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ANTHROPIC AND OPENAI BOTH MISSED THIS. Someone just open-sourced one SDK that gives AI agents a mouse, keyboard, and screen across macOS, Linux, and Windows. It's called CUA. Same code drives a local VM or a cloud sandbox regardless of the OS. Your agent sees the screen, clicks, types,...

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Simplifying AI

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31,222 次观看 • 9 天前 •via X (Twitter)

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Governments pay millions for this kind of system. Someone just open-sourced it for free. It's called Crucix. It watches the entire world and texts you when something changes. Pulls from 26 live sources every 15 minutes: - Satellite fire detection, flight and vessel tracking - Conflict zones and economic indicators - Live crypto and market prices - Social sentiment from Telegram intel channels It's two-way. Pushes alerts to Telegram and Discord. Text it back, type /brief for a summary. No cloud, no subscription. Runs on your own machine. 100% Free. Open Source.
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Governments pay millions for this kind of system. Someone just open-sourced it for free. It's called Crucix. It watches the entire world and texts you when something changes. Pulls from 26 live sources every 15 minutes: - Satellite fire detection, flight and vessel tracking - Conflict zones and economic indicators - Live crypto and market prices - Social sentiment from Telegram intel channels It's two-way. Pushes alerts to Telegram and Discord. Text it back, type /brief for a summary. No cloud, no subscription. Runs on your own machine. 100% Free. Open Source.

Simplifying AI

50,129 次观看 • 1 天前

I found this last night and I have not stopped thinking about it. HERMES JUST LAUNCHED HERMES DESKTOP. 100% FREE. It is a free desktop app that gives Hermes Agent a proper interface. One place for everything. What is inside: ↳ Auto install and setup, no terminal needed ↳ Streaming chat with token tracking ↳ Multiple agent profiles ↳ Memory you can actually see and edit ↳ 14 tool categories including web, browser, image gen, and voice ↳ Scheduler for automated tasks ↳ 16 messaging gateways including Telegram, WhatsApp, Discord, Slack, and Signal ↳ Full conversation history with search ↳ Backups and logs in one settings screen Works with Anthropic, OpenAI, Gemini, Grok, Groq, Ollama, and more. Hermes Agent is the brain. Hermes Desktop is the cockpit. Free. Open source. Mac, Windows, and Linux.
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I found this last night and I have not stopped thinking about it. HERMES JUST LAUNCHED HERMES DESKTOP. 100% FREE. It is a free desktop app that gives Hermes Agent a proper interface. One place for everything. What is inside: ↳ Auto install and setup, no terminal needed ↳ Streaming chat with token tracking ↳ Multiple agent profiles ↳ Memory you can actually see and edit ↳ 14 tool categories including web, browser, image gen, and voice ↳ Scheduler for automated tasks ↳ 16 messaging gateways including Telegram, WhatsApp, Discord, Slack, and Signal ↳ Full conversation history with search ↳ Backups and logs in one settings screen Works with Anthropic, OpenAI, Gemini, Grok, Groq, Ollama, and more. Hermes Agent is the brain. Hermes Desktop is the cockpit. Free. Open source. Mac, Windows, and Linux.

Kanika

60,084 次观看 • 1 个月前

Microsoft presents Windows Agent Arena Evaluating Multi-Modal OS Agents at Scale discuss: Large language models (LLMs) show remarkable potential to act as computer agents, enhancing human productivity and software accessibility in multi-modal tasks that require planning and reasoning. However, measuring agent performance in realistic environments remains a challenge since: (i) most benchmarks are limited to specific modalities or domains (e.g. text-only, web navigation, Q&A, coding) and (ii) full benchmark evaluations are slow (on order of magnitude of days) given the multi-step sequential nature of tasks. To address these challenges, we introduce the Windows Agent Arena: a reproducible, general environment focusing exclusively on the Windows operating system (OS) where agents can operate freely within a real Windows OS and use the same wide range of applications, tools, and web browsers available to human users when solving tasks. We adapt the OSWorld framework (Xie et al., 2024) to create 150+ diverse Windows tasks across representative domains that require agent abilities in planning, screen understanding, and tool usage. Our benchmark is scalable and can be seamlessly parallelized in Azure for a full benchmark evaluation in as little as 20 minutes. To demonstrate Windows Agent Arena's capabilities, we also introduce a new multi-modal agent, Navi. Our agent achieves a success rate of 19.5% in the Windows domain, compared to 74.5% performance of an unassisted human. Navi also demonstrates strong performance on another popular web-based benchmark, Mind2Web. We offer extensive quantitative and qualitative analysis of Navi's performance, and provide insights into the opportunities for future research in agent development and data generation using Windows Agent Arena.
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Microsoft presents Windows Agent Arena Evaluating Multi-Modal OS Agents at Scale discuss: Large language models (LLMs) show remarkable potential to act as computer agents, enhancing human productivity and software accessibility in multi-modal tasks that require planning and reasoning. However, measuring agent performance in realistic environments remains a challenge since: (i) most benchmarks are limited to specific modalities or domains (e.g. text-only, web navigation, Q&A, coding) and (ii) full benchmark evaluations are slow (on order of magnitude of days) given the multi-step sequential nature of tasks. To address these challenges, we introduce the Windows Agent Arena: a reproducible, general environment focusing exclusively on the Windows operating system (OS) where agents can operate freely within a real Windows OS and use the same wide range of applications, tools, and web browsers available to human users when solving tasks. We adapt the OSWorld framework (Xie et al., 2024) to create 150+ diverse Windows tasks across representative domains that require agent abilities in planning, screen understanding, and tool usage. Our benchmark is scalable and can be seamlessly parallelized in Azure for a full benchmark evaluation in as little as 20 minutes. To demonstrate Windows Agent Arena's capabilities, we also introduce a new multi-modal agent, Navi. Our agent achieves a success rate of 19.5% in the Windows domain, compared to 74.5% performance of an unassisted human. Navi also demonstrates strong performance on another popular web-based benchmark, Mind2Web. We offer extensive quantitative and qualitative analysis of Navi's performance, and provide insights into the opportunities for future research in agent development and data generation using Windows Agent Arena.

AK

19,684 次观看 • 1 年前

CCleaner used to be the default way to keep a Windows machine fast. Then it got bought, stuffed with ads and bundled crapware, and in 2017 one release was compromised and shipped malware to over 2 million people. Millions still install it every month because nothing else has really replaced it. So, a team called AdventDev just built a free, open-source replacement. It's called Kudu. Open the app and you get one dashboard for the whole machine. > System cleaner for temp files, logs, caches, and crash dumps. > Browser cleaner across every major browser. > Gaming cleaner for launcher and shader caches. > Registry cleaner for broken and orphaned entries. > Startup manager that shows the actual boot impact of each program. > Disk analyzer with an interactive treemap, so you can see where 40GB quietly disappeared to. > Debloater that rips Windows bloatware out. > Program uninstaller that also removes the leftovers other uninstallers leave behind. Then it does the parts CCleaner never did. A malware scanner with signature matching, heuristic analysis, and Windows Defender integration. A privacy shield that lets you flip 30+ Windows privacy settings from one screen: telemetry, ad ID, Cortana, tracking. Secure delete that overwrites files with random data before removing them, so nothing can recover them later. There's a real-time performance monitor with per-core CPU, memory, disk, network, and S.M.A.R.T. drive health. A one-click restore point before every clean, so you can roll back. Scheduled scans. A CLI mode for people who don't want a GUI. Support for 30 languages. Native app for Windows, macOS, and Linux. Intel and Apple Silicon builds. No ads, no upsells, no telemetry, no account. The cleaning rules are plain JSON files, so if your favorite app isn't covered yet, you can add support for it without writing a line of code. MIT license. 100% Open Source. Repo:
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CCleaner used to be the default way to keep a Windows machine fast. Then it got bought, stuffed with ads and bundled crapware, and in 2017 one release was compromised and shipped malware to over 2 million people. Millions still install it every month because nothing else has really replaced it. So, a team called AdventDev just built a free, open-source replacement. It's called Kudu. Open the app and you get one dashboard for the whole machine. > System cleaner for temp files, logs, caches, and crash dumps. > Browser cleaner across every major browser. > Gaming cleaner for launcher and shader caches. > Registry cleaner for broken and orphaned entries. > Startup manager that shows the actual boot impact of each program. > Disk analyzer with an interactive treemap, so you can see where 40GB quietly disappeared to. > Debloater that rips Windows bloatware out. > Program uninstaller that also removes the leftovers other uninstallers leave behind. Then it does the parts CCleaner never did. A malware scanner with signature matching, heuristic analysis, and Windows Defender integration. A privacy shield that lets you flip 30+ Windows privacy settings from one screen: telemetry, ad ID, Cortana, tracking. Secure delete that overwrites files with random data before removing them, so nothing can recover them later. There's a real-time performance monitor with per-core CPU, memory, disk, network, and S.M.A.R.T. drive health. A one-click restore point before every clean, so you can roll back. Scheduled scans. A CLI mode for people who don't want a GUI. Support for 30 languages. Native app for Windows, macOS, and Linux. Intel and Apple Silicon builds. No ads, no upsells, no telemetry, no account. The cleaning rules are plain JSON files, so if your favorite app isn't covered yet, you can add support for it without writing a line of code. MIT license. 100% Open Source. Repo:

Brady Long

146,249 次观看 • 6 天前

🚨 Alibaba just open sourced a GUI agent that lives inside your webpage and controls it with natural language. It's called Page Agent and it's not a browser extension. It's pure JavaScript no Python, no Puppeteer, no headless browser, no screenshots. Just one script tag and your web app understands natural language. Here's what it actually does: → Embed it with a single tag or npm install → Control any web interface with plain English commands → Text-based DOM manipulation no OCR, no vision models needed → Bring your own LLM (GPT, Claude, Qwen, anything) → Ships a built-in UI with human-in-the-loop support → Turn 20-click ERP/CRM workflows into one sentence → Optional Chrome extension for multi-tab agent tasks → Works on any web app SaaS, admin panels, internal tools Companies are charging $30/month for AI copilots built on this exact idea. This is 3 lines of code. Your users. Your interface. The AI copilot layer for every web app just got open sourced. 1.6K stars. 100% Open Source. (Link in the comments)
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🚨 Alibaba just open sourced a GUI agent that lives inside your webpage and controls it with natural language. It's called Page Agent and it's not a browser extension. It's pure JavaScript no Python, no Puppeteer, no headless browser, no screenshots. Just one script tag and your web app understands natural language. Here's what it actually does: → Embed it with a single tag or npm install → Control any web interface with plain English commands → Text-based DOM manipulation no OCR, no vision models needed → Bring your own LLM (GPT, Claude, Qwen, anything) → Ships a built-in UI with human-in-the-loop support → Turn 20-click ERP/CRM workflows into one sentence → Optional Chrome extension for multi-tab agent tasks → Works on any web app SaaS, admin panels, internal tools Companies are charging $30/month for AI copilots built on this exact idea. This is 3 lines of code. Your users. Your interface. The AI copilot layer for every web app just got open sourced. 1.6K stars. 100% Open Source. (Link in the comments)

Ihtesham Ali

135,384 次观看 • 4 个月前

MANUS AI: HYPE VS. REALITY 🔍 Yichao 'Peak' Ji (co-founder of ) confirmed rumors: ✅ Built on Anthropic Claude Sonnet, not their own foundation model ✅Has access to 29 tools and uses Browser Use open-source for browser control ✅User communicates with executor agent and not planner or other agents. ✅Each user gets isolated sandbox environment ✅Outperforms OpenAI Deep Research on GAIA benchmark Building AI products doesn't require training your own foundation models. We're probably just scratching the surface of what existing models can do with the right tooling and integration!
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MANUS AI: HYPE VS. REALITY 🔍 Yichao 'Peak' Ji (co-founder of ) confirmed rumors: ✅ Built on Anthropic Claude Sonnet, not their own foundation model ✅Has access to 29 tools and uses Browser Use open-source for browser control ✅User communicates with executor agent and not planner or other agents. ✅Each user gets isolated sandbox environment ✅Outperforms OpenAI Deep Research on GAIA benchmark Building AI products doesn't require training your own foundation models. We're probably just scratching the surface of what existing models can do with the right tooling and integration!

Philipp Schmid

202,928 次观看 • 1 年前

MiaoYan is a lightweight, native macOS Markdown editor for writing and notes — one of my open-source macOS projects. It just shipped its biggest update to date, introducing Split View for side-by-side Markdown editing and live preview, with smooth bidirectional scroll sync. This release also brings a full visual refinement, layout cycling between sidebar, list, and focus modes, faster startup with native window animations, and broad performance improvements across editing, preview, and export. Built entirely in Swift, not Electron. MiaoYan is local-first, requires no account, collects no telemetry, and avoids AI features by design. I built it for clean Markdown, performance, and a calm writing environment.
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MiaoYan is a lightweight, native macOS Markdown editor for writing and notes — one of my open-source macOS projects. It just shipped its biggest update to date, introducing Split View for side-by-side Markdown editing and live preview, with smooth bidirectional scroll sync. This release also brings a full visual refinement, layout cycling between sidebar, list, and focus modes, faster startup with native window animations, and broad performance improvements across editing, preview, and export. Built entirely in Swift, not Electron. MiaoYan is local-first, requires no account, collects no telemetry, and avoids AI features by design. I built it for clean Markdown, performance, and a calm writing environment.

Tw93

34,484 次观看 • 6 个月前

NVIDIA open-sourced a 600M model that transcribes 40 languages in real-time at 80ms latency and it costs $0. that's faster than you can blink. across mandarin, arabic, hindi, portuguese, tagalog, whatever,from a SINGLE checkpoint. → 17x more concurrent streams than buffered ASR on the same H100. → punctuation + capitalization built-in. no post-processing. → runs on your own GPU. no API bill 100% Open Source.
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NVIDIA open-sourced a 600M model that transcribes 40 languages in real-time at 80ms latency and it costs $0. that's faster than you can blink. across mandarin, arabic, hindi, portuguese, tagalog, whatever,from a SINGLE checkpoint. → 17x more concurrent streams than buffered ASR on the same H100. → punctuation + capitalization built-in. no post-processing. → runs on your own GPU. no API bill 100% Open Source.

Superman

103,621 次观看 • 11 天前

Visa just gave your AI a debit card. A real, spendable Visa card created by an AI chatbot in under 10 seconds. No human types in a card number or visits a checkout page. The machine handles it all. A tool called AgentCard just went live on Claude Desktop Anthropic’s AI assistant. You say create a card and the AI generates a one-time virtual Visa, preloaded with whatever amount you set. Then it spends it, anywhere Visa is accepted on your behalf. Visa, Mastercard, Google, Stripe, OpenAI, and Anthropic have all been building toward this moment for over a year. Visa calls it the trusted agent protocol, Mastercard calls it agent pay. Google published an open standard for agent payments and the infrastructure is already live. Santander and Mastercard just completed Europe’s first real AI‑agent payment in a live banking environment Now the part no one wants to talk about. Your AI agent can be manipulated and prompt injection a known, unsolved vulnerability can trick an agent into buying things you never asked for. The agent holds the card, makes the call and the agent can be fooled. Who is liable when an AI makes a bad purchase? You? Anthropic? Visa? The merchant? No one has answered this yet, regulators haven’t caught up, and no court has tested it.
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Visa just gave your AI a debit card. A real, spendable Visa card created by an AI chatbot in under 10 seconds. No human types in a card number or visits a checkout page. The machine handles it all. A tool called AgentCard just went live on Claude Desktop Anthropic’s AI assistant. You say create a card and the AI generates a one-time virtual Visa, preloaded with whatever amount you set. Then it spends it, anywhere Visa is accepted on your behalf. Visa, Mastercard, Google, Stripe, OpenAI, and Anthropic have all been building toward this moment for over a year. Visa calls it the trusted agent protocol, Mastercard calls it agent pay. Google published an open standard for agent payments and the infrastructure is already live. Santander and Mastercard just completed Europe’s first real AI‑agent payment in a live banking environment Now the part no one wants to talk about. Your AI agent can be manipulated and prompt injection a known, unsolved vulnerability can trick an agent into buying things you never asked for. The agent holds the card, makes the call and the agent can be fooled. Who is liable when an AI makes a bad purchase? You? Anthropic? Visa? The merchant? No one has answered this yet, regulators haven’t caught up, and no court has tested it.

Milk Road AI

70,591 次观看 • 4 个月前

PewDiePie just hit 20K GitHub stars in under 24 hours. The project? Odysseus. A self-hosted AI workspace that runs 100% on your machine. • Agents with tools • MCP built in • Persistent memory • File handling • Windows, macOS, Linux Your data never leaves your device. It supports Ollama, llama.cpp, and vLLM locally with OpenAI and OpenRouter support if you want cloud models too. The crazy part? A YouTuber with 110M+ subscribers just out-shipped most AI startups. And he built half of it using AI.
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PewDiePie just hit 20K GitHub stars in under 24 hours. The project? Odysseus. A self-hosted AI workspace that runs 100% on your machine. • Agents with tools • MCP built in • Persistent memory • File handling • Windows, macOS, Linux Your data never leaves your device. It supports Ollama, llama.cpp, and vLLM locally with OpenAI and OpenRouter support if you want cloud models too. The crazy part? A YouTuber with 110M+ subscribers just out-shipped most AI startups. And he built half of it using AI.

Charlie Hills

16,391 次观看 • 1 个月前

OpenClaw Releases iOS and Android Companion Node Apps That Connect a Phone to a Self-Hosted AI Agent Gateway Most "AI assistant" apps are a chatbot in a sandbox, calling someone else's API. OpenClaw's iOS and Android apps draw a very clear line away from that model. They're companion nodes, not standalone apps. Each phone pairs to a self-hosted OpenClaw Gateway over a WebSocket (default port 18789) with role: "node". The Gateway — the single control plane for sessions, routing, channels, and events — runs on macOS, Linux, or Windows (WSL2). The phone gives the agent a body: camera, location, voice, notifications, and a live Canvas. Here's what's actually interesting: → The assistant runs on your machine — chat messages land on the Gateway, never on the phone → Nodes expose a command surface (canvas., camera., device., notifications., system.*) through node.invoke → Privacy-heavy commands like camera.snap and screen.record stay off until you allowlist them via gateway.nodes.allowCommands → Camera and screen capture run foreground-only; pairing needs explicit approval (openclaw devices approve) → Both store listings declare no data collection; ws:// is LAN-only, remote needs a wss:// TLS endpoint via Tailscale Full analysis: Android app: iOS App: OpenClaw🦞
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OpenClaw Releases iOS and Android Companion Node Apps That Connect a Phone to a Self-Hosted AI Agent Gateway Most "AI assistant" apps are a chatbot in a sandbox, calling someone else's API. OpenClaw's iOS and Android apps draw a very clear line away from that model. They're companion nodes, not standalone apps. Each phone pairs to a self-hosted OpenClaw Gateway over a WebSocket (default port 18789) with role: "node". The Gateway — the single control plane for sessions, routing, channels, and events — runs on macOS, Linux, or Windows (WSL2). The phone gives the agent a body: camera, location, voice, notifications, and a live Canvas. Here's what's actually interesting: → The assistant runs on your machine — chat messages land on the Gateway, never on the phone → Nodes expose a command surface (canvas., camera., device., notifications., system.*) through node.invoke → Privacy-heavy commands like camera.snap and screen.record stay off until you allowlist them via gateway.nodes.allowCommands → Camera and screen capture run foreground-only; pairing needs explicit approval (openclaw devices approve) → Both store listings declare no data collection; ws:// is LAN-only, remote needs a wss:// TLS endpoint via Tailscale Full analysis: Android app: iOS App: OpenClaw🦞

Marktechpost AI

38,666 次观看 • 27 天前

HERMES AGENT NOW SUPPORTS COMPUTER USE ON WINDOWS AND LINUX. CLICKS, TYPES, SCROLLS YOUR DESKTOP IN THE BACKGROUND WHILE YOU WORK. computer use was macOS only. now it works on Windows and Linux too via Cua. Nous Research HOW IT WORKS: cua-driver runs as an MCP server. Hermes takes a screenshot with numbered elements. clicks element #14 (the search field). types a query. submits. reads the result. during all of this: → your cursor stays where you left it → keyboard focus doesn't change → windows don't come to front → macOS doesn't switch Spaces you and the agent co-work on the same machine. WHAT IT CAN DO: → find your latest Stripe email and summarize it → fill forms in a web app that has no API → navigate desktop apps (Mail, browser, Finder) → interact with any GUI application → extract data from apps only accessible via screen WORKS WITH ANY VISION MODEL: not locked to Anthropic. | Provider | Works | |---|---| | Claude (Sonnet/Opus) | best overall | | GPT-4+, GPT-5.5 | full support | | Gemini (via OpenRouter) | full support | | Local vLLM / LM Studio | if model supports vision | | Text-only models | degraded (accessibility tree only) | SETUP: hermes computer-use install or: hermes tools → Computer Use → cua-driver grant permissions when prompted: → Accessibility (system settings) → Screen Recording (system settings) start a session: hermes -t computer_use chat or add to config.yaml / Desktop app settings to enable permanently. SAFETY: → destructive actions require your approval → blocked key combos: empty trash, force delete, lock screen, log out → blocked type patterns: curl | bash, sudo rm -rf /, fork bombs → agent cannot click permission dialogs → agent cannot type passwords → agent cannot follow instructions embedded in screenshots pair with approvals.mode: manual if you want every single click confirmed. TOKEN NOTE: screenshots are expensive. each one adds vision tokens to context. use computer_use for tasks where no API exists. if the tool has an API or MCP server, use that instead. 15 levels of Hermes Agent👇
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HERMES AGENT NOW SUPPORTS COMPUTER USE ON WINDOWS AND LINUX. CLICKS, TYPES, SCROLLS YOUR DESKTOP IN THE BACKGROUND WHILE YOU WORK. computer use was macOS only. now it works on Windows and Linux too via Cua. Nous Research HOW IT WORKS: cua-driver runs as an MCP server. Hermes takes a screenshot with numbered elements. clicks element #14 (the search field). types a query. submits. reads the result. during all of this: → your cursor stays where you left it → keyboard focus doesn't change → windows don't come to front → macOS doesn't switch Spaces you and the agent co-work on the same machine. WHAT IT CAN DO: → find your latest Stripe email and summarize it → fill forms in a web app that has no API → navigate desktop apps (Mail, browser, Finder) → interact with any GUI application → extract data from apps only accessible via screen WORKS WITH ANY VISION MODEL: not locked to Anthropic. | Provider | Works | |---|---| | Claude (Sonnet/Opus) | best overall | | GPT-4+, GPT-5.5 | full support | | Gemini (via OpenRouter) | full support | | Local vLLM / LM Studio | if model supports vision | | Text-only models | degraded (accessibility tree only) | SETUP: hermes computer-use install or: hermes tools → Computer Use → cua-driver grant permissions when prompted: → Accessibility (system settings) → Screen Recording (system settings) start a session: hermes -t computer_use chat or add to config.yaml / Desktop app settings to enable permanently. SAFETY: → destructive actions require your approval → blocked key combos: empty trash, force delete, lock screen, log out → blocked type patterns: curl | bash, sudo rm -rf /, fork bombs → agent cannot click permission dialogs → agent cannot type passwords → agent cannot follow instructions embedded in screenshots pair with approvals.mode: manual if you want every single click confirmed. TOKEN NOTE: screenshots are expensive. each one adds vision tokens to context. use computer_use for tasks where no API exists. if the tool has an API or MCP server, use that instead. 15 levels of Hermes Agent👇

YanXbt

29,127 次观看 • 1 个月前

🧃 Introducing stereOS: a Linux based operating system hardened and purpose built for AI agents. It's clear that agents need an ACTUAL operating system (not what people are calling an "OS") to witness the full breadth and depth of their capabilities while mitigating the blast radius of autonomous, untrusted actors. But there are so many problems with AI sandboxes today: * Going out to the apple store and buying a mac mini will never scale and is way too expensive (obviously) * Running in Docker is too restrictive (agents can't stand up their own container infrastructure, no sub virtualization, docker-in-docker is very broken) * Firecracker strips all the hardware so GPU PCIe passthrough, secure boot, FIPs, etc. is out of the question. * Native VMs are too fat and the overhead of 1 agent per VM is too much. stereOS takes a different approach: it's a full NixOS system that you boot and then kick off agent sandboxes inside with gVisor + /nix/store namespace mounting. Each agent gets their own kernel and the /nix/store is read only by nature. Even if the agent was somehow able to escape the gVisor virtual kernel, they'd land on the NixOS system as the "agent" user! Not your actual hardware!! If you want to take a defense-in-depth approach, we support "native" agents that run at the system level kicked off by our `agentd` utility. These agents, on their own, can manage and kick off other sub agents using the internal sandboxing mechanisms. Today, we're open sourcing all of this: * stereOS: our purpose built Linux OS - * masterblaster: client utility to launch, manage, and orchestrate agents - * stereosd: the stereOS system control plane daemon - * agentd: the stereOS system agent management daemon - Give it a try, throw us a star, and let me know what you think 🧃⭐️
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🧃 Introducing stereOS: a Linux based operating system hardened and purpose built for AI agents. It's clear that agents need an ACTUAL operating system (not what people are calling an "OS") to witness the full breadth and depth of their capabilities while mitigating the blast radius of autonomous, untrusted actors. But there are so many problems with AI sandboxes today: * Going out to the apple store and buying a mac mini will never scale and is way too expensive (obviously) * Running in Docker is too restrictive (agents can't stand up their own container infrastructure, no sub virtualization, docker-in-docker is very broken) * Firecracker strips all the hardware so GPU PCIe passthrough, secure boot, FIPs, etc. is out of the question. * Native VMs are too fat and the overhead of 1 agent per VM is too much. stereOS takes a different approach: it's a full NixOS system that you boot and then kick off agent sandboxes inside with gVisor + /nix/store namespace mounting. Each agent gets their own kernel and the /nix/store is read only by nature. Even if the agent was somehow able to escape the gVisor virtual kernel, they'd land on the NixOS system as the "agent" user! Not your actual hardware!! If you want to take a defense-in-depth approach, we support "native" agents that run at the system level kicked off by our `agentd` utility. These agents, on their own, can manage and kick off other sub agents using the internal sandboxing mechanisms. Today, we're open sourcing all of this: * stereOS: our purpose built Linux OS - * masterblaster: client utility to launch, manage, and orchestrate agents - * stereosd: the stereOS system control plane daemon - * agentd: the stereOS system agent management daemon - Give it a try, throw us a star, and let me know what you think 🧃⭐️

John McBride

150,334 次观看 • 5 个月前

ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.
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ANTHROPIC JUST TURNED AI AGENTS INTO GIT REPOS Anthropic shipped "ant" - a CLI that runs every Claude API endpoint straight from your terminal. The headline isn't the terminal access. It's that you can now version-control an AI agent as YAML in Git and have CI sync it to the Claude Platform, the same way you ship code. - Every API resource is a subcommand: messages, models, files, agents, sessions - Define an agent in a YAML file, check it into your repo, and keep it in sync with one update command - Spin up a session, send it an event, then pull every event and tool call back from the same CLI - Claude Code knows how to drive ant out of the box - it shells out and reads the results with no glue code Agents just stopped being prompts you babysit and became infrastructure you deploy.

BuBBliK

200,080 次观看 • 1 个月前

NVIDIA just made paying for AI feel optional. Open model, a million tokens of context, free tier with no per-token cost, runs on your own hardware. Entire codebases, whole data rooms, a year of chat logs, all swallowed in one prompt. No chunking, no RAG, no rate limit theater. The closed-AI premium has 90 days to defend itself. Bookmark this and come back. Open beat closed. Again.
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NVIDIA just made paying for AI feel optional. Open model, a million tokens of context, free tier with no per-token cost, runs on your own hardware. Entire codebases, whole data rooms, a year of chat logs, all swallowed in one prompt. No chunking, no RAG, no rate limit theater. The closed-AI premium has 90 days to defend itself. Bookmark this and come back. Open beat closed. Again.

shmidt

295,692 次观看 • 1 个月前

INJECTIVE LAUNCHES INJECTIVE AGENTS WITH VERIFIABLE ON-CHAIN IDENTITY AND AUTOMATIC FEE ROUTING Injective 🥷 has launched Injective Agents, a platform for building autonomous trading agents that live entirely on-chain. Each agent gets a verifiable on-chain identity, automatic fee routing on every trade, and a public track record anyone can audit. Injective says deployment takes five minutes. The launch productizes roughly 18 months of agent infrastructure work at Injective. The chain released its iAgent SDK in November 2024, a Model Context Protocol server for AI-driven perpetual futures trading in February 2026, and an open-source AI Developer Toolkit in March. Injective Agents packages that stack into a consumer-facing product with revenue capture built in for agent operators. The move lands as on-chain agent volume accelerates across Base, Solana, and now Injective. Coinbase launched Agentic Wallets earlier this year.
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INJECTIVE LAUNCHES INJECTIVE AGENTS WITH VERIFIABLE ON-CHAIN IDENTITY AND AUTOMATIC FEE ROUTING Injective 🥷 has launched Injective Agents, a platform for building autonomous trading agents that live entirely on-chain. Each agent gets a verifiable on-chain identity, automatic fee routing on every trade, and a public track record anyone can audit. Injective says deployment takes five minutes. The launch productizes roughly 18 months of agent infrastructure work at Injective. The chain released its iAgent SDK in November 2024, a Model Context Protocol server for AI-driven perpetual futures trading in February 2026, and an open-source AI Developer Toolkit in March. Injective Agents packages that stack into a consumer-facing product with revenue capture built in for agent operators. The move lands as on-chain agent volume accelerates across Base, Solana, and now Injective. Coinbase launched Agentic Wallets earlier this year.

BSCN

17,042 次观看 • 3 个月前

MOONSHOT JUST CLONED CLAUDE CODE AND MADE IT FREE. It's called Kimi Code CLI. Open source, MIT license, maintained by the lab that shipped K3 yesterday. And it does things Claude Code doesn't: → drop a screen recording into the chat as input → built-in coder, explore, and plan subagents, each in its own context → plan mode before it touches a single file → MCP servers configured by the agent itself via /mcp-config → plugs into Zed, JetBrains, and VS Code → one binary, no Node setup, starts in milliseconds The CLI costs $0. K3 behind it starts at $3 per million tokens. Grab it for free👇
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MOONSHOT JUST CLONED CLAUDE CODE AND MADE IT FREE. It's called Kimi Code CLI. Open source, MIT license, maintained by the lab that shipped K3 yesterday. And it does things Claude Code doesn't: → drop a screen recording into the chat as input → built-in coder, explore, and plan subagents, each in its own context → plan mode before it touches a single file → MCP servers configured by the agent itself via /mcp-config → plugs into Zed, JetBrains, and VS Code → one binary, no Node setup, starts in milliseconds The CLI costs $0. K3 behind it starts at $3 per million tokens. Grab it for free👇

darkzodchi

400,197 次观看 • 9 天前

China open-sourced a peanut-sized OCR that parses entire 100-page PDFs in one shot.. It's called Unlimited-OCR. Only 3B params. Runs locally. Every other OCR tool chops your doc into pages and loses the thread. this one reads the whole thing in a single pass. → One-shot "long-horizon" parsing (32K context window) → Multilingual, out of the box → 93% on the standard parsing benchmark (+6 over baseline) → <0.11 error rate past 40 pages → Runs 100% locally on your own hardware → Works with Transformers, vLLM, SGLang, Docker, Ollama, llama.cpp Traditional cloud OCR (Textract, Google Vision, Azure Doc Intelligence) costs $1.50–$15 per 1,000 pages. This runs on your machine. For free. Forever. Baidu built it explicitly to push DeepSeek-OCR one step further. Already at 1.9M downloads on Hugging Face and most people have no idea it exists yet. 100% open source.
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China open-sourced a peanut-sized OCR that parses entire 100-page PDFs in one shot.. It's called Unlimited-OCR. Only 3B params. Runs locally. Every other OCR tool chops your doc into pages and loses the thread. this one reads the whole thing in a single pass. → One-shot "long-horizon" parsing (32K context window) → Multilingual, out of the box → 93% on the standard parsing benchmark (+6 over baseline) → <0.11 error rate past 40 pages → Runs 100% locally on your own hardware → Works with Transformers, vLLM, SGLang, Docker, Ollama, llama.cpp Traditional cloud OCR (Textract, Google Vision, Azure Doc Intelligence) costs $1.50–$15 per 1,000 pages. This runs on your machine. For free. Forever. Baidu built it explicitly to push DeepSeek-OCR one step further. Already at 1.9M downloads on Hugging Face and most people have no idea it exists yet. 100% open source.

Superman

1,083,022 次观看 • 8 天前

Introducing: OpenGranola 🔥 I built an open source meeting copilot for macOS. It transcribes both sides of your call on-device, searches your own notes in real time, and hands you talking points right when the conversation needs them. No audio leaves your Mac. Point it at a folder of markdown files, pick any LLM through OpenRouter (Claude, GPT-4o, Gemini, Llama), and it just works. It's invisible to screen share too — nobody knows you have it. The whole thing is open source. Link below
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Introducing: OpenGranola 🔥 I built an open source meeting copilot for macOS. It transcribes both sides of your call on-device, searches your own notes in real time, and hands you talking points right when the conversation needs them. No audio leaves your Mac. Point it at a folder of markdown files, pick any LLM through OpenRouter (Claude, GPT-4o, Gemini, Llama), and it just works. It's invisible to screen share too — nobody knows you have it. The whole thing is open source. Link below

yazin

292,933 次观看 • 4 个月前

Introducing the Agent Virtual Machine (AVM) Think V8 for agents. AI agents are currently running on your computer with no unified security, no resource limits, and no visibility into what data they're sending out. Every agent framework builds its own security model, its own sandboxing, its own permission system. You configure each one separately. You audit each one separately. You hope you didn't miss anything in any of them. The AVM changes this. It's a single runtime daemon (avmd) that sits between every agent framework and your operating system. Install it once, configure one policy file, and every agent on your machine runs inside it - regardless of which framework built it. The AVM enforces security (91-pattern injection scanner, tool/file/network ACLs, approval prompts), protects your privacy (classifies every outbound byte for PII, credentials, and financial data - blocks or alerts in real-time), and governs resources (you say "50% CPU, 4GB RAM" and the AVM fair-shares it across all agents, halting any that exceed their budget). One config. One audit command. One kill switch. The architectural model is V8 for agents. Chrome, Node.js, and Deno are different products but they share V8 as their execution engine. Agent frameworks bring the UX. The AVM brings the trust. Where needed, AVM can also generate zero-knowledge proofs of agent execution via 25 purpose-built opcodes and 6 proof systems, providing the foundational pillar for the agent-to-agent economy. AVM v0.1.0 - Changelog - Security gate: 5-layer injection scanner with 91 compiled regex patterns. Every input and output scanned. Fail-closed - nothing passes without clearing the gate. - Privacy layer: Classifies all outbound data for PII, credentials, and financial info (27 detection patterns + Luhn validation). Block, ask, warn, or allow per category. Tamper-evident hash-chained log of every egress event. - Resource governor: User sets system-wide caps (CPU/memory/disk/network). AVM fair-shares across all agents. Gas budget per agent - when gas runs out, execution halts. No agent starves your machine. - Sandbox execution: Real code execution in isolated process sandboxes (rlimits, env sanitization) or Docker containers (--cap-drop ALL, --network none, --read-only). AVM auto-selects the tier - agents never choose their own sandbox. - Approval flow: Dangerous operations (file writes, shell commands, network requests) trigger interactive approval prompts. 5-minute timeout auto-denies. Every decision logged. - CLI dashboard: hyperspace-avm top shows all running agents, resource usage, gas budgets, security events, and privacy stats in one live-updating screen. - Node.js SDK: Zero-dependency hyperspace/avm package. AVM.tryConnect() for graceful fallback - if avmd isn't running, the agent framework uses its own execution path. OpenClaw adapter example included. - One config for all agents: ~/.hyperspace/avm-policy.json governs every agent framework on your machine. One file. One audit. One kill switch.
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Introducing the Agent Virtual Machine (AVM) Think V8 for agents. AI agents are currently running on your computer with no unified security, no resource limits, and no visibility into what data they're sending out. Every agent framework builds its own security model, its own sandboxing, its own permission system. You configure each one separately. You audit each one separately. You hope you didn't miss anything in any of them. The AVM changes this. It's a single runtime daemon (avmd) that sits between every agent framework and your operating system. Install it once, configure one policy file, and every agent on your machine runs inside it - regardless of which framework built it. The AVM enforces security (91-pattern injection scanner, tool/file/network ACLs, approval prompts), protects your privacy (classifies every outbound byte for PII, credentials, and financial data - blocks or alerts in real-time), and governs resources (you say "50% CPU, 4GB RAM" and the AVM fair-shares it across all agents, halting any that exceed their budget). One config. One audit command. One kill switch. The architectural model is V8 for agents. Chrome, Node.js, and Deno are different products but they share V8 as their execution engine. Agent frameworks bring the UX. The AVM brings the trust. Where needed, AVM can also generate zero-knowledge proofs of agent execution via 25 purpose-built opcodes and 6 proof systems, providing the foundational pillar for the agent-to-agent economy. AVM v0.1.0 - Changelog - Security gate: 5-layer injection scanner with 91 compiled regex patterns. Every input and output scanned. Fail-closed - nothing passes without clearing the gate. - Privacy layer: Classifies all outbound data for PII, credentials, and financial info (27 detection patterns + Luhn validation). Block, ask, warn, or allow per category. Tamper-evident hash-chained log of every egress event. - Resource governor: User sets system-wide caps (CPU/memory/disk/network). AVM fair-shares across all agents. Gas budget per agent - when gas runs out, execution halts. No agent starves your machine. - Sandbox execution: Real code execution in isolated process sandboxes (rlimits, env sanitization) or Docker containers (--cap-drop ALL, --network none, --read-only). AVM auto-selects the tier - agents never choose their own sandbox. - Approval flow: Dangerous operations (file writes, shell commands, network requests) trigger interactive approval prompts. 5-minute timeout auto-denies. Every decision logged. - CLI dashboard: hyperspace-avm top shows all running agents, resource usage, gas budgets, security events, and privacy stats in one live-updating screen. - Node.js SDK: Zero-dependency hyperspace/avm package. AVM.tryConnect() for graceful fallback - if avmd isn't running, the agent framework uses its own execution path. OpenClaw adapter example included. - One config for all agents: ~/.hyperspace/avm-policy.json governs every agent framework on your machine. One file. One audit. One kill switch.

Varun

142,179 次观看 • 4 个月前