bytedance/MegaTTS3
💻 https://github.com/bytedance/MegaTTS3
TLDR MegaTTS3 by Bytedance is a lightweight and efficient text-to-speech (TTS) model with only 0.45B parameters. It supports high-quality voice cloning, bilingual (Chinese and English) speech synthesis, and accent intensity control. Users can download pre-trained models, use command-line tools for inference, and access a web UI. The project aims for academic use, with stringent security measures and is licensed under Apache-2.0.
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Nvidia adds native Python support to CUDA
🔗 https://thenewstack.io/nvidia-finally-adds-native-python-support-to-cuda/
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MinIO: AWS S3, but free and open-source
🔗 https://devjournal.info/minio-aws-s3-but-free-and-open-source/
TLDR MinIO offers an open-source, high-performance alternative to AWS S3 for object storage, ideal for indie developers and small teams due to its cost-effective scalability and flexibility. With features like bucket organization, IAM policies, event hooks, and multi-platform hosting options, MinIO can operate across local machines, Docker, Kubernetes, and cloud VMs. While it eliminates vendor lock-in and incurs no direct usage fees, MinIO does require responsible management of infrastructure for backups and high availability.
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React library for LLMs
🔗 https://llm-ui.com/
TLDR llm-ui is a React library that provides UI components for integrating Large Language Models into web applications. It works universally with any LLM model by operating on the model's output string, supporting popular services like ChatGPT, Claude, Ollama, Mistral, Hugging Face, and LangChain. The library aims to simplify the process of displaying LLM responses in React-based user interfaces.
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How Netflix Uses Java to Stream to 200M+ Users
🔗 https://amigoscode.com/blogs/how-netflix-uses-java-to-stream-to-200m-users
TLDR Netflix uses Java to manage a complex backend that streams 250 million hours of content daily. They transitioned from a monolithic architecture to microservices, leveraging Java for its concurrency, scalability, and rich ecosystem. Influential tools developed by Netflix include Eureka for service discovery and Hystrix for fault tolerance, which are integrated with Java to optimize performance and reliability across their AWS platform. Their approach and contributions have significantly impacted modern backend systems.
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Plate - Rich-text editor with AI, MCP, and shadcn/ui
🔗 https://platejs.org/
TLDR Plate Create blockquotes to emphasize important information or highlight quotes from external sources. This is suitable for certain scenarios, there are times when you want users to be able to paste content while preserving its formatting. To achieve this, your editor should be capable of handling 'text/html' data.
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Seamlessly Blend PHP with Node.js
🔗 https://blog.platformatic.dev/seamlessly-blend-php-with-nodejs
TLDR Platformatic introduces php-node, a Node.js module that allows developers to embed PHP within Node.js applications. The module utilizes Rust to execute PHP applications in a multi-threaded environment, providing enhanced performance and seamless integration. Key features include seamless integration, multi-threaded processing, improved performance, and a unified development environment. Use cases range from migrating legacy PHP apps to building hybrid applications. The post also provides examples of running PHP and WordPress inside a Node.js server.
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Podman vs. Docker: Containerization Tools Comparison
🔗 https://spacelift.io/blog/podman-vs-docker
TLDR Podman and Docker are two leading container platforms offering distinct features. Podman, developed by Red Hat, operates daemonless and supports rootless containers, enhancing security and system integration. Docker, highly popular for its ease of use, operates on a daemon-based architecture and has a rich ecosystem with broad third-party support. Both tools use OCI-compliant images allowing interoperability. While Docker's Swarm mode facilitates orchestration, Podman's design aligns closely with Kubernetes. Each tool is suitable for different use cases, with Podman excelling in secure, system-integrated environments and Docker being ideal for general development workflows.
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Astro 5.8
🔗 https://astro.build/blog/astro-580
TLDR Astro 5.8 has been released, requiring Node.js version 20.3.0 or higher, as Node.js 18 has reached end-of-life. While Astro will temporarily support Node.js 18.20.8, it's recommended to upgrade to Node.js 22 soon. Bug fixes are addressed and a CLI tool is available for easy upgrades.
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Claude 4: You better stop coding now
Claude 4, recently released by Anthropic, is a powerful AI model designed for advanced coding tasks, offering two versions: Sonnet 4 and Opus 4. The model excels in agentic mastery, multimodal tool integration, and efficient coding without hallucinations, setting itself apart from competitors like Gemini and GPT. With features catering to structured workflows and native tool integration, Claude 4 is poised to become a preferred choice for developers.
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GitLab vs GitHub : Key Differences in 2025
GitLab and GitHub are leading Git-hosting platforms with distinctive features. GitLab offers a fully integrated DevOps platform including CI/CD, security scanning, and infrastructure management out of the box, making it ideal for enterprises. GitHub, best known for its code hosting and collaboration capabilities, relies on third-party tools for extensive DevOps functionalities but excels in ease of use, community support, and integrations. Both platforms support AI-powered coding assistants, but GitLab's additional security and compliance features provide an edge for large organizations.
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Darklang Goes Open Source
https://api.daily.dev/r/z6afZQaCY
Darklang has transitioned from a source-available to fully open source model under Apache License 2.0 as part of restructuring from Dark Inc. to Darklang Inc. The decision was driven by user feedback, evolution toward local-first development with CLI support, and new business opportunities in developer tools. The platform now supports both cloud deployment and self-hosting while maintaining its core features like invisible infrastructure and trace-driven development
https://api.daily.dev/r/z6afZQaCY
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Spring Vault 4.0.0-M1
available
Spring.io
available
Spring Vault 4.0.0-M1 milestone release is now available, bringing updates to the Spring integration library for HashiCorp Vault. This milestone version provides
developers with early access to new features and improvements for managing secrets and security configurations in Spring applications.
Spring.io
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LeetCode Meditations: A Visualized Tour of DSA Concepts (A Handbook)
@computer_science_and_programming
A comprehensive handbook covering fundamental data structures and algorithms concepts through visual explanations and code examples. Topics include arrays, hash tables, two pointers technique, sliding window, stacks, binary search, linked lists, trees, heaps, and backtracking. Each concept is explained with practical implementations in JavaScript, TypeScript, and Python, along with time and space complexity analysis. The guide emphasizes understanding core principles rather than memorizing specific problem solutions.
@computer_science_and_programming
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JavaScript Animation Engine
https://animejs.com/?ref=dailydev
Anime.js is a versatile JavaScript animation library offering several features, including rotating objects, creating motion paths, and animating SVG paths. Users can create timelines, apply staggered animations, and make elements draggable with customizable easing options. The library also supports advanced configurations like spring physics and media query-based animations.
https://animejs.com/?ref=dailydev
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GPT-4.1 Prompting Guide
@computer_science_and_programming
The post provides a comprehensive guide on GPT-4.1 prompting using the OpenAI API. It includes open-source examples, advanced techniques, and detailed walkthroughs, empowering developers to efficiently utilize GPT-4.1 capabilities. The guide also encourages sharing your own examples and insights for further learning.
@computer_science_and_programming
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flurries of latent creativity
@computer_science_and_programming
A developer shares their weekend project of building a complete compiler from scratch, creating a simplified BASIC variant called toybasic that transpiles to Go code. The implementation uses three stages: a lexer built with nex for tokenization, a parser using goyacc for syntax tree generation, and a custom Go compiler that walks the tree to generate equivalent Go code. The project demonstrates practical compiler construction using modern tools while working with a simple but complete programming language
@computer_science_and_programming
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