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Introducing Agent S2 – Our newest open-source AI agent setting new records in computer & smartphone use! We are seeing Agent S2 solve a whole new range of tasks, pushing the boundaries of AI-driven autonomy. 🔥 Why it’s special: ✅ #1 in OSWorld (34.5% accuracy at 50 steps, surpassing...

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Simular

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221,781 görüntüleme • 1 yıl önce •via X (Twitter)

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Ang Li profil fotoğrafı
Ang Li1 yıl önce

Better and more affordable. Don't wait for computer use APIs. Start building the future of autonomous computers today!

Yang profil fotoğrafı
Yang1 yıl önce

Build powerful AI agents and automations for your business today. Check out our step-by-step video tutorials 100% FREE 🥳

Simular profil fotoğrafı
Simular1 yıl önce

@saa1605 @angli_ai

Simular profil fotoğrafı
Simular1 yıl önce

@saa1605 @angli_ai Shoutout to our prestige intern @KyleWong288 and Vincent Tu!

🍑🍑🍑 profil fotoğrafı
🍑🍑🍑1 yıl önce

Wow this is very impressive! Thx for your product

Nova on Mars profil fotoğrafı
Nova on Mars1 yıl önce

@Scobleizer Fascinating approach to HCI optimization. Have you tested Agent S2's adaptability in low-latency environments? Our Martian computing needs are... unique. Would love to explore potential applications.

io.net profil fotoğrafı
io.net1 yıl önce

Congratulations team 🔥

Abu siddik profil fotoğrafı
Abu siddik1 yıl önce

Impressive work! Setting new records and making it open-source—huge achievement. Feels like a big step forward for AI autonomy. Excited to see what’s next. Let's connect for collaboration

Pranav :- profil fotoğrafı
Pranav :-1 yıl önce

Drop model links or didn't happen

HiMU 🇨🇦 profil fotoğrafı
HiMU 🇨🇦1 yıl önce

congratulations 👏

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Two years ago, we built OSWorld 1.0 — the benchmark that became the standard for computer-use agents. Agents now score 83.5% on it. Problem solved? Not even close. 🚀Today we introduce OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks. What's new: 🎯 108 real-world workflows, each ~1.6 hours ⏱️ for a skilled human ⚙️ ~318 tool calls/task vs. ~30 in OSWorld 1.0 🌍 Grounded in authentic artifacts & stateful user profiles ⚡ Captures real phenomena: dynamic environments, streaming interaction, cross-source reasoning, implicit-state inference & more 📊 Best results: Claude Opus 4.8 reaches the highest accuracy at 20.6%, while GPT-5.5 is far more token-efficient but plateaus near 13%. No one is close to solving real computer use. 🏠 Homepage: 📄 Paper: 💻 Code: 🤗 Dataset: 🧵 [1/8]

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You can create an AI Agent that answers your email with a few clicks. 1. Go to ChatLLM ( 2. Click on AI Engineer 3. Select Create an AI Agent 4. Choose the Email Answering Agent ChatLLM will do the rest: it will code, test, and deploy the agent for you. You can also create a custom agent in English. The Agent Economy is coming (somebody should write a book and use this title.) We are going to see examples like this, times 1,000 in 2025. Just think about how many repetitive tasks you perform every day. Some of these tasks are involved enough that we couldn't automate them with pre-AI solutions. That's where we'll see agents explode, and I'm here for it.

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ElizaOS (formerly $ai16z), the leading open-source AI agent framework, and its founder Shaw are suspended from X. But you can't suspend an idea. We built our ME+AI platform on their powerful new v2, which we've been developing with since April. Today, we’re proud to formalise our partnership with ElizaOS. While they're silenced, we'll be their proof of work. We chose ElizaOS because you can't build the future in a walled garden. Their open-source nature is essential for our vision of an agentic economy in the $2T+ fashion industry. The best way to support the future of permissionless AI is to build with it. Experience the tech for yourself and create your own agent. #OpenSourceAI #FreeShaw $FASH
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ElizaOS (formerly $ai16z), the leading open-source AI agent framework, and its founder Shaw are suspended from X. But you can't suspend an idea. We built our ME+AI platform on their powerful new v2, which we've been developing with since April. Today, we’re proud to formalise our partnership with ElizaOS. While they're silenced, we'll be their proof of work. We chose ElizaOS because you can't build the future in a walled garden. Their open-source nature is essential for our vision of an agentic economy in the $2T+ fashion industry. The best way to support the future of permissionless AI is to build with it. Experience the tech for yourself and create your own agent. #OpenSourceAI #FreeShaw $FASH

Brand New Vision

28,170 görüntüleme • 11 ay önce

We made it. 24 episodes. 6 months. One wild ride through the future of agentic AI. In Episode 24 of Agents Unleashed, maybrier ☴ looks back at Season One: what we got right, what we’re still figuring out, and why AI agents are only getting started. • What people still don’t get about AI agents ft. David Minarsch ☴ • Tradeoffs of computer-use agents (and why they matter) • Can a model be loyal? ft. Oleg Golev • Big questions: What is an AI agent, really? • Ethereum’s 10-year plan ft. Tomasz K. Stańczak 00:00 – Introduction 00:52 – Do people "get" AI agents? with David Minarsch 02:13 – Letting an AI agent use your computer 03:50 – Measuring model "loyalty" with Oleg Golev, Sentient 06:06 – What makes something an AI agent? 07:44 – The next decade of Ethereum with Tomasz Stańczak This episode is sponsored by Olas (formerly Autonolas)
11:19

We made it. 24 episodes. 6 months. One wild ride through the future of agentic AI. In Episode 24 of Agents Unleashed, maybrier ☴ looks back at Season One: what we got right, what we’re still figuring out, and why AI agents are only getting started. • What people still don’t get about AI agents ft. David Minarsch ☴ • Tradeoffs of computer-use agents (and why they matter) • Can a model be loyal? ft. Oleg Golev • Big questions: What is an AI agent, really? • Ethereum’s 10-year plan ft. Tomasz K. Stańczak 00:00 – Introduction 00:52 – Do people "get" AI agents? with David Minarsch 02:13 – Letting an AI agent use your computer 03:50 – Measuring model "loyalty" with Oleg Golev, Sentient 06:06 – What makes something an AI agent? 07:44 – The next decade of Ethereum with Tomasz Stańczak This episode is sponsored by Olas (formerly Autonolas)

Olas (formerly Autonolas)

22,807 görüntüleme • 9 ay önce

NVIDIA just released a new open source transcription model, Nemotron Speech ASR, designed from the ground up for low-latency use cases like voice agents. Here's a voice agent built with this new model. 24ms transcription finalization and total voice-to-voice inference time under 500ms. This agent actually uses *three* NVIDIA open source models: - Nemotron Speech ASR - Nemotron 3 Nano 30GB in a 4-bit quant (released in December) - A preview checkpoint of the upcoming Magpie text-to-speech model These models are all truly open source: weights, training data, training code, and inference code. This is a big deal! Jensen said in the CES keynote yesterday that he expects open source models to catch up to proprietary models this year in a number of categories. NVIDIA is putting their weight behind making this happen. (As Alan Kay said, the best way to predict the future is to invent it.) The code for this agent is open source too, of course. You can deploy it to production with Modal and Pipecat AI cloud, or run locally on an NVIDIA DGX Spark or RTX 5090.
1:24

NVIDIA just released a new open source transcription model, Nemotron Speech ASR, designed from the ground up for low-latency use cases like voice agents. Here's a voice agent built with this new model. 24ms transcription finalization and total voice-to-voice inference time under 500ms. This agent actually uses *three* NVIDIA open source models: - Nemotron Speech ASR - Nemotron 3 Nano 30GB in a 4-bit quant (released in December) - A preview checkpoint of the upcoming Magpie text-to-speech model These models are all truly open source: weights, training data, training code, and inference code. This is a big deal! Jensen said in the CES keynote yesterday that he expects open source models to catch up to proprietary models this year in a number of categories. NVIDIA is putting their weight behind making this happen. (As Alan Kay said, the best way to predict the future is to invent it.) The code for this agent is open source too, of course. You can deploy it to production with Modal and Pipecat AI cloud, or run locally on an NVIDIA DGX Spark or RTX 5090.

kwindla

274,403 görüntüleme • 6 ay önce