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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!

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Ari Weinstein

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242,786 просмотров • 22 часов назад •via X (Twitter)

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Previewing Ultrafast mode for OpenAI's GPT 5.6 Sol, powered by Cerebras. GPT-5.6 Sol Ultrafast generates responses at up to 750 tokens per second. That's the full, GPT-5.6-Sol model -- up to 14× faster than the same model on Standard processing. It speedran Humanity’s Last Exam in 11h 11m, nearly 7× faster than Claude Fable 5 with comparable accuracy.
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Previewing Ultrafast mode for OpenAI's GPT 5.6 Sol, powered by Cerebras. GPT-5.6 Sol Ultrafast generates responses at up to 750 tokens per second. That's the full, GPT-5.6-Sol model -- up to 14× faster than the same model on Standard processing. It speedran Humanity’s Last Exam in 11h 11m, nearly 7× faster than Claude Fable 5 with comparable accuracy.

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The new ChatGPT Work comes with a new Computer Use experience. It's faster and introduces picture-in-picture, so you can keep an eye on Computer Use while it works!
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The new ChatGPT Work comes with a new Computer Use experience. It's faster and introduces picture-in-picture, so you can keep an eye on Computer Use while it works!

Ari Weinstein

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GPT-6 Astra “uses Unity to assemble a city scene from existing assets, allowing users to easily create an immersive 3D environment to explore that matches their vision.” “Alongside Astra, we are also updating the Codex harness to significantly improve the speed of computer use. Combined with Astra's efficiency, this translates to a 1.9x faster task completion compared to the current GPT-5.6 Sol experience, on the Mind2Web benchmark. “ “The model's improvements on speed mean it can take on many time consuming life tasks for you, faster than you can.*” I’ll admit, others and I have created far more impressive demos, but keep in mind this was done in Unity, which is a much more difficult environment for models to work with. If they weren’t using computer use which would’ve been extremely slow they were likely manipulating the project programmatically through C# and/or Unity’s YAML-serialized scene files which again models are pretty bad at. So this is a solid upgrade from 5.6 - from what I’ve seen unity!
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GPT-6 Astra “uses Unity to assemble a city scene from existing assets, allowing users to easily create an immersive 3D environment to explore that matches their vision.” “Alongside Astra, we are also updating the Codex harness to significantly improve the speed of computer use. Combined with Astra's efficiency, this translates to a 1.9x faster task completion compared to the current GPT-5.6 Sol experience, on the Mind2Web benchmark. “ “The model's improvements on speed mean it can take on many time consuming life tasks for you, faster than you can.*” I’ll admit, others and I have created far more impressive demos, but keep in mind this was done in Unity, which is a much more difficult environment for models to work with. If they weren’t using computer use which would’ve been extremely slow they were likely manipulating the project programmatically through C# and/or Unity’s YAML-serialized scene files which again models are pretty bad at. So this is a solid upgrade from 5.6 - from what I’ve seen unity!

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21,513 просмотров • 1 день назад

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.
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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.

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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.🧵
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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.🧵

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Today Google DeepMind released a state of the art computer use model, in partnership with Browserbase. Computer use is hard to evaluate. You need reliable browser infrastructure and realistic tasks. Below, we cover how we ran these benchmarks and how you can try yourself!
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Today Google DeepMind released a state of the art computer use model, in partnership with Browserbase. Computer use is hard to evaluate. You need reliable browser infrastructure and realistic tasks. Below, we cover how we ran these benchmarks and how you can try yourself!

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Today we're bringing ChatGPT Voice to the desktop app. The same incredible GPT Live model, now able use your entire computer. Try it with Codex & ChatGPT Work on desktop. Team really cooked. Now, here's Guinness Chen and jason:
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Today we're bringing ChatGPT Voice to the desktop app. The same incredible GPT Live model, now able use your entire computer. Try it with Codex & ChatGPT Work on desktop. Team really cooked. Now, here's Guinness Chen and jason:

Andrew Ambrosino

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The new ChatGPT Mac app is amazing. I got a fully working Breakout game code using a shortcut to pull up the app with GPT-4o and a simple screenshot of my screen. So many use cases and faster workflows.

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⚡️OPENAI: GPT-5.6 SOL IS 54% MORE TOKEN EFFICIENT ON AGENTIC CODING Sam Altman says the new GPT-5.6 Sol model is 54% more token efficient on agentic coding tasks and is “as good or better” than competing models. He also said OpenAI aims to offer better value with “every enterprise now is thinking about spend and the value they’re getting in exchange for AI.”

Coin Bureau

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Our first short course with Anthropic! Building Towards Computer Use with Anthropic. This teaches you to build an LLM-based agent that uses a computer interface by generating mouse clicks and keystrokes. Computer Use is an important, emerging capability for LLMs that will let AI agents do many more tasks than were possible before, since it lets them interact with interfaces designed for humans to use, rather than only tools that provide explicit API access. I hope you will enjoy learning about it! This course is taught by Anthropic's Head of Curriculum, Colt_Steele. You'll learn to apply image reasoning and tool use to "use" a computer as follows: a model processes an image of the screen, analyzes it to understand what's going on, and navigates the computer via mouse clicks and keystrokes. This course goes through the key building blocks, and culminates in a demo of an AI assistant that uses a web browser to search for a research paper, downloads the PDF, and finally summarizes the paper for you. In detail, you’ll: - Learn about Anthropic's family of models, when to use which one, and make API requests to Claude - Use multi-modal prompts that combine text and image content blocks, and also work with streaming responses - Improve your prompting by using prompt templates, using XML to structure prompts, and providing examples - Implement prompt caching to reduce cost and latency - Apply tool-use to build a chatbot that can call different tools to respond to queries - See all these building blocks come together in Computer Use demo Please sign up here:
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Our first short course with Anthropic! Building Towards Computer Use with Anthropic. This teaches you to build an LLM-based agent that uses a computer interface by generating mouse clicks and keystrokes. Computer Use is an important, emerging capability for LLMs that will let AI agents do many more tasks than were possible before, since it lets them interact with interfaces designed for humans to use, rather than only tools that provide explicit API access. I hope you will enjoy learning about it! This course is taught by Anthropic's Head of Curriculum, Colt_Steele. You'll learn to apply image reasoning and tool use to "use" a computer as follows: a model processes an image of the screen, analyzes it to understand what's going on, and navigates the computer via mouse clicks and keystrokes. This course goes through the key building blocks, and culminates in a demo of an AI assistant that uses a web browser to search for a research paper, downloads the PDF, and finally summarizes the paper for you. In detail, you’ll: - Learn about Anthropic's family of models, when to use which one, and make API requests to Claude - Use multi-modal prompts that combine text and image content blocks, and also work with streaming responses - Improve your prompting by using prompt templates, using XML to structure prompts, and providing examples - Implement prompt caching to reduce cost and latency - Apply tool-use to build a chatbot that can call different tools to respond to queries - See all these building blocks come together in Computer Use demo Please sign up here:

Andrew Ng

170,425 просмотров • 1 год назад

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I think all sites will use WebMCP in the future. Agents using your site are MUCH faster with it. Plus, it opens up the door for new, creative interactions:

Vinny

68,073 просмотров • 9 дней назад

Trump is babbling complete nonsense “Hopefully they'll be able to get these expensive computers going. You know, the reason you use computers is to make time so that it's like fast. You don't use them so that you have to come up with an answer three days later. And that's a little scary when they say what, what are they doing? You use a computer because it calculates quickly and you use paper because you save cost, but the paper turns out to be much quicker than the computer”
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Trump is babbling complete nonsense “Hopefully they'll be able to get these expensive computers going. You know, the reason you use computers is to make time so that it's like fast. You don't use them so that you have to come up with an answer three days later. And that's a little scary when they say what, what are they doing? You use a computer because it calculates quickly and you use paper because you save cost, but the paper turns out to be much quicker than the computer”

Headquarters

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Live on Cline (v3.67.1) OpenAI 's GPT 5.3 Codex. The speed and token efficiency improvements are real. Here is what's new: > 25% faster than 5.2 Codex > #1 on SWE-Bench Pro (4 different programming languages) > Fewer tokens per task than any prior OpenAI model Runs cost less and finish faster. You can use it in Cline right now without setting up an API key. Select the model and try it on your repo.

Cline

21,291 просмотров • 6 месяцев назад