正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Perplexity Computer is massively multi-model. Computer orchestrates models to run agents in parallel, leveraging Opus to match each task to the model best suited for it. In total, Computer can route work across 19 different models.

Perplexity

460,687 subscribers

531,610 次观看 • 3 个月前 •via X (Twitter)

教育新闻政治科学技术

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Perplexity Computer orchestrates 20 different AI models - and now you can embed them directly inside apps you create. To prove it, we built CEO Chat. Text Elon, Jensen, Zuck, and other tech CEOs. They text back.

Perplexity Computer orchestrates 20 different AI models - and now you can embed them directly inside apps you create. To prove it, we built CEO Chat. Text Elon, Jensen, Zuck, and other tech CEOs. They text back.

Computer

84,243 次观看 • 3 个月前

You don’t have to use one model (or one provider!) for everything. With Workshop, you can combine frontier and local models in the same workflow. For example: Opus can be the main agent, and delegate specific tasks to Gemma 4 via subagents. Better quality where it matters. Better privacy, speed, and cost where it counts. One workflow, best model for each task.

You don’t have to use one model (or one provider!) for everything. With Workshop, you can combine frontier and local models in the same workflow. For example: Opus can be the main agent, and delegate specific tasks to Gemma 4 via subagents. Better quality where it matters. Better privacy, speed, and cost where it counts. One workflow, best model for each task.

Workshop AI

799,762 次观看 • 1 个月前

🚨 Perplexity dropped "Computer" and nobody is talking about it. An AI system that runs 19 models at once and builds entire projects by itself. It researches, designs, codes, and deploys live websites in minutes. No subscriptions to 5 different tools. No switching tabs. Here's how to use it:

🚨 Perplexity dropped "Computer" and nobody is talking about it. An AI system that runs 19 models at once and builds entire projects by itself. It researches, designs, codes, and deploys live websites in minutes. No subscriptions to 5 different tools. No switching tabs. Here's how to use it:

Nav Toor

33,583 次观看 • 2 个月前

ami is now a desktop app run parallel coding agents from your computer without breaking your flow claude opus 4.5 is unreasonably good but the interfaces around it haven't caught up go try it out for free :)

ami is now a desktop app run parallel coding agents from your computer without breaking your flow claude opus 4.5 is unreasonably good but the interfaces around it haven't caught up go try it out for free :)

Aiden Bai

81,801 次观看 • 4 个月前

The AI Super Bowl… ChatGPT vs Claude 🏈 Run your prompt across multiple models at once with /multi-agent then an AI judge picks the best answer so you don't have to. Need to quickly switch between models? Use /agent to switch to a different model in seconds but retain your context.

The AI Super Bowl… ChatGPT vs Claude 🏈 Run your prompt across multiple models at once with /multi-agent then an AI judge picks the best answer so you don't have to. Need to quickly switch between models? Use /agent to switch to a different model in seconds but retain your context.

BLACKBOX AI

309,750 次观看 • 4 个月前

Thank you Perplexity and Aravind Srinivas Bhai for the Mac Mini 🤟 Perplexity Computer + Mac Mini. Excited to test it out and see what it can do.

Thank you Perplexity and Aravind Srinivas Bhai for the Mac Mini 🤟 Perplexity Computer + Mac Mini. Excited to test it out and see what it can do.

AshutoshShrivastava

51,466 次观看 • 1 个月前

today we're launching a dataset of computer-use recordings to build the next generation of computer-use agents. 300+ tasks across all kinds of software. open-source. link in the comments. Markov

today we're launching a dataset of computer-use recordings to build the next generation of computer-use agents. 300+ tasks across all kinds of software. open-source. link in the comments. Markov

Dev

81,060 次观看 • 4 个月前

How to check if your recently delivered Model Y has the new HW4.5 computer

How to check if your recently delivered Model Y has the new HW4.5 computer

Brandon

323,015 次观看 • 4 个月前

Introducing screengrasp - The new SOTA agent click position model - beating Anthropic Computer Use, OmniParser and Molmo by a wide margin. - Simplified API access to the best click models on the market. 🔁Retweet and DM for free API credits. More details 👇

Introducing screengrasp - The new SOTA agent click position model - beating Anthropic Computer Use, OmniParser and Molmo by a wide margin. - Simplified API access to the best click models on the market. 🔁Retweet and DM for free API credits. More details 👇

Florian S

54,319 次观看 • 1 年前

Day to day cancer causing agents in daily routine fact check Grok Computer

Day to day cancer causing agents in daily routine fact check Grok Computer

GLOBAL NEWS

380,078 次观看 • 11 个月前

Breaking: Perplexity just announced Perplexity Computer on Mobile at their developer event in SF.

Breaking: Perplexity just announced Perplexity Computer on Mobile at their developer event in SF.

Morgan

34,592 次观看 • 3 个月前

subagents are just recursive agents where you can apply different prompts + models depending on the task. since they’re just a primitive, Cursor cli can actually spawn subagents by calling cursor-agent in headless mode via shell commands. that’s what makes the cli so nice. you can extend it, experiment, and have a lot of fun exploring orchestration patterns. here’s one way to do it w. dynamic model selection: 1. create a subagents.mdc rule 2. drop in: ``` --- alwaysApply: true --- ALWAYS spawn subagents by running `cursor-agent -p [task] --output-format=text --force --model [model]` in the terminal. Each subagent should return a summary of the changes it made. Subagents should be used for ALL tasks You can adopt a fan-out pattern where you spawn subagents to perform parallel isolated tasks, and then fan-in the results. Use the following models: - `--model gpt-5` for reasoning, researching, and planning - `--model sonnet-4` for implementation ``` 3. start cursor cli and try it out you can also adjust the rule to be more explicit when it should use subagents, when not to, which models when etc.

subagents are just recursive agents where you can apply different prompts + models depending on the task. since they’re just a primitive, Cursor cli can actually spawn subagents by calling cursor-agent in headless mode via shell commands. that’s what makes the cli so nice. you can extend it, experiment, and have a lot of fun exploring orchestration patterns. here’s one way to do it w. dynamic model selection: 1. create a subagents.mdc rule 2. drop in: ``` --- alwaysApply: true --- ALWAYS spawn subagents by running `cursor-agent -p [task] --output-format=text --force --model [model]` in the terminal. Each subagent should return a summary of the changes it made. Subagents should be used for ALL tasks You can adopt a fan-out pattern where you spawn subagents to perform parallel isolated tasks, and then fan-in the results. Use the following models: - `--model gpt-5` for reasoning, researching, and planning - `--model sonnet-4` for implementation ``` 3. start cursor cli and try it out you can also adjust the rule to be more explicit when it should use subagents, when not to, which models when etc.

eric zakariasson

54,017 次观看 • 9 个月前

Perplexity Computer uses Excel like a real financial analyst. We gave Computer Amazon's last 5 earnings releases. It built us a fully working 3-statement financial model with an assumptions tab, charts, and clean formatting that would impress your MD.

Perplexity Computer uses Excel like a real financial analyst. We gave Computer Amazon's last 5 earnings releases. It built us a fully working 3-statement financial model with an assumptions tab, charts, and clean formatting that would impress your MD.

Computer

82,810 次观看 • 3 个月前

Open weight models are now available in Kiro. Three open weight models are available in the IDE and CLI, so you don’t have to default to the largest model for every task. Choose the right model based on speed, cost, or long-running agentic workflows. What model would you like to see supported next? #Kiro #BuildwithKiro #AICoding

Open weight models are now available in Kiro. Three open weight models are available in the IDE and CLI, so you don’t have to default to the largest model for every task. Choose the right model based on speed, cost, or long-running agentic workflows. What model would you like to see supported next? #Kiro #BuildwithKiro #AICoding

Kiro

22,183 次观看 • 4 个月前

Looking to save? Meet the computer you can talk to.

Looking to save? Meet the computer you can talk to.

Windows

15,791,378 次观看 • 7 个月前

ByteDance just open sourced an AI SuperAgent that can research, code, build websites, create slide decks, and generate videos. All by itself. DeerFlow 2.0 (27K+ GitHub stars ⭐️), an AI system acting like an autonomous employee with its own computer workspace to research and code. Standard chatbots only generate text and forget your preferences. DeerFlow solves this by giving the AI an isolated virtual computer environment where it safely runs programs. When given a massive task, the main program creates several smaller AI assistants to work simultaneously. It also saves your past workflows so it gets smarter about your needs. DeerFlow is model-agnostic — it works with any LLM that implements the OpenAI-compatible API. Fully supports running local models on your own computer using tools like Ollama. An example - you ask for research on the top 10 AI startups in 2026 for a presentation, the lead agent in DeerFlow breaks that big job into smaller sub-tasks. It assigns one sub-agent to look into each company, another to find funding details, and a third to handle competitor analysis. These agents do all their work in parallel. Everything eventually converges, and a final agent pulls the results into a slide deck complete with custom visuals.

ByteDance just open sourced an AI SuperAgent that can research, code, build websites, create slide decks, and generate videos. All by itself. DeerFlow 2.0 (27K+ GitHub stars ⭐️), an AI system acting like an autonomous employee with its own computer workspace to research and code. Standard chatbots only generate text and forget your preferences. DeerFlow solves this by giving the AI an isolated virtual computer environment where it safely runs programs. When given a massive task, the main program creates several smaller AI assistants to work simultaneously. It also saves your past workflows so it gets smarter about your needs. DeerFlow is model-agnostic — it works with any LLM that implements the OpenAI-compatible API. Fully supports running local models on your own computer using tools like Ollama. An example - you ask for research on the top 10 AI startups in 2026 for a presentation, the lead agent in DeerFlow breaks that big job into smaller sub-tasks. It assigns one sub-agent to look into each company, another to find funding details, and a third to handle competitor analysis. These agents do all their work in parallel. Everything eventually converges, and a final agent pulls the results into a slide deck complete with custom visuals.

Rohan Paul

50,056 次观看 • 3 个月前

We made it easy to run local models on your computer and use them from your phone. A secure, end-to-end encrypted connection in just a few clicks. Available now with LM Studio and Locally AI - Local AI Chat.

We made it easy to run local models on your computer and use them from your phone. A secure, end-to-end encrypted connection in just a few clicks. Available now with LM Studio and Locally AI - Local AI Chat.

Adrien Grondin

12,045 次观看 • 11 天前

DDR4 ram can actually be modified to work in DDR5 motherboards - this is a safe and effective way to use the cheaper, inexpensive previous gen memory in your computer. 💯

DDR4 ram can actually be modified to work in DDR5 motherboards - this is a safe and effective way to use the cheaper, inexpensive previous gen memory in your computer. 💯

AlphaFox

699,216 次观看 • 6 个月前

Devin for Terminal is a local agent that works with all frontier models, including Opus 4.7, GPT 5.5, and SWE-1.6. You can switch model mid-session, or handoff to Devin in the cloud.

Devin for Terminal is a local agent that works with all frontier models, including Opus 4.7, GPT 5.5, and SWE-1.6. You can switch model mid-session, or handoff to Devin in the cloud.

Cognition

10,129,242 次观看 • 1 个月前