Kitten TTS: Ultra-lightweight, offline text-to-speech for any device
Kitten TTS . - Open-source, highly efficient text-to-speech model with 15 million parameters and <25MB size.\n. - CPU-optimized, runs offline on virtually any device including embedded systems without needing GPUs.\n. - Offers multiple premium, expressive voices with real-time synthesis speeds (~5x real-time on desktop CPUs).\n. - Developer preview with fast load times (~700ms on high-end hardware); voice quality is good but slightly artificial.\n. - Licensed under Apache-2.0, enabling wide integration without cloud dependence or license restrictions.\n. - Sparks discussion about the future of tiny, offline AI models for privacy, speed, and low-power environments.\n. - Setup complexity around Python environments remains a barrier for some users.. . 9-bit Bytes: An Alternate History of Computing. - Explores the hypothetical impact if 9-bit bytes had replaced 8-bit as the standard.\n. - Expands IPv4 addresses from 32 to 36 bits, postponing address exhaustion and easing NAT/IPv6 adoption.\n. - Extends UNIX timestamps range to year 3058, eliminating the 2038 problem.\n. - Unicode expanded to 18 bits, accommodating over 262,000 characters natively, avoiding current compromises.\n. - Enables 36-bit pointers supporting up to 32GB process memory on 32-bit systems.\n. - Other benefits include larger AS numbers, port IDs, cleaner instruction sets, and better color encoding.\n. - Challenges include necessary network protocol evolution (TCP sequence numbers) and adapting hardware/kernels to non-power-of-two byte sizes.\n. - Suggests these manageable tradeoffs would have improved many fundamental standards and postponed technical constraints.. . Claude Code IDE for Emacs. - Deep integration of Claude Code AI assistant into Emacs using the Model Context Protocol (MCP).\n. - Provides bidirectional awareness: Claude can run within Emacs and use its editing features, project management, LSP, and Elisp functions.\n. - Supports automatic project detection, multi-session buffers, terminal color integrations, and access to xref, tree-sitter, imenu, Flycheck/Flymake diagnostics, and ediff diff views.\n. - Exposes custom user Emacs functions to AI via MCP tools, enabling domain-specific workflows and programmable AI commands.\n. - Supports Emacs 28.1+; setup involves standard Emacs packaging and a separate Claude Code CLI install.\n. - Enables complex queries such as project-wide symbol references or syntax tree analysis with AI deeply embedded in the editor context.\n. - Early-stage, with debug logs and workarounds for terminal bugs, but demonstrates a new level of AI-assisted IDE integration for Emacs users.. . Rethinking DOM from First Principles (Steven Wittens). - The DOM and core web platform have stagnated, burdened by legacy design, excessive complexity, and bloated APIs (>350 properties per node).\n. - CSS conflates text styling (inheritance) and layout (containment), resulting in awkward layout code and performance pitfalls.\n. - Modern UI development on the web involves "kitbashing" fragmented technologies (HTML/CSS/SVG) and manual behavior management.\n. - Proposes a radical redesign: a minimalist, multi-threaded, asynchronous data model with first-class layout and GPU acceleration.\n. - Highlights projects like Use.GPU’s minimal HTML-like renderer as promising alternatives.\n. - Calls for browsers designed for clean UI models that shed legacy constraints, enabling better performance and developer experience.\n. - Emphasizes that current web platform evolution is incremental patchwork rather than foundation-led innovation.. . Jules: Google’s Asynchronous Coding Agent Now Public. - Jules, powered by Gemini 2.5 Pro, exits beta with UI polish, bug fixes, GitHub issues and multimodal integration.\n. - Uses structured AI planning for improved code quality, supporting asynchronous workflows where users submit tasks and return for results later.\n. - Offers tiered usage: Introductory, AI Pro (5x capacity), and AI Ultra (20x capacity) with free AI Pro for eligible college students.\n. - Fits mobile and limited-time coding scenarios, enabling coding on-the-go with async task management.\n. - User feedback highlights uneven quality across tasks, beneficial rapid prototyping, but sometimes inferior to competitors like Claude Code or GitHub Copilot.\n. - Google’s fragmented AI product ecosystem complicates user experience with multiple separate subscriptions and interfaces.\n. - Demonstrates growing interest in asynchronous AI coding assistants but reflects ongoing challenges in coherence, documentation, and UI consistency in the AI coding space....