# Offline Published articles for Offline. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## GNOME 51 released DevFeed: [GNOME 51 released]() Original publisher: [Read original article]() Author: corbet Published: 2026-09-17T13:08:12Z Content type: release Language: en Sources: [LWN.net]() Topics: [version](), [App](), [data](), [interface](), [file]() Tags: [application](), [changes](), [data](), [desktop](), [file](), [gnome](), [gnome-51](), [improvements](), [interface](), [maps](), [offline](), [performance](), [transit](), [version]() ### AI overview GNOME 51 has been released with performance improvements, offline data and improved transit information in Maps, a new file previewer interface, and other changes. ### Source excerpt Version 51 of the GNOME desktop environment has been released. The list of changes includes a number of performance improvements, offline data and better transit information in the Maps application, a new interface for the file previewer, and more. ## GNOME 51 Released With Improved Frame Scheduling, Many App Improvements DevFeed: [GNOME 51 Released With Improved Frame Scheduling, Many App Improvements]() Original publisher: [Read original article]() Author: Michael Larabel Published: 2026-09-16T16:25:21Z Content type: news Language: en Sources: [Phoronix]() Topics: [releases](), [Wayland](), [Release notes](), [Software](), [ui](), [legacy](), [Nvidia]() Tags: [desktop](), [desktop-linux](), [driver](), [experience](), [faster](), [improvements](), [legacy](), [linux-benchmarking](), [linux-hardware-benchmarks](), [linux-hardware-reviews](), [linux-how-to](), [linux-performance](), [linux-server-benchmarks](), [notes](), [nvidia](), [offline](), [open-source-graphics](), [other](), [phoronix](), [phoronix-test-suite](), [protocols](), [release](), [release-notes](), [settings](), [software](), [time](), [ubuntu](), [ubuntu-benchmarks](), [ubuntu-hardware](), [ui](), [wayland](), [workstation]() ### AI overview GNOME 51 has been released with improved frame scheduling and desktop responsiveness, new Wayland protocol support, removal of legacy NVIDIA EGLStreams driver support, and updates to several GNOME applications and settings. ### Source excerpt Right on schedule and in time for appearing in the likes of Ubuntu 26.10 and Fedora Workstation 45, the GNOME 51 desktop is officially released... ## Khan Academy Uses Local Storage and Request Queues to Handle Offline Actions DevFeed: [Khan Academy Uses Local Storage and Request Queues to Handle Offline Actions]() Original publisher: [Read original article]() Author: Khan Academy Published: 2015-08-17T22:00:00Z Content type: article Language: en Sources: [Khan Academy]() Topics: [LocalStorage](), [client](), [Code](), [Internet](), [servers]() Tags: [architecture](), [change](), [code](), [engineering](), [function](), [hints](), [linear](), [local](), [news](), [offline](), [queue](), [request](), [server](), [web-frontend]() ### AI overview This article explains how Khan Academy addressed offline hint cheating by changing the client's request architecture. Actions are stored in local storage and placed in a queue for retry when connectivity returns, with linear backoff to avoid repeated requests during outages. ### Source excerpt By Phillip Lemons The problem Recently, a number of students on Khan Academy found a way to cheat ... Read more ## Mastering Edge AI on Raspberry Pi with LiteRT and Gemma DevFeed: [Mastering Edge AI on Raspberry Pi with LiteRT and Gemma]() Original publisher: [Read original article]() Author: Lu Wang; Terry Heo; Naushir Patuck; José María Casanova Published: 2026-09-12T11:04:33.891311Z Content type: tutorial Language: en Sources: [Google Developers Blog]() Topics: [LiteRT](), [On-device AI](), [Local AI](), [AI, ML & Data Engineering](), [Google AI](), [cpu](), [Security, Privacy and Abuse Prevention]() Tags: [cli](), [cpu](), [edge](), [gemma](), [gpu](), [inference](), [litert](), [offline](), [on-device](), [real-time](), [robotics]() ### AI overview The article explains how to deploy Gemma models with LiteRT on a Raspberry Pi for local, real-time edge AI applications such as robotics. It highlights LiteRT-LM, CPU and GPU optimization, and reported performance figures for Gemma 4 E2B on Raspberry Pi 5. ### Source excerpt Deploying secure, real-time Edge AI on Raspberry Pi is now simplified using LiteRT and lightweight Gemma open models. LiteRT optimizes CPU and GPU performance, delivering fast token speeds for models like Gemma4, enabling real-time local reasoning for robotics. Developers can quickly convert, quantize, and run these models using the lightweight LiteRT CLI tool. Support for Hailo AI accelerators is also coming very soon. ## Refreshing the Travel-Time Map Behind Lyft's Marketplace: Rebuilding Neighborhood Reachability... DevFeed: [Refreshing the Travel-Time Map Behind Lyft's Marketplace: Rebuilding Neighborhood Reachability...]() Original publisher: [Read original article]() Author: Manjunath Shettar Published: 2026-09-10T16:12:28Z Content type: article Language: en Sources: [Lyft Engineering - Medium]() Topics: [dataset](), [airflow]() Tags: [airflow](), [data-processing](), [feature-engineering](), [latency](), [lyft](), [offline](), [tea]() ### AI overview Lyft describes rebuilding its Neighborhood Reachability Signals: offline, regional travel-time matrices between geohash-6 cells and their associated neighborhood-center lists. The refresh replaces older static data and is intended to support marketplace pricing, driver guidance, and demand heatmaps, with future work aimed at time-aware travel times. ### Source excerpt Refreshing the Travel-Time Map Behind Lyft's Marketplace: Rebuilding Neighborhood Reachability Signals Every time Lyft calculates pricing to balance a market, nudges a driver toward an under-served pocket of a city, or paints a heatmap of where demand is building, there is a quiet lookup table doing work in the background. It answers a deceptively simple question: how long does it take to get from here to there?, for millions of pairs of places, across hundreds of regions. That lookup table is the Neighborhood Reachability Signal, and for years large parts of it were frozen in a snapshot of the world from 2018-2019. This is the story of how we rebuilt it, why a refresh substantial enough to be worth adopting was what finally moved Pricing to switch, the cleanly positive results that came out of that switch, and where we're taking it next, from one static file per region to time-aware travel times that change with the rhythm of the day. What is a Neighborhood Reachability Signal? A geohash is a compact way of carving the world into a grid of cells. At geohash-6 resolution, each cell is roughly the size of a few city blocks. Slice a region into geohash-6 cells and you get a clean, discrete coordinate system for "neighborhoods" that downstream systems can reason about. The Forecasting & Real-Time Optimization (FORTOP) team produces the Neighborhood Reachability Signals dataset, which consists of two companion files for each region: Neighborhood Reachability Matrix: the estimated travel time, in minutes, between the centers of pairs of geohash-6 cells. Think of it as a sparse origin-to-destination travel-time matrix for a region. Neighborhood Centers: the list of all geohashes that appear in the ETA files for that region, i.e. the "vocabulary" of cells that the marketplace is allowed to talk about. Both files are generated offline on a schedule by an Airflow DAG. They are static in the sense that they are precomputed and shipped, rather than queried live (which is exact ## How to Get Started With Ollama DevFeed: [How to Get Started With Ollama]() Original publisher: [Read original article]() Author: Real Python Published: 2026-09-01T14:00:00Z Content type: tutorial Language: en Sources: [Real Python]() Topics: [Language models](), [SDKs]() Tags: [ai](), [apps](), [how-to](), [large-language-models-llms](), [learn](), [local](), [models](), [offline](), [open-source](), [privacy](), [python](), [text-generation](), [tutorial]() ### AI overview A video course on using Ollama and its Python SDK to run local LLMs, generate text, and build offline-capable AI applications. ### Source excerpt Learn how to install Ollama, pull local models, and connect them to your Python code using the chat and text generation interfaces. ## Running Ollama Locally with Podman on Fedora Linux DevFeed: [Running Ollama Locally with Podman on Fedora Linux]() Original publisher: [Read original article]() Author: Yazan Monshed Published: 2026-08-05T08:00:00Z Content type: article Language: en Sources: [Fedora Magazine]() Topics: [Fedora](), [Large Language Model](), [Linux](), [Open Source Models & Datasets](), [API](), [cURL](), [GPU]() Tags: [ai-development](), [api](), [curl](), [fedora-project-community](), [gpu](), [large-language-models-llms](), [linux](), [llama](), [nvidia](), [offline](), [ollama](), [open-source](), [podman](), [privacy](), [python](), [terminal](), [using-software]() ### AI overview This article explains how to run Ollama locally in a Podman container on Fedora Linux. It covers installing or verifying Podman, creating persistent storage for model weights, running the Ollama container, downloading Llama 3, optionally enabling Nvidia GPU acceleration, and using Ollama's local REST API with curl. ### Source excerpt Running Large Language Models (LLMs) locally has become increasingly popular for development, privacy, and offline testing. Ollama makes this incredibly straightforward, allowing you to run models like Llama 3 or Mistral directly on your machine. By leveraging Podman on Fedora Linux, you can isolate Ollama inside a container. This approach keeps your host system clean [...] ## Building Local-First Apps: The Complete Guide to Offline-First Database Sync DevFeed: [Building Local-First Apps: The Complete Guide to Offline-First Database Sync]() Original publisher: [Read original article]() Author: Jeff Olson Published: 2026-07-27T00:00:00Z Content type: tutorial Language: en Sources: [Turso Blog]() Topics: [Local-First](), [Turso](), [SQLite](), [Databases](), [Back end]() Tags: [architecture](), [auth](), [backend](), [database](), [databases](), [guide](), [local-first](), [offline](), [sqlite](), [storage](), [sync](), [turso]() ### AI overview A complete guide to building local-first, offline-first applications. It explains the local-first model, where data lives on the device and the cloud provides backup, synchronization, and coordination, then introduces Turso Sync and SQLite-based approaches. The article also covers architecture patterns and practical challenges including conflict resolution, authentication, storage management, and partial synchronization. ### Source excerpt What local-first means, how Turso Sync works, three architecture patterns, and how to handle the hard parts: conflicts, auth, storage, and partial sync. ## Calendar API: Local Calendars, Cloud Sync, and Conflict Handling DevFeed: [Calendar API: Local Calendars, Cloud Sync, and Conflict Handling]() Original publisher: [Read original article]() Author: Shai Almog Published: 2026-07-25T00:00:00Z Content type: release Language: en Sources: [CodeName One]() Topics: [API](), [cross-platform](), [Concurrency](), [Cloud](), [Google Calendar](), [Android](), [iOS](), [macOS](), [Microsoft](), [JavaScript](), [HTTP](), [OAuth]() Tags: [android](), [api](), [apis](), [apple](), [backend](), [cloud](), [concurrency](), [cross-platform](), [google](), [http](), [ios](), [javascript](), [macos](), [oauth](), [offline](), [storage](), [sync](), [synchronization](), [work]() ### AI overview The article introduces a cross-platform calendar API that unifies local calendars and cloud providers through a capability-based model. It covers events, tasks, recurrence, time zones, offline mutations, optimistic concurrency, provider synchronization, and conflict handling. ### Source excerpt The new calendar API handles local calendars, cloud providers, recurrence, conflicts, and offline changes through one capability-based model. ## Check out the New Node.js API Documentation Preview DevFeed: [Check out the New Node.js API Documentation Preview]() Original publisher: [Read original article]() Published: 2026-07-24T19:00:00Z Content type: release Language: en Sources: [Node.js Blog]() Topics: [Node.js](), [SDKs](), [migration]() Tags: [ai](), [announcement](), [api](), [documentation](), [javascript](), [llms](), [migration](), [node-js](), [offline](), [search](), [tools]() ### AI overview Node.js has released a preview of redesigned API documentation. It retains content from the existing Markdown sources while adding built-in search, a shared site design, llms.txt, and accessibility for offline or JavaScript-disabled use. ### Source excerpt Node.js® is a free, open-source, cross-platform JavaScript runtime environment that lets developers create servers, web apps, command line tools and scripts. ## Remote Asset Libraries DevFeed: [Remote Asset Libraries]() Original publisher: [Read original article]() Author: Julian Eisel Published: 2026-07-22T12:26:48Z Content type: release Language: en Sources: [Blender]() Topics: [Library](), [Self-hosted](), [Internet]() Tags: [download](), [general-development](), [internet](), [libraries](), [offline](), [optional](), [remote](), [self-hosting]() ### AI overview Blender's Remote Asset Libraries let users browse assets stored on remote servers and download them only when needed. They support optional online content, self-hosting, and offline access after assets are downloaded. ### Source excerpt Browse assets stored online and download them only when needed. ## What Matters Most for NoSQL Migrations DevFeed: [What Matters Most for NoSQL Migrations]() Original publisher: [Read original article]() Author: Cynthia Dunlop Published: 2026-07-21T13:44:46Z Content type: tutorial Language: en Sources: [ScyllaDB]() Topics: [NoSQL](), [Database Migration](), [migration](), [data-architecture](), [data](), [App]() Tags: [apps](), [community](), [complexity](), [data](), [data-modeling](), [database](), [database-migration](), [databases](), [how-to](), [migration](), [offline](), [performance](), [scale](), [validation](), [what-matters]() ### AI overview This article presents practical guidance for planning, executing, and de-risking NoSQL database migrations. It compares online and offline approaches and emphasizes schema migration, data movement, and validation, with attention to performance, scale, complexity, and disruption. ### Source excerpt How to prioritize the things that matter most for planning, executing and de-risking your NoSQL database migration ## Meeting Notes - A Free Desktop App for Tracking 1:1s DevFeed: [Meeting Notes - A Free Desktop App for Tracking 1:1s]() Original publisher: [Read original article]() Author: Dean Hume Published: 2026-06-29T10:16:48Z Content type: article Language: en Sources: [Dean Hume]() Topics: [App](), [meetings](), [Local-First](), [asr](), [Whisper](), [Open Source](), [Markdown]() Tags: [app](), [autosave](), [desktop](), [free](), [meetings](), [notes](), [offline](), [on-device](), [open-source](), [recording](), [speech-to-text](), [technical-leadership](), [technical-program-manager](), [whisper](), [writing]() ### AI overview The article introduces Meeting Notes, a free, open-source Windows desktop app for organizing 1:1 notes by person. It supports topic tags, Markdown, autosave, voice recording, and offline speech-to-text using Whisper, with data and audio kept on the device. ### Source excerpt Meeting Notes is a free offline desktop app for 1:1s. Organise notes by person, tag topics, and transcribe meetings on-device with Whisper. ## Open source Chrome extension recreates LinkedIn from your data exports DevFeed: [Open source Chrome extension recreates LinkedIn from your data exports]() Original publisher: [Read original article]() Author: Alex Ewerlöf Published: 2026-06-28T17:41:27Z Content type: article Language: en Sources: [Alex Ewerlof Notes]() Topics: [Extension](), [Chrome extension](), [Open Source](), [App](), [data](), [CSV](), [GitHub](), [Single-page application (SPA)]() Tags: [app](), [chrome](), [chrome-extension](), [code](), [csv](), [extension](), [gdpr](), [github](), [offline](), [open-source]() ### AI overview The article introduces LinkedOut, a free open-source Chrome extension and offline single-page application that lets users inspect and browse data exported from LinkedIn. It describes the author's findings about the breadth of the export and explains how the app processes the data locally without gathering or transmitting it. ### Source excerpt An open source extension to recreate LinkedIn from your data exports ## Use your own language model key in VS Code DevFeed: [Use your own language model key in VS Code]() Original publisher: [Read original article]() Author: Kayla Cinnamon Published: 2026-06-18T00:00:00Z Content type: article Language: en Sources: [Visual Studio Code - Code Editing. Redefined.]() Topics: [AI Chat]() Tags: [agent](), [agents](), [ai](), [anthropic](), [api](), [api-keys](), [azure](), [blog](), [copilot](), [embeddings](), [extension](), [gemini](), [github-copilot](), [model](), [models](), [offline](), [openai](), [vs-code]() ### AI overview The article explains how to use bring your own key (BYOK) or local language models in VS Code chat and agent workflows. It covers supported providers, offline local-model use, and limitations such as BYOK not applying to standard code completions. ### Source excerpt Learn how to use bring your own key (BYOK) in VS Code to add models from providers like Azure, Anthropic, Gemini, OpenAI, Huggingface, OpenRouter, or use a local model with Ollama, Foundry Local, and more. Read the full article ## Scaling beyond one: How Airbnb evolved its data architecture for a multi-product world DevFeed: [Scaling beyond one: How Airbnb evolved its data architecture for a multi-product world]() Original publisher: [Read original article]() Author: Patrick Lam Published: 2026-06-09T17:01:02Z Content type: article Language: en Sources: [The Airbnb Tech Blog - Medium]() Topics: [data-architecture](), [Data Infrastructure](), [data-modeling](), [data]() Tags: [analytics](), [architecture](), [data](), [data-architecture](), [data-engineering](), [data-infrastructure](), [data-modeling](), [engineering](), [offline](), [post](), [technology]() ### AI overview Airbnb's data and analytics engineering teams evolved a decade-old offline data warehouse to support Homes, Experiences, and Services. The article examines the trade-offs between separate product-specific data models and a unified monolithic model while describing the need for a consistent, flexible, and scalable data foundation. ### Source excerpt How Airbnb's data engineers and analytics engineers built a consistent and flexible data modeling framework to support the expansion into Homes, Experiences, and Services. By: Patrick Lam, Namrata Lamba, Jamie Stober With the May 2025 Summer Release, Airbnb redesigned its app, relaunched Experiences, and debuted Services, pushing us beyond our traditional Homes focus. For the data teams, this meant rapidly evolving a decade-old infrastructure to integrate two brand-new product pillars. Our data engineers and analytics engineers rose to the challenge by building a consistent and flexible framework to serve as a robust and scalable data foundation for the next decade of growth. But getting there wasn't straightforward. This fundamental shift surfaced a critical question for our data organization: How do you evolve your offline data architecture to support new product lines without introducing disorder in vital analytics services? We knew the approach we took would have long-lasting implications. A fragmented strategy risked creating data silos, inconsistent analytics, and a tangled web of technical debt that would likely slow down future innovation. In this post, we'll take you behind the scenes to share key decisions that we made, the framework that emerged, and the lessons that helped reshape our offline data warehouse for the future. Note that we focus specifically on our offline data warehouse (the analytics-oriented data infrastructure owned by our data engineers and analytics engineers) rather than the online data systems that serve the app directly, as the two domains have fundamentally different requirements, constraints, and design philosophies that warrant separate treatment. The core dilemma: separate vs. monolithic The first and most critical question was how to structure offline data for the new, three-product world, with Homes, a refreshed Experiences product, and the new Services offering. This involved a trade-off between two main approaches: Separate ## Build new features using built-in AI in Chrome DevFeed: [Build new features using built-in AI in Chrome]() Original publisher: [Read original article]() Author: Thomas Steiner GitHub LinkedIn Mastodon Bluesky Homepage Published: 2026-05-26T07:00:00Z Content type: article Language: en Sources: [developer.chrome.com: Blog]() Topics: [AI Chat](), [SDKs](), [User interface design]() Tags: [accessibility](), [ai](), [alt-text](), [api](), [apis](), [chrome](), [firebase](), [inference](), [json](), [multimodal](), [offline](), [on-device](), [privacy](), [web-apps]() ### AI overview The article describes Chrome's built-in AI APIs for adding on-device writing, summarization, structured output, image accessibility, rewriting, and translation features to web applications. ### Source excerpt Learn more about the talk given at Google I/O 2026 by Thomas Steiner. ## The Architecture Of Local-First Web Development DevFeed: [The Architecture Of Local-First Web Development]() Original publisher: [Read original article]() Author: hello@smashingmagazine.com (Durgesh Pawar) Published: 2026-05-06T10:00:00Z Content type: opinion Language: en Sources: [Articles on Smashing Magazine -- For Web Designers And Developers]() Topics: [Local-First](), [Web Development](), [web applications](), [PWA](), [React](), [backends](), [Database](), [GraphQL](), [Redis](), [Cache]() Tags: [api](), [apps](), [coding](), [data](), [database](), [local-first](), [offline](), [performance](), [react](), [redis](), [web](), [web-apps](), [web-development]() ### AI overview An opinionated examination of local-first web development, prompted by a project management app that became nearly unusable over a poor connection. The article contrasts local-first architecture with offline-first approaches and discusses the practical lessons learned from using local-first patterns in production apps. ### Source excerpt An honest perspective on building local-first web apps in 2026, written for developers who've been doing this long enough to be skeptical of silver bullets. ## BEGA joins Works with Home Assistant DevFeed: [BEGA joins Works with Home Assistant]() Original publisher: [Read original article]() Author: Miranda Bishop Published: 2026-05-05T00:00:01Z Content type: news Language: en Sources: [Home Assistant]() Topics: [Home Assistant]() Tags: [community](), [devices](), [ecosystem](), [energy](), [offline](), [safety](), [smart](), [smart-home](), [sustainability](), [tech](), [works-with-home-assistant]() ### AI overview BEGA has joined the Works with Home Assistant program, bringing a large portfolio of certified architectural lighting products. Its BEGA Smart system uses Zigbee, supports flexible expansion, and works offline without an internet connection. The article also highlights BEGA's repairable fixtures and replaceable components, including outdoor lighting options. ### Source excerpt How do you more or less double the number of Works with Home Assistant-certified devices available to our community? Have BEGA join the program! This German firm has spent more than 75 years designing a wide range of architectural lighting that sets the industry standard: and now they're bringing that expertise to your smart home. Bright BEGA-nnings If you haven't heard of BEGA before, you may have admired their work without realizing it. That's because they produce the kind of beautifully engineered fixtures you see gracing the facades of fancy hotels, elegant public buildings, and stylish modern homes worldwide. They're probably better known for this kind of work than for smart home tech, which is precisely what makes their joining the Works with Home Assistant program so exciting. Because BEGA aren't just dipping a toe in: they're bringing what's almost certainly the largest single addition of certified devices we've ever had in one go: enough to very nearly double the number of certified products in the program! And it's not just the volume that impresses. BEGA Smart - their Zigbee-powered smart lighting system - is flexible, expandable, and designed to work entirely offline, with no internet connection required. BEGA: putting the smart into smart home lighting. "With BEGA Smart, we aim to combine high-quality architectural lighting with intelligent control. Integrating with Home Assistant allows us to bring our lighting solutions into an open and flexible smart home ecosystem that many of our customers already value. By doing so, we enhance comfort, safety, and energy efficiency while enabling new ways to experience light. We're excited to support the community and be part of this ecosystem." - Heinrich Gantenbrink, Managing Partner at BEGA Beyond beautiful design BEGA's premium positioning isn't only about aesthetics. Their commitment to repairability also aligns well with the Open Home Foundation's sustainability principles. Rather than treating a luminaire a ## How Sample Vault syncs gigabyte-scale databases from cloud to local with Turso DevFeed: [How Sample Vault syncs gigabyte-scale databases from cloud to local with Turso]() Original publisher: [Read original article]() Author: Jeff Olson Published: 2026-05-04T00:00:00Z Content type: article Language: en Sources: [Turso Blog]() Topics: [Turso](), [Local-First](), [Databases](), [Cloud](), [data](), [App](), [Artificial Intelligence]() Tags: [ai](), [case-study](), [cloud](), [databases](), [embedded-replicas](), [local](), [offline](), [sync](), [turso]() ### AI overview Sample Vault uses Turso to synchronize gigabyte-scale, per-user audio metadata databases bidirectionally between the cloud and local devices. The local replicas support offline queries across libraries containing more than 100,000 audio files, while cloud processing generates spectral, classification, genre, mood, and AI-derived metadata. ### Source excerpt Sample Vault uses Turso for cloud-to-local bidirectional sync with per-user databases, enabling offline-first access to gigabyte-scale audio metadata without custom sync code. ## GPT-5.5 System Card DevFeed: [GPT-5.5 System Card]() Original publisher: [Read original article]() Published: 2026-04-23T11:00:00Z Content type: article Language: en Sources: [OpenAI News]() Topics: [Security & Privacy](), [API](), [Code](), [Deployment]() Tags: [api](), [code](), [cybersecurity](), [deployment](), [gpt](), [offline](), [release](), [safety](), [tools]() ### AI overview GPT-5.5 is presented as a model for complex real-world work, including coding, online research, information analysis, document and spreadsheet creation, and tool use. The system card describes predeployment safety evaluations, targeted red-teaming, feedback from nearly 200 early-access partners, and safeguards intended to reduce misuse while preserving beneficial uses. It also notes separate consideration of GPT-5.5 Pro and additional safeguards for deployment in the API. ### Source excerpt GPT-5.5 is a new model designed for complex, real-world work, including writing code, researching online, analyzing information, creating documents and spreadsheets, and moving across tools to get things done. Relative to earlier models, GPT-5.5 understands the task earlier, asks for less guidance, uses tools more effectively, checks it work and keeps going until it's done. ## How Vinted Serves Personalised Search Autocomplete DevFeed: [How Vinted Serves Personalised Search Autocomplete]() Original publisher: [Read original article]() Author: Justina Bartulevičienė Published: 2026-04-22T00:00:00Z Content type: article Language: en Sources: [Vinted]() Topics: [recommendation systems](), [data](), [systems](), [Learning]() Tags: [autocomplete](), [model](), [offline](), [performance](), [personalisation](), [pipeline](), [search]() ### AI overview Vinted describes the architecture and operation of its personalized search autocomplete service. The system generates candidate queries from product metadata and search logs, indexes and matches them with typo tolerance, and ranks suggestions using personalization and a Learning-to-Rank model. The service supports 24 languages and more than 50 country-language combinations, with 125 million queries and reported throughput of 4,700 queries per second at 31 ms P99. ### Source excerpt At Vinted, more than 20% of all search sessions now start with a click on an autocomplete suggestion. A few years ago, that number was below 8%. Autocomplete not only saves typing effort - it helps people discover listings they didn't know existed, and guides them toward successful searches. Today, across 24 languages and 50+ country-language combinations, we have a pool of 125 million different queries ready to suggest to users. Our service, svc-suggestions, runs on Vespa and matches and ranks 4,700 queries per second at 31 ms P99. ## ESP-IDF Installation Manager v0.8: Streamlined Setup for ESP-IDF Development DevFeed: [ESP-IDF Installation Manager v0.8: Streamlined Setup for ESP-IDF Development]() Original publisher: [Read original article]() Author: John Lee Published: 2026-03-02T00:00:00Z Content type: release Language: en Sources: [Blog on Developer Portal]() Topics: [ESP-IDF](), [cross-platform](), [Espressif](), [Package manager](), [CI/CD]() Tags: [beginner](), [blog](), [cross-platform](), [dependencies](), [eim](), [esp-idf](), [esp-idf-tool](), [espressif](), [gui](), [installation](), [linux](), [macos](), [offline](), [pipelines](), [release](), [reproducible-builds](), [toolchains](), [windows]() ### AI overview ESP-IDF Installation Manager v0.8 adds native package-manager installation methods, offline ESP-IDF installation, improved environment activation, CI/CD integration, and version management across Windows, macOS, and Linux. ### Source excerpt The ESP-IDF Installation Manager (EIM) v0.8 introduces simplified installation across Windows, macOS, and Linux through native package managers. This article covers the new release features, installation methods, offline capabilities, and headless usage for CI/CD pipelines. ## Introducing React Native Bindings for Turso DevFeed: [Introducing React Native Bindings for Turso]() Original publisher: [Read original article]() Author: Nikita Sivukhin Published: 2026-01-29T00:00:00Z Content type: release Language: en Sources: [Turso Blog]() Topics: [React Native](), [Turso](), [SQLite](), [Cloud](), [Android](), [iOS](), [TypeScript](), [API]() Tags: [android](), [apis](), [cloud](), [ios](), [offline](), [on-device](), [react-native](), [sqlite](), [sync](), [turso](), [typescript]() ### AI overview Turso announces official React Native bindings that combine an embedded SQLite-compatible database with optional bidirectional sync to Turso Cloud. The package targets on-device use on iOS and Android, while keeping asynchronous network and SDK logic in TypeScript. ### Source excerpt Our new React Native bindings ship Turso's embedded SQLite database, encryption, vector search, and bidirectional Turso Cloud sync to iOS and Android. [Next page]()