# hub Published articles for hub. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## IBM Quantum System Two Heads to Switzerland: 120-Qubit Nighthawk r2 at CSCS by End of 2026 DevFeed: [IBM Quantum System Two Heads to Switzerland: 120-Qubit Nighthawk r2 at CSCS by End of 2026]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-11T16:25:47Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [ibm](), [Quantum Computing](), [Supercomputing](), [Cloud](), [Algorithms](), [Optimization](), [Simulation and Design](), [Hardware]() Tags: [2026](), [ai](), [algorithms](), [amd](), [chemistry](), [cloud](), [collaboration](), [core](), [enterprise](), [financial-services](), [hardware](), [hub](), [ibm](), [infrastructure](), [manufacturing](), [optimization](), [processors](), [quantum](), [quantum-computing](), [science](), [simulation](), [supercomputing]() ### AI overview IBM and Lockheed Martin are establishing a quantum innovation hub at ETH Zurich, centered on an IBM Quantum System Two planned for installation at the Swiss National Supercomputing Centre by the end of 2026. The system will use IBM's 120-qubit Nighthawk r2 processor and support research in areas including chemistry, materials science, optimization, and financial services. ### Source excerpt IBM and Lockheed Martin are setting up a quantum innovation hub at ETH Zurich, and its core is Switzerland's first IBM Quantum System Two, to be installed at the Swiss National Supercomputing Centre (CSCS) in Lugano by the end of 2026. The hub comes out of an offset agreement with armasuisse, Switzerland's Federal Office for The post IBM Quantum System Two Heads to Switzerland: 120-Qubit Nighthawk r2 at CSCS by End of 2026 appeared first on StorageReview.com. ## Switzerland's first IBM Quantum System Two DevFeed: [Switzerland's first IBM Quantum System Two]() Original publisher: [Read original article]() Published: 2026-09-10T07:00:00Z Content type: article Language: en Sources: [IBM Research]() Topics: [Quantum Computing](), [ibm](), [Supercomputing]() Tags: [2026](), [collaboration](), [development](), [hub](), [ibm](), [industry](), [innovation](), [news](), [quantum](), [quantum-community](), [quantum-computing](), [quantum-network](), [quantum-systems](), [research](), [science](), [switzerland](), [technology](), [with]() ### AI overview IBM and Lockheed Martin are launching a quantum innovation hub at ETH Zurich, anchored by Switzerland's first IBM Quantum System Two. Expected to be operational by the end of 2026 at the Swiss National Supercomputing Centre in Lugano, it will expand quantum computing access for Swiss universities, startups, companies, and researchers. ### Source excerpt Lockheed Martin and IBM are launching a Swiss quantum innovation hub at ETH Zurich to advance research, industry collaboration, and workforce development. ## Async GRPO with LoRA across HF Jobs: a bucket, a proxy, and no NCCL DevFeed: [Async GRPO with LoRA across HF Jobs: a bucket, a proxy, and no NCCL]() Original publisher: [Read original article]() Author: Amine Dirhoussi; Quentin Gallouédec; Kashif Rasul; Sergio Paniego Published: 2026-09-10T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [lora](), [grpo](), [jobs](), [vllm](), [NCCL](), [async](), [hugging face]() Tags: [async](), [grpo](), [hub](), [hugging-face](), [jobs](), [llm](), [lora](), [nccl](), [open-source](), [rl](), [storage](), [trl](), [vllm]() ### AI overview This article describes asynchronous GRPO training with a LoRA adapter across separate Hugging Face Jobs. The adapter is synchronized to vLLM replicas through a shared Storage Bucket, while a proxy handles authentication, rollout routing, and adapter-load broadcasts. Five runs reduced the time for 500 steps from 3 hours 27 minutes to 53 minutes. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Introducing @huggingface/kernels: 200+ WebGPU Kernels for Local AI DevFeed: [Introducing @huggingface/kernels: 200+ WebGPU Kernels for Local AI]() Original publisher: [Read original article]() Author: Nico Martin; Joshua Published: 2026-09-01T00:00:00Z Content type: release Language: en Sources: [Hugging Face - Blog]() Topics: [webgpu](), [Local AI](), [Machine learning](), [Inference](), [benchmarking](), [GPU](), [Optimization]() Tags: [benchmark](), [gpu](), [hub](), [inference](), [javascript](), [kernels](), [local-ai](), [open-source](), [optimization](), [shaders](), [testing](), [webgpu]() ### AI overview Hugging Face releases @huggingface/kernels, a JavaScript library and collection of 207 versioned WebGPU kernel packages for browser-based local AI. It also introduces Fleet, a browser benchmarking and testing suite that gathers opted-in performance and correctness evidence across hardware. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## State of Open Models: Summer 2026 Observations DevFeed: [State of Open Models: Summer 2026 Observations]() Original publisher: [Read original article]() Author: Adina Yakefu; Apolinário from multimodal AI art; Irene Solaiman Published: 2026-08-14T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [Artificial Intelligence](), [Open Source](), [quantization](), [datasets](), [Nvidia](), [spaces](), [Hardware](), [Nemotron](), [qwen](), [Benchmark](), [API]() Tags: [api](), [artificial-intelligence](), [benchmark](), [community](), [datasets](), [hardware](), [hub](), [nemotron](), [nvidia](), [open-source](), [quantization](), [qwen](), [research](), [spaces]() ### AI overview This article examines the summer 2026 state of open models, highlighting rapid growth in public model repositories, datasets, and Spaces; the dominance of a small number of repositories in downloads; the rising scale of Chinese open models; differing model portfolio strategies; and the strong role of AMD, NVIDIA, and community quantization in making large models accessible. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets DevFeed: [Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets]() Original publisher: [Read original article]() Author: Sundar Raghavan; Steven Palma; Cagatay Cali; Arron Bailiss; Yin Song Published: 2026-08-13T17:16:04Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [lerobot](), [hugging face](), [cloud-infrastructure](), [dataset](), [SDKs](), [Command-line interface](), [Open Source]() Tags: [agents](), [apache](), [aws](), [cli](), [code](), [data](), [datasets](), [hub](), [hugging-face](), [lerobot](), [models](), [open](), [open-source](), [robots](), [storage](), [strands-agents](), [train](), [xet]() ### AI overview This article describes a continuous robotics data loop using Strands Agents, LeRobot, Hugging Face Hub, and Hugging Face Storage Buckets. It covers recording demonstrations, collecting episodes, training policies on growing datasets, deploying checkpoints, and using mutable Xet-backed storage to reduce repeated data transfers. ### Source excerpt Record, train, and deploy from one place with Strands Agents, LeRobot, and Hugging Face Storage Buckets You have an agent that can already record a demonstration and push it to the Hugging Face Hub. Now you want to run that loop continuously: collect episodes through the day, train a policy on the growing dataset, deploy it, and pull the next batch back to improve it. Run that loop once and every piece works. Run it every day and you start paying for the same byte transfers over and over. ## Agent Registry vs Agent Hub: Which one do you need? DevFeed: [Agent Registry vs Agent Hub: Which one do you need?]() Original publisher: [Read original article]() Author: Matar Peles Published: 2026-08-10T11:40:18Z Content type: comparison Language: en Sources: [Developer Experience & Platform Engineering Blog | Port]() Topics: [AI Agent](), [Microsoft](), [Security](), [bedrock](), [Claude](), [cursor]() Tags: [agent](), [agentic](), [agents](), [ai](), [apis](), [bedrock](), [claude](), [cursor](), [enterprise](), [governance](), [hub](), [microsoft](), [policy](), [registry](), [workflow]() ### AI overview The article compares AI agent registries and agent hubs. Registries provide governance by tracking agent identity, ownership, access boundaries, versions, lifecycle state, and policy approvals, while hubs help teams discover and reuse existing agents. It argues that organizations need both capabilities and can build them as one system to address agent sprawl. ### Source excerpt Compare agent registries and agent hubs to understand their roles, key differences, and which one your team actually needs. ## Meta is back with Muse Glimmer: local, agentic, multimodal, and open source DevFeed: [Meta is back with Muse Glimmer: local, agentic, multimodal, and open source]() Original publisher: [Read original article]() Author: Pedro Cuenca; merve; ben burtenshaw; Aritra Roy Gosthipaty Published: 2026-08-10T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [vlm](), [multimodal](), [Artificial Intelligence](), [hugging face](), [Benchmark](), [coding]() Tags: [agentic](), [artificial-intelligence](), [benchmark](), [hub](), [hugging-face](), [images](), [llama-cpp](), [llms](), [local](), [meta](), [model](), [multimodal](), [muse](), [open-source](), [videos](), [vllm](), [vlm](), [vlms]() ### AI overview Hugging Face presents Muse Glimmer, a local, agentic, multimodal, open-source 30B-parameter vision-language model developed with Meta. The article outlines its vision and language architecture, benchmark context, optional speculative decoding for faster generation, and support for both images and videos. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Baseten on Hugging Face Inference Providers 🔥 DevFeed: [Baseten on Hugging Face Inference Providers 🔥]() Original publisher: [Read original article]() Author: Alex Ker; Roland Crosby; Sid Shanker; Johan; Célina Hanouti; Simon Brandeis; Lucain Pouget; merve Published: 2026-08-06T00:00:00Z Content type: news Language: en Sources: [Hugging Face - Blog]() Topics: [AI Chat](), [SDKs]() Tags: [baseten](), [deepseek](), [enterprise](), [hub](), [hugging-face](), [inference](), [inference-providers](), [llms](), [partnerships](), [sdks](), [text-generation]() ### AI overview Baseten is now an Inference Provider on the Hugging Face Hub, offering conversational and text-generation access to supported open-weight LLMs. The integration is available through Hugging Face Python and JavaScript SDKs, with custom-key and Hugging Face-routed request modes. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Home Assistant: domótica autoalojada DevFeed: [Home Assistant: domótica autoalojada]() Original publisher: [Read original article]() Author: Antonio Pérez Published: 2026-08-03T00:00:00Z Content type: tutorial Language: es Sources: [tengoping.com]() Topics: [Home Assistant](), [Proxmox](), [Open Source](), [USB](), [Kernel]() Tags: [home-assistant](), [hub](), [kvm](), [lxc](), [os](), [proxmox](), [usb](), [vlan]() ### AI overview A Spanish tutorial explains how to self-host Home Assistant OS as a virtual machine on Proxmox. It recommends a full VM rather than LXC, discusses the Supervisor and add-ons, warns users to inspect community scripts, and covers updates, USB passthrough, dashboard access, and network isolation. ### Source excerpt Instala Home Assistant OS como VM en Proxmox, por qué conviene evitar el LXC, primeros pasos con el dashboard y cómo aislar tu domótica en su propia VLAN. ## AWS Weekly Roundup: AWS Builder Center at 1 year, Network Scanning in Security Hub, Loom for AWS, and more (July 13, 2026) DevFeed: [AWS Weekly Roundup: AWS Builder Center at 1 year, Network Scanning in Security Hub, Loom for AWS, and more (July 13, 2026)]() Original publisher: [Read original article]() Author: Esra Kayabali Published: 2026-07-13T16:18:20Z Content type: news Language: en Sources: [AWS News Blog]() Topics: [Amazon Web Services](), [Security]() Tags: [agents](), [amazon-aurora](), [amazon-elastic-container-service](), [amazon-elastic-kubernetes-service](), [amazon-sagemaker](), [announcements](), [aws](), [aws-security-hub](), [community](), [ecosystem](), [github](), [hub](), [launch](), [linux](), [mcp](), [news](), [platform](), [sandbox](), [security](), [spaces](), [week-in-review](), [workshops]() ### AI overview AWS Weekly Roundup highlights the first anniversary of AWS Builder Center, including its expansion into sandbox environments, workshops, Spaces, community features, and the Builders' Library. It also covers the launch of Network Scanning in AWS Security Hub, which probes resources from the public internet to identify actual reachability, alongside other weekly AWS announcements. ### Source excerpt AWS Builder Center turned one year old last week. Launched on July 9, 2025, the platform has grown from a community hub with Wishlist voting, community profiles, and a toolbox into a full ecosystem with sandbox environments, workshops, Spaces, and a Builders' Library. To mark the anniversary, Rick Suttles published a full feature timeline covering [...] ## 🤗 Kernels: Major Updates DevFeed: [🤗 Kernels: Major Updates]() Original publisher: [Read original article]() Author: Sayak Paul; Daniël de Kok; David Holtz Published: 2026-07-06T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [kernels](), [Security](), [Open Source](), [Nix](), [Git](), [systems]() Tags: [git](), [hub](), [kernel-builder](), [kernels](), [open-source](), [optimization](), [sandbox](), [security](), [updates]() ### AI overview Hugging Face's Kernels project introduces a first-class "kernel" repository type on the Hub, allowing users to inspect supported accelerators, operating systems, and backend versions. The update also adds trusted publishers, code signing, reproducible Nix-based builds, and embedded Git source identifiers to improve security and provenance. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Shipping huggingface\_hub every week with AI, open tools, and a human in the loop DevFeed: [Shipping huggingface\_hub every week with AI, open tools, and a human in the loop]() Original publisher: [Read original article]() Author: Lucain Pouget; Célina Hanouti Published: 2026-06-23T00:00:00Z Content type: tutorial Language: en Sources: [Hugging Face - Blog]() Topics: [releases](), [AI Chat]() Tags: [agents](), [ai](), [ci](), [github-actions](), [hub](), [huggingface-hub](), [maintainers](), [open-source](), [release](), [release-notes](), [tools](), [workflow]() ### AI overview A tutorial on automating a weekly huggingface_hub release workflow with GitHub Actions and open tools. It separates mechanical release tasks from AI-assisted drafting of release notes and announcements, while retaining human review for judgment-sensitive work. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot DevFeed: [From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot]() Original publisher: [Read original article]() Author: Sundar Raghavan; Cagatay Cali Published: 2026-06-17T10:18:05Z Content type: tutorial Language: en Sources: [Hugging Face - Blog]() Topics: [AI Bots](), [SDKs]() Tags: [agents](), [hardware](), [hub](), [hugging-face](), [inference](), [integration](), [lerobot](), [mesh](), [robots](), [strands-agents]() ### AI overview A tutorial for using the Strands Robots SDK and LeRobot to record simulated demonstrations, run policies, deploy the same agent code to physical hardware, and coordinate robot fleets. ### Source excerpt You have a robot, a folder of demonstration data on the Hugging Face Hub, and a new task you want it to learn. Today that takes five separate tools: one to record new demonstrations, another to train, a third to test in simulation, custom code to deploy on hardware, and yet another to coordinate when you have more than one robot. The pieces work on their own. They don't talk to each other. ## Agentic Resource Discovery: Let agents search DevFeed: [Agentic Resource Discovery: Let agents search]() Original publisher: [Read original article]() Author: ben burtenshaw; shaun smith Published: 2026-06-17T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [AI Bots](), [MSP MCP]() Tags: [agentic](), [agents](), [announcement](), [api](), [artificial-intelligence](), [compliance](), [hub](), [hugging-face](), [manifest](), [mcp](), [mcp-server](), [open](), [resource](), [search](), [skills](), [tool](), [tools]() ### AI overview The article introduces Agentic Resource Discovery (ARD), a draft open specification for cataloging and searching agent capabilities across federated registries. It describes Hugging Face's Discover Tool as a reference implementation that lets agents discover skills, ML applications, and MCP servers dynamically. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## How an Agent Built a 3D Paris Gallery by Chaining Two Hugging Face Spaces DevFeed: [How an Agent Built a 3D Paris Gallery by Chaining Two Hugging Face Spaces]() Original publisher: [Read original article]() Author: Mishig ᠮᠢᠰᠾᠢᠭ Published: 2026-06-09T10:46:19Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [hugging face](), [spaces](), [gradio](), [Artificial Intelligence](), [coding](), [SDKs]() Tags: [3d](), [agent](), [ai](), [building](), [coding](), [generation](), [gradio](), [hub](), [hugging-face](), [images](), [integration](), [spaces]() ### AI overview A coding agent builds a 3D gallery of Paris monuments by chaining two Hugging Face Spaces: one generates images and the other reconstructs 3D Gaussian splats. The article presents Gradio Spaces as documented, callable building blocks that agents can integrate into multimedia software pipelines. ### Source excerpt I asked a coding agent to build a beautiful website showcasing the monuments of Paris as 3D Gaussian splats. I never opened an image generator. I never touched a 3D reconstruction tool. The agent produced every asset (the images and the 3D splats) by calling two Hugging Face Spaces directly, then wired them into a cinematic viewer. ## Migrating Your GitHub CI to Hugging Face Jobs DevFeed: [Migrating Your GitHub CI to Hugging Face Jobs]() Original publisher: [Read original article]() Author: Abubakar Abid Published: 2026-06-09T00:00:00Z Content type: tutorial Language: en Sources: [Hugging Face - Blog]() Topics: [jobs](), [ci](), [GitHub Actions](), [hugging face](), [GPU](), [Docker](), [GitHub]() Tags: [ci](), [docker](), [github](), [github-actions](), [gpu](), [guide](), [how-to](), [hub](), [hugging-face](), [jobs](), [open-source](), [self-hosted]() ### AI overview This tutorial explains how to migrate GitHub Actions CI to Hugging Face Jobs. It combines GitHub-managed workflows with ephemeral self-hosted runners on selectable CPU or GPU hardware, provides real-time logs, and reports about a 30% reduction in CPU CI time for Trackio. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Designing the hf CLI as an agent-optimized way to work with the Hub DevFeed: [Designing the hf CLI as an agent-optimized way to work with the Hub]() Original publisher: [Read original article]() Author: Célina Hanouti; Lucain Pouget Published: 2026-06-04T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [Command-line interface](), [AI-assisted coding](), [Claude Code](), [codex](), [cursor](), [SDKs](), [coding]() Tags: [agent](), [agents](), [article](), [blog](), [claude-code](), [cli](), [codex](), [coding](), [cursor](), [hub](), [huggingface-hub]() ### AI overview This article describes how Hugging Face rebuilt its CLI for both human users and coding agents. It explains agent detection, output optimized for compact and complete machine-readable results, and benchmarks showing lower token usage than hand-rolled commands or the Python SDK on complex multi-step tasks. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Shipping a Trillion Parameters With a Hub Bucket: Delta Weight Sync in TRL DevFeed: [Shipping a Trillion Parameters With a Hub Bucket: Delta Weight Sync in TRL]() Original publisher: [Read original article]() Author: Amine Dirhoussi; Quentin Gallouédec; Kashif Rasul; Lewis Tunstall; Edward Beeching; Albert Villanova del Moral; Leandro von Werra; Sergio Paniego Published: 2026-05-27T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [AI, ML & Data Engineering](), [NCCL]() Tags: [artificial-intelligence](), [compute](), [hub](), [hugging-face](), [inference](), [llm](), [model](), [models](), [nccl](), [open-source](), [payload](), [policy](), [rl](), [space](), [storage](), [sync](), [train](), [training](), [trl](), [update](), [vllm]() ### AI overview The article describes delta weight synchronization for asynchronous reinforcement-learning training. A TRL change stores only modified model weights in sparse safetensors files and lets vLLM fetch them from a Hugging Face bucket, reducing transfer payloads and enabling disaggregated training without a shared cluster. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## DeepInfra on Hugging Face Inference Providers 🔥 DevFeed: [DeepInfra on Hugging Face Inference Providers 🔥]() Original publisher: [Read original article]() Author: Aray Sultanbekova; Shang-Pin; Utemuratov; Yessen K; Oguz Vuruskaner; Célina Hanouti; Simon Brandeis; Lucain Pouget Published: 2026-04-29T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [deepinfra](), [hugging face](), [inference-providers](), [AI Inference](), [SDKs](), [Large Language Model](), [API keys](), [text-generation](), [text-to-image]() Tags: [ai-inference](), [api](), [api-keys](), [applications](), [artificial-intelligence](), [code](), [deepinfra](), [enterprise](), [hub](), [hugging-face](), [inference](), [inference-providers](), [javascript](), [llms](), [open](), [open-source](), [partnerships](), [pricing](), [python](), [sdks](), [text-generation](), [text-to-image]() ### AI overview DeepInfra is now a supported Inference Provider on the Hugging Face Hub, with serverless access to more than 100 models and integration with Hugging Face's JavaScript and Python SDKs. The article describes provider selection, API-key and routed-by-Hugging-Face modes, supported model tasks, and initial access to conversational and text-generation models. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. ## Snyk Opens San Francisco Innovation Hub DevFeed: [Snyk Opens San Francisco Innovation Hub]() Original publisher: [Read original article]() Author: Peter McKay Published: 2026-03-18T04:00:00Z Content type: news Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [Responsibility & Safety]() Tags: [ai](), [ai-security](), [americas](), [awareness](), [blog](), [community](), [developer](), [developers](), [development](), [devops](), [hub](), [innovation](), [pmm](), [security](), [snyk-platform](), [snyk-team](), [tech]() ### AI overview Snyk announces a San Francisco innovation hub focused on AI security. The space will host weekly technical sessions and hackathons for Bay Area AI engineers and promotes integrating security throughout AI development. ### Source excerpt Snyk is opening a new innovation hub in downtown San Francisco, creating a strategic center of gravity for AI security. This new community space invites all Bay Area builders to join weekly hackathons and technical sessions to help shape the future of secure AI innovation. ## State of Open Source on Hugging Face: Spring 2026 DevFeed: [State of Open Source on Hugging Face: Spring 2026]() Original publisher: [Read original article]() Author: Avijit Ghosh; Lucie-Aimée Kaffee; Yacine Jernite; Irene Solaiman Published: 2026-03-17T16:37:55Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [hugging face](), [Open Source](), [Open Source Models & Datasets](), [Artificial Intelligence](), [datasets](), [data](), [Nvidia](), [cursor](), [Visual Studio Code]() Tags: [ai](), [analysis](), [applications](), [community](), [cursor](), [data](), [datasets](), [ecosystem](), [hub](), [hugging-face](), [model](), [nvidia](), [open](), [open-source]() ### AI overview This analysis examines the growth and concentration of the open-source AI ecosystem on Hugging Face in 2025. It reports nearly doubled user, model, and dataset activity, increasing participation through fine-tuned models, adapters, benchmarks, and applications, while highlighting concentrated downloads, specialized communities, and growing company adoption. ### Source excerpt This post builds on an earlier analysis conducted mid-2025, available here, which examined what the Hugging Face Community is building. We recommend reading additional perspectives on the open source ecosystem in and outside of Hugging Face from the Data Provenance Initiative, Interconnects, OpenRouter and a16z, and MIT and the Linux Foundation. ## Vercel Open Source Program: Winter 2026 cohort DevFeed: [Vercel Open Source Program: Winter 2026 cohort]() Original publisher: [Read original article]() Author: Alli Pope Published: 2026-03-17T13:00:00Z Content type: article Language: en Sources: [Vercel News]() Topics: [Open Source](), [Vercel](), [online privacy](), [OpenAPI Specification](), [React](), [React Native](), [Shadcn UI](), [Web](), [Android](), [Canvas](), [Framer Motion](), [Large Language Model]() Tags: [2025](), [agents](), [ai](), [ai-agents](), [android](), [browser](), [components](), [framer](), [hub](), [llm](), [online-privacy](), [open-source](), [openapi](), [react-native](), [scale](), [svelte](), [vercel](), [vue]() ### AI overview Vercel introduces the winter 2026 cohort of its Open Source Program, highlighting projects that receive resources, credits, and support. The cohort includes tools and projects spanning AI-native applications, developer infrastructure, design systems, creative tooling, privacy, Android connectivity, and web development. ### Source excerpt In April, we launched the Vercel Open Source Program to give maintainers the resources, credits, and support they need to ship faster and scale confidently. The first group joined through our spring 2025 cohort. Today we are welcoming the winter 2026 cohort. From AI-native apps and developer infrastructure to design systems and creative tooling, open source builders continue to amaze us. Meet the creators and explore their projects. Winter 2026 Cohort Answer Overflow Answer Overflow is an open source project that makes the content sent in public Discord servers accessible to search engines and AI agents. Over 300+ communities use Answer Overflow to create web pages from their Discord content and it serves 1.5 million monthly active users. Creator: Rhys Sullivan View the project View GitHub Repository UI TripleD UI TripleD offers UI blocks, components, and full pages in shadcn/ui and Base UI, powered by Framer Motion, with a Landing Builder, Background Builder, and Grid Generator. Creator: Moumen Soliman View the project View GitHub repository hot-updater An open source React Native OTA (Over-The-Air) update solution built as a modern alternative to CodePush, designed to avoid vendor lock-in and work across many infrastructure providers. Creator: Kang Sungyu View the project View GitHub repository Screenshot Studio Screenshot Studio is an open source, fully in-browser canvas editor for creating high-quality visual designs without installs or backend dependencies, with real traction and an active contributor community. Creator: Kartik Labhshetwar View the project View GitHub repository Takumi JSX -> Image. A next/og alternative with more advanced features, with growing adoption across companies and open source projects. Creator: Kane Wang View the project View GitHub repository APIs.guru A directory and tooling hub for OpenAPI definitions of public APIs, used by thousands of developers and increasingly by LLM-driven workflows. Creator: Ivan Goncharov View the project V ## Introducing Storage Buckets on the Hugging Face Hub DevFeed: [Introducing Storage Buckets on the Hugging Face Hub]() Original publisher: [Read original article]() Author: Lucain Pouget; Eliott Coyac; Adrien Carreira; Victor Mustar; Julien Chaumond; Quentin Lhoest; Pierric Cistac; Sylvestre Bcht; Hugo Larcher; Rajat Arya Published: 2026-03-10T00:00:00Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [hugging face](), [xet](), [datasets](), [distributed-training](), [Machine learning](), [cloud-infrastructure](), [Open Source]() Tags: [announcement](), [artificial-intelligence](), [cloud](), [datasets](), [distributed-training](), [hub](), [hugging-face](), [open-source](), [storage](), [training](), [xet]() ### AI overview The article introduces Storage Buckets on the Hugging Face Hub, a mutable S3-like storage option for machine-learning artifacts. Built on Xet, Buckets use chunking and deduplication to reduce redundant transfers, storage use, and enterprise billing, while pre-warming places frequently accessed data near distributed-training compute. ### Source excerpt We're on a journey to advance and democratize artificial intelligence through open source and open science. [Next page]()