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Ana Sayfaya Dön

Director is an open-source framework to build AI video agents that can reason through complex video tasks & instantly stream the results. Video tasks like: 🔍Search ✂️Clipping ✏️Editing 🗣️🔄Dubbing 🎥Generation e.g See the video agents in action 👇

Anup Gosavi

2,595 subscribers

499,715 görüntüleme • 1 yıl önce •via X (Twitter)

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10 Yorum

Sindhu Biswal profil fotoğrafı

Sindhu Biswal1 yıl önce

Would like to try

🟨🟩THE BUTCHER 🟨🟩 profil fotoğrafı

🟨🟩THE BUTCHER 🟨🟩1 yıl önce

I would love to try as well.

Rushab Jain profil fotoğrafı

Rushab Jain1 yıl önce

Cool stuff

Adarsh Kathriya profil fotoğrafı

Adarsh Kathriya1 yıl önce

why did u used claude 😅

Folarin Abraham profil fotoğrafı

Folarin Abraham1 yıl önce

This looks like a promising tool. I would like to be able to generate clips for different bosses or puzzles shown in video game walkthroughs. While I could not get it to automatically generate the clips, I was able to specify timestamps and download clips.

Ganesh Patil profil fotoğrafı

Ganesh Patil1 yıl önce

Crazy stuff 🚀

Reddy Gives profil fotoğrafı

Reddy Gives1 yıl önce

Everyone shud learn!

Leo Grundström profil fotoğrafı

Leo Grundström1 yıl önce

I would love to try this out!

prajein. profil fotoğrafı

prajein.1 yıl önce

this is awesome

Cecilia💓💫 樂✰ profil fotoğrafı

Cecilia💓💫 樂✰1 yıl önce

No one wants to watch Ai slop

Benzer Videolar

1/ Today, VideoDB is launching Director: Open-source framework to build AI video agents that can reason through complex video tasks & instantly stream the results. Video tasks like: 🔍Search ✂️Clipping ✏️Editing 🗣️🔄Dubbing 🎥Generation e.g Here’s a “Highlights agent” 👇

1/ Today, VideoDB is launching Director: Open-source framework to build AI video agents that can reason through complex video tasks & instantly stream the results. Video tasks like: 🔍Search ✂️Clipping ✏️Editing 🗣️🔄Dubbing 🎥Generation e.g Here’s a “Highlights agent” 👇

Anup Gosavi

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This is huge for video AI. Stream dropped Vision Agents, an open-source framework that lets AI watch and understand live video in real-time. - Sports coaching - Real-time threat detection - Live meeting assistants Combines YOLO, Gemini, OpenAI. Free. Open-source 🧵👇

This is huge for video AI. Stream dropped Vision Agents, an open-source framework that lets AI watch and understand live video in real-time. - Sports coaching - Real-time threat detection - Live meeting assistants Combines YOLO, Gemini, OpenAI. Free. Open-source 🧵👇

Alvaro Cintas

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Learn how to build a Gemini 3 Deep Agents with this video from LangChain. These agents can reason through complex, long horizon tasks by: > Breaking goals into actionable steps > Delegating specific work for specialized models > Leveraging file systems and code execution

Learn how to build a Gemini 3 Deep Agents with this video from LangChain. These agents can reason through complex, long horizon tasks by: > Breaking goals into actionable steps > Delegating specific work for specialized models > Leveraging file systems and code execution

Google AI Developers

19,484 görüntüleme • 7 ay önce

It’s getting insanely easy to build complex multi-agent systems in n8n. You can now build supervisor agents that delegates tasks to specialized sub agents. Just add the sub agents via AI Agent Tool node. All in one place and a lot easier to debug! Zero code!

It’s getting insanely easy to build complex multi-agent systems in n8n. You can now build supervisor agents that delegates tasks to specialized sub agents. Just add the sub agents via AI Agent Tool node. All in one place and a lot easier to debug! Zero code!

elvis

45,690 görüntüleme • 11 ay önce

Simplest way to create an AI agent today: You don't need to write any code. You don't need to build a workflow. You can literally build agents that complete useful tasks for you using a single prompt. Check the quick video I recorded!

Simplest way to create an AI agent today: You don't need to write any code. You don't need to build a workflow. You can literally build agents that complete useful tasks for you using a single prompt. Check the quick video I recorded!

Santiago

62,639 görüntüleme • 9 ay önce

AI Agents, explained in Yoruba. AI Agents (Ọ̀gbọ́n àpinlẹ̀rọ aláròbọ) are tools that can plan tasks, use tools, and act on your behalf. How are they different from chatbots? This video is part of my Tech and AI literacy series in Yoruba:

AI Agents, explained in Yoruba. AI Agents (Ọ̀gbọ́n àpinlẹ̀rọ aláròbọ) are tools that can plan tasks, use tools, and act on your behalf. How are they different from chatbots? This video is part of my Tech and AI literacy series in Yoruba:

Wuraola Oyewusi

18,398 görüntüleme • 6 ay önce

"I really don't want to manage an AI team." Cathryn found a solution: Paperclip, the open-source project What she showed me: • Paperclip leads her agents using its project management setup • Humans on her team use it to assign tasks to agents • Agents delegate tasks to humans or other agents • Paperclip turns your goals into agent tasks • It turns an SEO audit doc (for example) into agent tasks • It organizes OpenClaw agents OR even creates its own agents Also: fast-forward to 9min25sec to see a 3-minute Paperclip setup. (YouTube version in first comment.)

"I really don't want to manage an AI team." Cathryn found a solution: Paperclip, the open-source project What she showed me: • Paperclip leads her agents using its project management setup • Humans on her team use it to assign tasks to agents • Agents delegate tasks to humans or other agents • Paperclip turns your goals into agent tasks • It turns an SEO audit doc (for example) into agent tasks • It organizes OpenClaw agents OR even creates its own agents Also: fast-forward to 9min25sec to see a 3-minute Paperclip setup. (YouTube version in first comment.)

Andrew Warner

54,178 görüntüleme • 3 ay önce

We're excited to announce that Coinbase Developer Platform🛡️ AgentKit supports the new OpenAI Agents SDK. OpenAI’s new Agents SDK is an open source framework for building and scaling agents that includes built-in tools for web search, file search, and computer use, and tools to track and optimize agent performance—making it easier than ever to build production-ready AI agents. Coinbase AgentKit complements this by adding secure crypto wallets directly to your agents, enabling them to transact globally, instantly, and with near-zero fees—unlocking true financial autonomy.

We're excited to announce that Coinbase Developer Platform🛡️ AgentKit supports the new OpenAI Agents SDK. OpenAI’s new Agents SDK is an open source framework for building and scaling agents that includes built-in tools for web search, file search, and computer use, and tools to track and optimize agent performance—making it easier than ever to build production-ready AI agents. Coinbase AgentKit complements this by adding secure crypto wallets directly to your agents, enabling them to transact globally, instantly, and with near-zero fees—unlocking true financial autonomy.

Coinbase Developer Platform🛡️

20,287 görüntüleme • 1 yıl önce

INTELLIGENT TASKS ARE A STEPPING STONE TO AGI Today, we are launching ChatLLM Tasks. We have hooked up tools like web search, email, and web scrappers to mini-agents that can be triggered on a schedule. These tasks combine intelligent tool use with crons! We think this is the first step towards AGI. The next step is to connect our AI engineer to create more complex tasks. AGI STEP ONE - DONE!

INTELLIGENT TASKS ARE A STEPPING STONE TO AGI Today, we are launching ChatLLM Tasks. We have hooked up tools like web search, email, and web scrappers to mini-agents that can be triggered on a schedule. These tasks combine intelligent tool use with crons! We think this is the first step towards AGI. The next step is to connect our AI engineer to create more complex tasks. AGI STEP ONE - DONE!

Bindu Reddy

18,486 görüntüleme • 1 yıl önce

Ok finally dug into Meta's new Movie Gen paper. Text-to-video is cool and all but, to me the precise editing feature is the game changer. I mean just look at these results 🤯 It can handle complex VFX tasks like replacing environments, doing set extensions, swapping characters, removing items, adding particle effects with realistic lighting interaction. The coolest bit to me is how they trained this model, because paired before/after vfx editing datasets are super scarce. TL;DR They taught it video editing through a clever three-stage process: 1. Started with image editing data, treating it like single-frame video edits. 2. Created synthetic video editing tasks by animating still image edits and using AI models (like SAM and DINO) for object segmentation. 3. The model generated edited videos, and then learned to reconstruct the originals from the edited version Meta calls this "video editing via backtranslation" and the results speak for themselves.

Ok finally dug into Meta's new Movie Gen paper. Text-to-video is cool and all but, to me the precise editing feature is the game changer. I mean just look at these results 🤯 It can handle complex VFX tasks like replacing environments, doing set extensions, swapping characters, removing items, adding particle effects with realistic lighting interaction. The coolest bit to me is how they trained this model, because paired before/after vfx editing datasets are super scarce. TL;DR They taught it video editing through a clever three-stage process: 1. Started with image editing data, treating it like single-frame video edits. 2. Created synthetic video editing tasks by animating still image edits and using AI models (like SAM and DINO) for object segmentation. 3. The model generated edited videos, and then learned to reconstruct the originals from the edited version Meta calls this "video editing via backtranslation" and the results speak for themselves.

Bilawal Sidhu

50,775 görüntüleme • 1 yıl önce

✨ All in One, Wan for All✨ We are excited to introduce our latest model to our talented community creators: Wan2.1-VACE, All-in-One Video Creation and Editing model. Model size: 1.3B, 14B License: Apache-2.0 📌 Wan2.1-VACE provides solutions for various tasks, including reference-to-video generation (R2V), video-to-video editing (V2V), and masked video-to-video editing (MV2V), allowing creators to freely combine these capabilities to achieve complex tasks. 👉 Multimodal inputs enhancing the controllability of video generation. 👉 Unified single model for consistent solutions across tasks. 👉 Free combination of capabilities unlocking deeper creative potentials. 😄 Wanna try? 1️⃣ Github: 2️⃣Hugging Face: 3️⃣ ModelScope: 4️⃣ API Service: 5️⃣ Coming soon!

✨ All in One, Wan for All✨ We are excited to introduce our latest model to our talented community creators: Wan2.1-VACE, All-in-One Video Creation and Editing model. Model size: 1.3B, 14B License: Apache-2.0 📌 Wan2.1-VACE provides solutions for various tasks, including reference-to-video generation (R2V), video-to-video editing (V2V), and masked video-to-video editing (MV2V), allowing creators to freely combine these capabilities to achieve complex tasks. 👉 Multimodal inputs enhancing the controllability of video generation. 👉 Unified single model for consistent solutions across tasks. 👉 Free combination of capabilities unlocking deeper creative potentials. 😄 Wanna try? 1️⃣ Github: 2️⃣Hugging Face: 3️⃣ ModelScope: 4️⃣ API Service: 5️⃣ Coming soon!

Wan

198,539 görüntüleme • 1 yıl önce

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Super excited to share 🧠MLGym 🦾 – the first Gym environment for AI Research Agents 🤖🔬 We introduce MLGym and MLGym-Bench, a new framework and benchmark for evaluating and developing LLM agents on AI research tasks. The key contributions of our work are: 🕹️ Enables the exploration of different training algorithms for AI Research Agents such as RL 🛠️ Provides a flexible evaluation framework that can accommodate different artifacts such as models, algorithms, or predictions 🤖 Allows researchers to evaluate any model without the need to develop a custom agentic harness 🎯 Introduces 13 diverse open-ended AI Research tasks for evaluating AI Research Agents on a wide range of domains such as computer vision, natural language processing, reinforcement learning, game theory, and logical reasoning. 📈 Proposes a new evaluation metric for AI Research Agents MLGym makes it easy to: 1) Add new tasks 2) Evaluate new models 3) Integrate new agents Check out a video of the MLGym Agent to see how it performs the full pipeline of idea generation💡, implementation 👩‍💻, experimentation 👩‍🔬, and iteration 🔄 to improve on ML tasks. Huge thanks to the exceptionally talented Deepak Nathani who led this work and to all the other amazing collaborators who made this possible 🙏🫶🚀

Roberta Raileanu

105,030 görüntüleme • 1 yıl önce

I made an AI data science team with Python. I'm excited to share my new project, the AI Data Science Team, a Python package for creating AI co-pilots and agents to assist in common data science tasks. I walk you through the GitHub page, showcasing the progress and potential of this project. I'll explain how these agents can streamline tasks like code generation and modeling pipeline creation, making data science projects more efficient. Introduction to AI Data Science Team Project Integrating Human-in-the-Loop Example: Accessing Agents for Feature Engineering Setting up Feature Engineering Agent Code On GitHub: Python AI-Tips Newsletter (stay updated as I build this project in the open):

I made an AI data science team with Python. I'm excited to share my new project, the AI Data Science Team, a Python package for creating AI co-pilots and agents to assist in common data science tasks. I walk you through the GitHub page, showcasing the progress and potential of this project. I'll explain how these agents can streamline tasks like code generation and modeling pipeline creation, making data science projects more efficient. Introduction to AI Data Science Team Project Integrating Human-in-the-Loop Example: Accessing Agents for Feature Engineering Setting up Feature Engineering Agent Code On GitHub: Python AI-Tips Newsletter (stay updated as I build this project in the open):

Matt Dancho (Business Science)

11,799 görüntüleme • 1 yıl önce

📢 OPEN AGENTS 🤖⚡️ A new video series in which we build an open platform for AI agents. ✅ 100% open-source ✅ Open models & data ✅ Open compute via GPUtopia ✅ Open money aka #bitcoin ✅ Open agent marketplace with rev-share ⚡️ Follow along 👉

📢 OPEN AGENTS 🤖⚡️ A new video series in which we build an open platform for AI agents. ✅ 100% open-source ✅ Open models & data ✅ Open compute via GPUtopia ✅ Open money aka #bitcoin ✅ Open agent marketplace with rev-share ⚡️ Follow along 👉

OpenAgents

594,254 görüntüleme • 2 yıl önce

The agentic enterprise is here. We’re unveiling new innovations across AI agents, real-time data, governance, & interoperability to help enterprises build AI that can reason, automate, and drive action at scale. Check out the highlights 👇

The agentic enterprise is here. We’re unveiling new innovations across AI agents, real-time data, governance, & interoperability to help enterprises build AI that can reason, automate, and drive action at scale. Check out the highlights 👇

Snowflake

18,668 görüntüleme • 1 ay önce

Hermes Desktop just removed the biggest barrier to AI agents. No more terminal. Here’s what changed everything: → You can now run Hermes in a clean Mac app → Edit memory + skills without SSH → Search every past conversation instantly → Run multi-agent workflows visually → Assign tasks like a real team board This turns AI from “tool” → “operator.” Save this video, you’ll finally understand how agents actually work. Want the SOP? DM me. 💬

Hermes Desktop just removed the biggest barrier to AI agents. No more terminal. Here’s what changed everything: → You can now run Hermes in a clean Mac app → Edit memory + skills without SSH → Search every past conversation instantly → Run multi-agent workflows visually → Assign tasks like a real team board This turns AI from “tool” → “operator.” Save this video, you’ll finally understand how agents actually work. Want the SOP? DM me. 💬

Julian Goldie SEO

42,735 görüntüleme • 2 ay önce

One of the most impressive AI demo I've seen. This is the future of customer service. Agents that can understand text, speech, images and even live video. Soon to be all open-source.

One of the most impressive AI demo I've seen. This is the future of customer service. Agents that can understand text, speech, images and even live video. Soon to be all open-source.

Lior Alexander

270,967 görüntüleme • 1 yıl önce

Knowledge graphs are infinitely better than vector search for building the memory of AI agents. With five lines of code, you can build a knowledge graph with your data. When you see the results, you'll never go back to vector-mediocrity-land. Here is a quick video:

Knowledge graphs are infinitely better than vector search for building the memory of AI agents. With five lines of code, you can build a knowledge graph with your data. When you see the results, you'll never go back to vector-mediocrity-land. Here is a quick video:

Santiago

398,030 görüntüleme • 1 yıl önce

Introducing 🦀 CRAB: Cross-environment Agent Benchmark for Multimodal Language Model Agents 🦀 CRAB provides an end-to-end and easy-to-use framework to build multimodal agents, operate environments, and create benchmarks to evaluate them, featuring three key components: - 🔀 Cross-environment support - agents can operate tasks in 📱 Android and 💻 Ubuntu. - 🕸️ Graph evaluator - provides a fine-grain evaluation metric for agents. - 🤖 Task generation - composes subtasks to automatically generate tasks. By connecting all devices to agents, 🦀CRAB unlocks greater capabilities for human-like tasks than ever before. Use 🦀 CRAB to benchmark your multimodal agents! - 👨‍💻 Check out the repository: - 📝 Read the paper: - 🌐 Find out more via the project page: - 🐫 Join our community:

Introducing 🦀 CRAB: Cross-environment Agent Benchmark for Multimodal Language Model Agents 🦀 CRAB provides an end-to-end and easy-to-use framework to build multimodal agents, operate environments, and create benchmarks to evaluate them, featuring three key components: - 🔀 Cross-environment support - agents can operate tasks in 📱 Android and 💻 Ubuntu. - 🕸️ Graph evaluator - provides a fine-grain evaluation metric for agents. - 🤖 Task generation - composes subtasks to automatically generate tasks. By connecting all devices to agents, 🦀CRAB unlocks greater capabilities for human-like tasks than ever before. Use 🦀 CRAB to benchmark your multimodal agents! - 👨‍💻 Check out the repository: - 📝 Read the paper: - 🌐 Find out more via the project page: - 🐫 Join our community:

CAMEL-AI.org

72,661 görüntüleme • 1 yıl önce

AI agents need context. Smart glasses give you all the context I'm streaming HD video from my glasses And they stream everywhere. X, your app, OnlyFans, etc With open-source SDK so you can build stuff like calorie counter, super memory, "Her", etc.

AI agents need context. Smart glasses give you all the context I'm streaming HD video from my glasses And they stream everywhere. X, your app, OnlyFans, etc With open-source SDK so you can build stuff like calorie counter, super memory, "Her", etc.

cayden 凯登

39,021 görüntüleme • 9 ay önce