider enables users to interact with a blockchain node without running one themselves, like Infura.
Blockchain RPC Provider costs include gas fees paid to the network and RPC costs to the provider.
Querying blockchain data each time from the network can be slow and expensive, so a caching layer is needed.
Instead of querying data for NFT transactions every time, a caching solution was implemented to improve speed and reduce costs.
Various NFT transactions like minting, transferring, and burning were tracked with ownership changes.
To save costs, a time-based rotation strategy between four free-tier RPC providers was employed.
Infura Pro costs $225/month, Alchemy Growth costs $49/month plus additional fees, and running a personal node costs 2-3 million KRW/month.
Relying on free tiers, limitations, and response formats of RPC providers varied, requiring rotation for continuous data collection.
A balance was sought between real-time blockchain updates and cost efficiency by collecting changes periodically and storing them for quick responses.
Third-party blockchain indexing services like The Graph and Moralis could also be utilized for data aggregation.
Querying blockchain data in real-time for a project led to delays and high costs, prompting the need for a caching mechanism.
Implementing a backend API and caching layer improved response times and reduced the number of RPC calls for NFT-related actions like transfers and burns.
Multiple types of NFTs were managed, including puzzle pieces, blueprint items, and material items, each with different transaction events.
A time-based approach with rotating between multiple free-tier RPC providers was a cost-effective solution for continuous data collection.
The implementation allowed for collecting blockchain data without incurring additional costs, addressing budget constraints for a student project.

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Dev

273

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My Typescript Journey and effect of Copilot auto-completion

During a break from university, the individual decided to enhance their development skills by learning new technologies.
Based on suggestions from ChatGPT, they opted to focus on general development and DevOps instead of fundamental skills.
They started by learning ES6+ Function in JavaScript and async await in just two days from documentation and YouTube.
Next, they delved into learning TypeScript from a tutorial by Hitesh Chaudhary on FreeCodeCamp.
While practicing coding in VScode, they noticed that Copilot's auto-completion feature was completing their code automatically when naming functions.
Although auto-completion generally helps, in this case, the individual found it counter-productive as it hindered their learning process by not allowing them time to think and understand the concepts.
The advice given is to disable Copilot's auto-completion feature while learning. Instead, utilize Copilot for asking questions and clarifying doubts, which can enhance the learning process.

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Dev

185

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✨ Why the Same Font Can Look So Different — and How to Fix It

Fonts can look different even when using the same font due to variations like glyphs.
Typography discrepancy noticed when comparing personal portfolio site to Brittany Chiang’s site.
Discovered that the letter 'a' had different glyphs: double-storey and single-storey.
Double-storey 'a' is traditional, while the single-storey 'a' looks more modern.
Used CSS property font-feature-settings to change the glyph style to single-storey 'a'.
Attempted to implement the change through Next.js and Tailwind CSS, but it didn't work.
Opted to self-host the Inter font by downloading it from GitHub and configuring it in the project.
After self-hosting the font, successfully achieved the desired single-storey 'a' style.
Key takeaway: Fonts like Inter have multiple glyph variations, and font-feature-settings in CSS can customize glyphs.
When using third-party font services, not all OpenType features may be accessible.
Self-hosting fonts provides more control over glyph variations and styling.
Useful Links: Brittany's Portfolio, Google fonts article on font glyphs, MDN for font-feature-settings, Next.js Docs on Using Local Fonts.
Author invites feedback and tips in the comments.
Article concludes with gratitude for reading.

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Medium

179

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How Google Plans to Save Indians ₹20,000 Crore from Cybercrime in 2025

Google is enhancing fraud detection on UPI platforms and Google Pay using AI.
In 2024, Google helped prevent frauds worth ₹13,000 crore and issued over 41 million scam warnings.
A new engineering center will be established in India, focusing on building India-specific safety tools.
Expansion of Google's fraud awareness program DigiKavach.
Campaigns like “Mauka Gawao” have reached over 177 million users.
Google collaborates with the Indian Cyber Crime Coordination Centre and the national cybercrime helpline.
Teaming up with banks, telecom companies, and fintechs through the Safer Internet India Coalition.
Introduction of an interactive tool called ShieldUp! to educate users on recognizing scams.
Google funds awareness campaigns targeting vulnerable users and MSMEs through NGOs like CyberPeace Foundation.
Plans to introduce AI-generated content labels to combat misinformation like deepfakes.
Google Play Protect scans 200 billion apps daily to identify and remove malicious software.
Preparation for future threats by moving toward quantum-resistant cryptographic methods.
Google aims to save Indians ₹20,000 crore from cybercrime losses by 2025.
The initiative combines AI fraud prevention, localized threat analysis, digital education, and industry collaboration.
The approach promises to enhance online safety for millions of Indian users and organizations.

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Dev

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What is git tags ? How to Use Git Tags (Create, List, Push & Delete) — Ariful Haque Sajib

Git tags are references to specific points in Git history used to mark important milestones like release versions.
There are two types of Git tags: lightweight (pointers to commits) and annotated (store metadata).
Tags are useful for version control, documentation, deployment, and referencing important points in history.
Commands for creating tags include lightweight and annotated tag creation and tagging specific commits.
Commands for listing tags provide ways to view all tags, use pattern matching, and show tag details.
Pushing tags to remote repositories can be done for specific tags or for all tags at once.
Checking out tags allows for creating detached HEAD states and branching from tags.
Deleting tags can be done locally or from remote repositories.
Advanced usage includes signing tags with GPG, verifying signed tags, and listing tags with creation dates.
Understanding the differences between Git tags and branches is crucial for efficient workflow management.
Git tags are valuable for marking project milestones, enabling easy rollbacks, and improving version management.

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Dev

256

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Why Composition over Inheritance Is More Than Just a Design Principle

Inheritance is default for reusing behavior, but in evolving systems, composition offers more flexibility.
Inheritance leads to rigid hierarchies, tight coupling, low reusability, and poor maintainability.
Composition injects behavior at runtime, offering modularity, loose coupling, flexibility, and testability.
Example: Multi-Channel Notification Service in .NET demonstrates composition usage.
NotificationService uses composition with INotificationChannel to send messages through different channels.
Composition allows mixing channels without subclassing, fragile overrides, or bloating class hierarchy.
In modern .NET applications, composition leads to simpler, more maintainable code.
Inheritance still has its uses, but for flexibility, reusability, and testability, composition is preferred.

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Medium

311

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How I Used ChatGPT to Automate Code Reviews? (You Can A

A software developer shared their experience using ChatGPT to automate parts of their code reviews, aiming to save time and improve the review process.
Code reviews help ensure clean, functional, and maintainable code but can be time-consuming, especially with multiple projects.
The developer leveraged ChatGPT to look for common issues like bugs, bad formatting, and missing comments, while reserving a final human review for major decisions.
Using the ChatGPT's web interface, the developer found the tool helpful in identifying issues that might have been overlooked.
Automating code reviews through ChatGPT saved time and provided additional insights, although it was not flawless.
Implementing AI tools for code reviews can streamline the process and aid developers in catching errors and adhering to coding standards.
AI-based code review tools can complement human expertise by providing valuable feedback and enhancing the overall review process.
By combining AI automation with human oversight, developers can potentially increase the efficiency and effectiveness of their code review workflows.
The use of ChatGPT for code reviews highlights the evolving role of AI in software development processes, offering innovative solutions for enhancing productivity.
Integrating AI tools like ChatGPT into development workflows demonstrates the potential for improved efficiency and code quality in software development projects.
Exploring AI-powered solutions for code reviews showcases the adaptability of developers in leveraging technology to streamline their work processes.
The experience of using ChatGPT for code reviews underscores the ongoing evolution of AI applications in the realm of software development.
While ChatGPT may not replace human reviews entirely, it can serve as a valuable tool for assisting developers in code analysis and optimization.
The developer's journey with ChatGPT for code reviews illustrates the benefits of combining AI capabilities with human intuition in software engineering practices.

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18 Likes

Medium

168

Lumera Protocol : Unlocking Verifiable AI with Modular Blockchain Infrastructure

Lumera Protocol is addressing the challenge of trust in AI and Web3 by focusing on transparency and verifiability.
Lumera is a Layer‑1 blockchain aiming to accelerate decentralized, verifiable AI, previously known as Pastel Network.
Key Features of Lumera Protocol include Modular Blockchain Architecture, Verifiable Compute using ZKPs, Decentralized Compute Marketplace, and Interoperability.
The protocol offers a marketplace for compute resources, connects with other chains through IBC, and allows AI computations to be validated on-chain.
Next steps for Lumera include Public Testnet, Compute Marketplace Beta, Token Swap, and Foundry Campaign for early incentives.
Lumera's goal is to make decentralized AI transparent, verifiable, and accessible to all, empowering developers without reliance on centralized entities.
Ultimately, Lumera Protocol combines blockchain modularity with verifiable computation to enable trustworthy AI applications.
Get involved in the Lumera revolution by exploring the testnet, joining the Foundry Campaign, and holding $LUME tokens for governance.

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