Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

Open Computer Agent - LLMs completing tasks using a VM. It's playground to test how well current LLM agents use a computer to solve everyday tasks. And this is just the start - very soon models will be 10x faster and 10x better at it! ❤️ built with e2b... show more

Leandro von Werra

11,217 subscribers

17,126 views • 1 year ago •via X (Twitter)

Gaming Science & Technology Education

Anya Rossi• Live Now

Private livecam show

5 Comments

Leandro von Werra1 year ago

Try it out:

Rainmaker2 years ago

Here I share an XGBoost model that delivers a 25% CAGR with minimal drawdown on Visa stock. In this free Substack post I share code and commentary for a powerful Machine Learning strategy that delivers powerful returns.

Van Tuan Bui1 year ago

Love this! 🖥️🤖

Squad | AI Agents1 year ago

Very cool, we’ve been experimenting with some no-code agent setups too. Love where the space is heading!!

kfant1 year ago

agent running no log no actions

Related Videos

OpenAI just released access to Computer Use Agent via an API. It combines GPT-4o vision with advanced reasoning for an AI Agent to simulate controlling computer interfaces and performing tasks just like humans. You can try it for free using this Agent Playground.

OpenAI just released access to Computer Use Agent via an API. It combines GPT-4o vision with advanced reasoning for an AI Agent to simulate controlling computer interfaces and performing tasks just like humans. You can try it for free using this Agent Playground.

Shubham Saboo

64,206 views • 1 year ago

Computer use agents are slow and brittle. The fix isn’t just stronger models, but also deploying them as multi-agent systems. MACU is a general Multi-Agent Computer Use framework that consistently lifts success rates by 3.4-25.5% and is up to 1.5x faster on long-horizon tasks.🧵

Computer use agents are slow and brittle. The fix isn’t just stronger models, but also deploying them as multi-agent systems. MACU is a general Multi-Agent Computer Use framework that consistently lifts success rates by 3.4-25.5% and is up to 1.5x faster on long-horizon tasks.🧵

Jing Yu Koh

32,664 views • 4 months ago

🎮 Computer Use Agent Arena is LIVE! 🚀 🔥 Easiest way to test computer-use agents in the wild without any setup 🌟 Compare top VLMs: OpenAI Operator, Claude 3.7, Gemini 2.5 Pro, Qwen 2.5 vl and more 🕹️ Test agents on 100+ real apps & webs with one-click config 🔒 Safe & free access on cloud-hosted machines Page: Leaderboard (tentative): Blog: Data & Code (coming soon): ⭐️Why Computer Agent Arena? 1️⃣Beyond Static Benchmarks: We use computers to perform enormous tasks and workflows every day, and AI agents have the potential to automate these tasks. However, existing benchmarks are very limited (e.g., only 369 tasks in OSWorld and 812 tasks in WebArena). To better measure their capabilities, we introduce Computer Agent Arena for users to easily compare & test AI agents on all kinds of crowdsourced real-world computer use tasks. 2️⃣Cloud Testing, Simplified: As agents like OpenAI’s Operator and Claude 3.7 sonnet release, users face configuration challenges and privacy hurdles to deploy on their own computers. Our platform integrates these agents with cloud-hosted machines, providing users with quick and secure access. 3️⃣Unified Embodied Digital Environment: Unlike Chatbot Arena, we provide users with a real embodied environment—computers—where all agents are grounded in real computer tasks and environments. Led by @XLANG_Lab [1/🧵]

🎮 Computer Use Agent Arena is LIVE! 🚀 🔥 Easiest way to test computer-use agents in the wild without any setup 🌟 Compare top VLMs: OpenAI Operator, Claude 3.7, Gemini 2.5 Pro, Qwen 2.5 vl and more 🕹️ Test agents on 100+ real apps & webs with one-click config 🔒 Safe & free access on cloud-hosted machines Page: Leaderboard (tentative): Blog: Data & Code (coming soon): ⭐️Why Computer Agent Arena? 1️⃣Beyond Static Benchmarks: We use computers to perform enormous tasks and workflows every day, and AI agents have the potential to automate these tasks. However, existing benchmarks are very limited (e.g., only 369 tasks in OSWorld and 812 tasks in WebArena). To better measure their capabilities, we introduce Computer Agent Arena for users to easily compare & test AI agents on all kinds of crowdsourced real-world computer use tasks. 2️⃣Cloud Testing, Simplified: As agents like OpenAI’s Operator and Claude 3.7 sonnet release, users face configuration challenges and privacy hurdles to deploy on their own computers. Our platform integrates these agents with cloud-hosted machines, providing users with quick and secure access. 3️⃣Unified Embodied Digital Environment: Unlike Chatbot Arena, we provide users with a real embodied environment—computers—where all agents are grounded in real computer tasks and environments. Led by @XLANG_Lab [1/🧵]

Bowen Wang

93,330 views • 1 year ago

Antigravity's computer use has also been massively upgraded with Gemini 3 Flash. It is both faster and better at doing long agentic tasks using the browser. Here's Antigravity doing deep research on the Pareto frontier of models and writing code to visualize the result.

Antigravity's computer use has also been massively upgraded with Gemini 3 Flash. It is both faster and better at doing long agentic tasks using the browser. Here's Antigravity doing deep research on the Pareto frontier of models and writing code to visualize the result.

Varun Mohan

157,542 views • 10 months ago

Openclaw wrappers are the best businesses to start in 2026. The reason you can't find a good use case for open claw is that the use cases are boring and live inside legacy businesses with manual workflows. They're repetitive tasks that you can solve by deploying open claw and Computer-Use Agents.

Openclaw wrappers are the best businesses to start in 2026. The reason you can't find a good use case for open claw is that the use cases are boring and live inside legacy businesses with manual workflows. They're repetitive tasks that you can solve by deploying open claw and Computer-Use Agents.

Nick Vasilescu

149,197 views • 8 months ago

icymi Hugging Face dropped a computer use agent last week 🔥 built on various Qwen3-VL models & E2B sandbox, ask the app to do anything 🙌🏻 it exposes each thinking step to you, try different models with a neat UI🤩

icymi Hugging Face dropped a computer use agent last week 🔥 built on various Qwen3-VL models & E2B sandbox, ask the app to do anything 🙌🏻 it exposes each thinking step to you, try different models with a neat UI🤩

merve

16,102 views • 11 months ago

8/ Computer Use Are A Sadness - 🎖️Engagement Award Exploiting computer use agents using LLM security vulnerabilities for fun and profit Hijack agents that try to access your computer

8/ Computer Use Are A Sadness - 🎖️Engagement Award Exploiting computer use agents using LLM security vulnerabilities for fun and profit Hijack agents that try to access your computer

Alex Reibman 🖇️

25,051 views • 1 year ago

Muse Spark Open is built to plan, act, and use computer across agentic tasks for life and work. You can now build a powerful personal AI agent with an open stack, and SGLang to make it: - Ultra-responsive with NVFP4 MegaMoE and sequence parallelism - Faster for agentic and coding tasks with our DFlash2 draft model - Customizable for specialized use cases via fine-tuning with Miles We’re incredibly proud to have made this possible with AI at Meta, NVIDIA AI, AI at AMD, Intel, and RadixArk!

Muse Spark Open is built to plan, act, and use computer across agentic tasks for life and work. You can now build a powerful personal AI agent with an open stack, and SGLang to make it: - Ultra-responsive with NVFP4 MegaMoE and sequence parallelism - Faster for agentic and coding tasks with our DFlash2 draft model - Customizable for specialized use cases via fine-tuning with Miles We’re incredibly proud to have made this possible with AI at Meta, NVIDIA AI, AI at AMD, Intel, and RadixArk!

SGLang

286,385 views • 11 days ago

Open AI released Operator, an agent that can use the browser to perform and automate tasks for you! I have built an Open Source version of Operator using Browser Use, running locally on your computer. 100% Open Source

Open AI released Operator, an agent that can use the browser to perform and automate tasks for you! I have built an Open Source version of Operator using Browser Use, running locally on your computer. 100% Open Source

Sumanth

62,485 views • 1 year ago

A look at computer use and the built-in browser in the new ChatGPT app 👀 dominik kundel walks through how ChatGPT can work with apps on your computer and browse the web to research, navigate websites, and complete tasks with you.

A look at computer use and the built-in browser in the new ChatGPT app 👀 dominik kundel walks through how ChatGPT can work with apps on your computer and browse the web to research, navigate websites, and complete tasks with you.

ChatGPT

128,615 views • 3 months ago

🤔Can we assess agents across various apps & OS w.o. crafting new envs? OSWorld🖥️: A unified, real computer env for multimodal agents to evaluate open-ended computer tasks with arbitrary apps and interfaces on Ubuntu, Windows, & macOS. + annotated 369 real-world computer tasks 👇

🤔Can we assess agents across various apps & OS w.o. crafting new envs? OSWorld🖥️: A unified, real computer env for multimodal agents to evaluate open-ended computer tasks with arbitrary apps and interfaces on Ubuntu, Windows, & macOS. + annotated 369 real-world computer tasks 👇

Tianbao Xie

68,838 views • 2 years ago

Listen to James Murdza's demo of a 100% open-source Computer Use. The agent is using 3 different LLMs: 🔸Llama 3.2 (AI at Meta) 🔸Llama 3.3 🔸OS-Atlas (Qwen, Junyang Lin) This example is using @e2b_dev's Desktop Sandbox as a virtual computer. It's completely open-source too, so go build your own agent.

Listen to James Murdza's demo of a 100% open-source Computer Use. The agent is using 3 different LLMs: 🔸Llama 3.2 (AI at Meta) 🔸Llama 3.3 🔸OS-Atlas (Qwen, Junyang Lin) This example is using @e2b_dev's Desktop Sandbox as a virtual computer. It's completely open-source too, so go build your own agent.

Tereza Tizkova, 🌁 at AI Engineer 06/29-07/02

71,412 views • 1 year ago

We've been using Cua-Bench internally—and with customers—for the last few months to evaluate every computer-use agent we deploy. Today it's open-source. 15 public tasks, 40 variations, adapters for OSWorld and Windows Agent Arena. One CLI, self-hostable.

We've been using Cua-Bench internally—and with customers—for the last few months to evaluate every computer-use agent we deploy. Today it's open-source. 15 public tasks, 40 variations, adapters for OSWorld and Windows Agent Arena. One CLI, self-hostable.

Cua

87,427 views • 9 months ago

2/ Task Bridge Computer use agent that reads through your slack messages, identifies tasks, and submits them to Asana Zero effort task management with computer use

2/ Task Bridge Computer use agent that reads through your slack messages, identifies tasks, and submits them to Asana Zero effort task management with computer use

Alex Reibman 🖇️

43,619 views • 1 year ago

With Astra, ChatGPT is nearly 2x faster at computer use than before. In addition to the amazing new model, we’ve optimized the harness to make computer use run much faster. These optimizations work in existing models too, so tasks are sped up by ~60% in GPT-5.6 Sol. Try it!

With Astra, ChatGPT is nearly 2x faster at computer use than before. In addition to the amazing new model, we’ve optimized the harness to make computer use run much faster. These optimizations work in existing models too, so tasks are sped up by ~60% in GPT-5.6 Sol. Try it!

Ari Weinstein

292,785 views • 1 month ago

He is 18 teaching AI at Stanford making $2.2M on agents - and in 60 minutes revealed how to repeat it from zero: 00:30 - 5% who build agents will replace the 95% who just use them 38:33 - Jev Engineering is the only thing you need to make $2.2M on an agent 52:47 - Claude + Jev 10x cheaper and faster right now after watching I built my first agent with Jev in 15 minutes and sold it to a million dollar company for $100k: save & watch - the article below shows how to use Jev Engineering to make Claude 10x cheaper and build a $2.2M agent.

He is 18 teaching AI at Stanford making $2.2M on agents - and in 60 minutes revealed how to repeat it from zero: 00:30 - 5% who build agents will replace the 95% who just use them 38:33 - Jev Engineering is the only thing you need to make $2.2M on an agent 52:47 - Claude + Jev 10x cheaper and faster right now after watching I built my first agent with Jev in 15 minutes and sold it to a million dollar company for $100k: save & watch - the article below shows how to use Jev Engineering to make Claude 10x cheaper and build a $2.2M agent.

Noisy

13,207 views • 1 month ago

Today we're announcing cua-bench: a framework for benchmarking, training data, and RL environments for computer-use AI agents. Why? Current agents show 10x variance across minor UI changes. Here's how we're fixing it.

Today we're announcing cua-bench: a framework for benchmarking, training data, and RL environments for computer-use AI agents. Why? Current agents show 10x variance across minor UI changes. Here's how we're fixing it.

Cua

189,823 views • 10 months ago

jev has changed computer-use forever. i built a computer use tool with jev that costs basically nothing to use, and has sub-second latency. it can even decide what to type, and doesn't need an LLM. open source. link below. no LLM required.

jev has changed computer-use forever. i built a computer use tool with jev that costs basically nothing to use, and has sub-second latency. it can even decide what to type, and doesn't need an LLM. open source. link below. no LLM required.

shiv

173,496 views • 1 month ago

We’ve been working with OpenAI for the past few weeks to test their latest Computer-using Agent model. On our evals, CUA has set a new SOTA. Once integrated with an agent, it can complete long-horizon tasks previously impossible. Try CUA on our playground and Act SDK for free!

We’ve been working with OpenAI for the past few weeks to test their latest Computer-using Agent model. On our evals, CUA has set a new SOTA. Once integrated with an agent, it can complete long-horizon tasks previously impossible. Try CUA on our playground and Act SDK for free!

Scrapybara

90,006 views • 1 year ago