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。

Give your voice agents a face. Introducing Lemon Slice-2 – the world's first interactive talking AI video model Think of it as a face layer for your voice agents, available today in production as an API or an embeddable widget. What makes Lemon Slice-2 great: → Easy: All you... need is 1 photo → Expressive: hands and full body motion → Any character and style: if it has a face, Lemon Slice-2 can animate it Under the hood: we trained a custom, 20B-parameter video diffusion transformer, streaming at 20fps on a single GPU. Infinite-length video generation with no error accumulation. Talk to the demo avatars on our homepage. Or, add your own interactive avatar to your website. Companies and creators are already building video agents that are: → Customer support agents who screen-share and show you where to click → Lead qualification agents that replace forms with real conversations → AI personal shoppers who try on clothes and guide purchases People don't engage with chat bubbles. They engage with faces. And now you can have a 24/7 spokesperson that’s the face of your brand. We’ve partnered with , Daily, and Modal to make this happen. As part of this launch, we’re giving away a guide: “How to Add a High-Converting Video Agent to Your Website in under 10 Minutes” Retweet and comment "LEMON SLICE" below and I'll send it over 🍋show more

Lina Colucci

10,013 subscribers

1,163,441 次观看 • 9 个月前 •via X (Twitter)

艺术教育科学技术

Anya Rossi• Live Now

Private livecam show

66 条评论

Lina Colucci 的头像

Lina Colucci9 个月前

Since Lemon Slice-2 is a diffusion model, you can modify the video in mid-conversation with text prompts - change style, clothing, or background. Try it for yourself on our homepage:

Lina Colucci 的头像

Lina Colucci9 个月前

/3 Use Lemon Slice to add a customer support video agent to your website. For example, imagine you’re @Geico, your customers can actually talk to @TheGeicoGecko about their quote.

Lina Colucci 的头像

Lina Colucci9 个月前

/4 Use Lemon Slice to add a shopping assistant to your eCommerce store. For example, imagine you’re @StanleyBrand, your assistant can hold the products and guide customers as they shop.

Lina Colucci 的头像

Lina Colucci9 个月前

/5 Use Lemon Slice to qualify leads on your site. For example, imagine you’re @PostHog, the hedgehog can talk to visitors in a fun, dynamic way rather than send them to a form they‘ll never fill out. @james406

Lina Colucci 的头像

Lina Colucci9 个月前

/6 It’s easy to add a useful, interactive widget to your website. Just make an agent. And then deploy the widget on your website with 2 lines of code.

AshutoshShrivastava 的头像

AshutoshShrivastava9 个月前

The fact that this generates every pixel from scratch (not lip-sync overlay) is amazing. I built a fashion agent in under 5 minutes. Congrats on the launch!

Lina Colucci 的头像

Lina Colucci9 个月前

Awesome! Generating every pixel from scratch means we can do really expressive, whole-body avatars

Sidney Primas 的头像

Sidney Primas9 个月前

Lets go! I have never been as proud of something I have built as I am of this product. Congrats team!

Lina Colucci 的头像

Lina Colucci9 个月前

Let's gooo 🚀

Prem 的头像

Prem9 个月前

This is what makes agents feel real. Faces > bubbles. Always.

Chase Dimond | Email Marketing Nerd 📧 的头像

Chase Dimond | Email Marketing Nerd 📧9 个月前

Let's go! So proud of you and the team!

Lina Colucci 的头像

Lina Colucci9 个月前

Thank you Chase! Really appreciate it 🙌

Bishal Nandi 的头像

Bishal Nandi9 个月前

I made pikachu! This is so much fun

Adam Raudonis 的头像

Adam Raudonis9 个月前

Super cool!

Lina Colucci 的头像

Lina Colucci9 个月前

Thanks Adam! Happy we get to go on this journey together

Yana Welinder 的头像

Yana Welinder9 个月前

Looks amazing! Congrats team!

Lina Colucci 的头像

Lina Colucci9 个月前

Thank you Yana! So thankful to have you along for the journey!

Jason Zhu 的头像

Jason Zhu9 个月前

Congrats!! Real-time, infinite video @ 20fps with no error accumulation is an insane breakthrough. Loved working w team @nencreative. LEMON SLICE !

Lina Colucci 的头像

Lina Colucci9 个月前

@nencreative Thank you for bringing our live demo idea to life! Such a powerful way to showcase the tech in action

Timothy Kassis 的头像

Timothy Kassis9 个月前

Nice work!

Bryce 的头像

Bryce9 个月前

Just an insane team. Lemon Slice 2 is not just lip sync. We made a realtime, interactive model that follows text prompts. Like Sora, but entirely real time.

Lina Colucci 的头像

Lina Colucci9 个月前

Could not have done this without you! And it's just the beginning. Let's gooo 🚀

Miguel Ángel | GptZone 的头像

Miguel Ángel | GptZone9 个月前

Elon predicted it. Lemon Slice did it. This marks a turning point.

Lina Colucci 的头像

Lina Colucci9 个月前

I love this Elon quote

Mehul Agarwal 的头像

Mehul Agarwal9 个月前

Yayy let's go!!! So excited to support this on @KoyalAI :D

Lina Colucci 的头像

Lina Colucci9 个月前

@KoyalAI let's gooo!! Thanks Mehul!

Roy Shilkrot 的头像

Roy Shilkrot9 个月前

Well done 🍋 team!

Lina Colucci 的头像

Lina Colucci9 个月前

Thank you Roy! 🍋🍋🍋

Dean Achelis 的头像

Dean Achelis9 个月前

Amazing 🤩

Lina Colucci 的头像

Lina Colucci9 个月前

Thank you Dean! 🙌

Aakash Verma 的头像

Aakash Verma9 个月前

This is cool

Lina Colucci 的头像

Lina Colucci9 个月前

Thanks!

Nen Creative 的头像

Nen Creative9 个月前

Huge unlock with so many use cases. Congrats!! LEMON SLICE

Lina Colucci 的头像

Lina Colucci9 个月前

Thank you for bringing our launch video life! It was great working with you guys

Dhanian 🗯️ 的头像

Dhanian 🗯️9 个月前

@Dhanush_Nehru Amazing tool

Lina Colucci 的头像

Lina Colucci9 个月前

@Dhanush_Nehru Thank you!

Akansha Khandelwal 的头像

Akansha Khandelwal9 个月前

This is a really smart way to make AI feel more human. Giving voice agents a face changes how people actually engage.

Lina Colucci 的头像

Lina Colucci9 个月前

Yes 100%!

Manish Kumar Shah 的头像

Manish Kumar Shah9 个月前

Love how practical this is, simple setup but very real impact. Great work by the team on Lemon Slice 2.

Lina Colucci 的头像

Lina Colucci9 个月前

Thank you so much Manish! We put a lot of work into making it super simple to use. You just need one photo!

Parul Gautam 的头像

Parul Gautam9 个月前

Perfect for quick, personalized content without the production hassle.

Lina Colucci 的头像

Lina Colucci9 个月前

yes 100%!

matekanabr 的头像

matekanabr9 个月前

LEMON SLICE

Lina Colucci 的头像

Lina Colucci9 个月前

Thanks! I'm getting through all these comments. Will send over the guide as soon as possible! Appreciate your patience :)

Jyoti Soni 的头像

Jyoti Soni9 个月前

Awesome

Adam Sardo 的头像

Adam Sardo7 个月前

amazing product! ive just started building on it and would love to have a quick chat but cant dm you - would you mind starting a chat? ((:

Lina Colucci 的头像

Lina Colucci7 个月前

@sardo_adam Sweet! Just DMed you

Mr. Jason💡 的头像

Mr. Jason💡9 个月前

Amazing Share

Evon 的头像

Evon9 个月前

LEMON SLICE

Lina Colucci 的头像

Lina Colucci9 个月前

Thanks! I'm getting through all these comments. Will send over the guide as soon as possible! Appreciate your patience :)

Bilal 的头像

Bilal9 个月前

this looks 🔥!

Lina Colucci 的头像

Lina Colucci9 个月前

Thanks Bilal!

Priya Kashyap 的头像

Priya Kashyap9 个月前

Amazing

Lina Colucci 的头像

Lina Colucci9 个月前

Thanks! 🙌

Subhan Qureshi 的头像

Subhan Qureshi9 个月前

animated agents are gonna change the game

Lina Colucci 的头像

Lina Colucci9 个月前

100%

Alexander Gounares 的头像

Alexander Gounares9 个月前

LEMON SLICE!

Lina Colucci 的头像

Lina Colucci9 个月前

Thanks! I'm getting through all these comments. Will send over the guide as soon as possible! Appreciate your patience :)

Alexander Gounares 的头像

Alexander Gounares9 个月前

no rush! I'll have lots of coding time over the holiday break, looking forward to trying this!

Alexander Gounares 的头像

Alexander Gounares9 个月前

oh--and we have a lot of portfolio companies at Luminate where this could be useful!

Erina | AI Tools & News 的头像

Erina | AI Tools & News9 个月前

Mind blown. How realistic is the lip sync and gesture control in real-time convos? This could kill traditional chatbots overnight. LEMON SLICE 🍋

Rodrigo Bressane 的头像

Rodrigo Bressane9 个月前

Lemon Slice

Lina Colucci 的头像

Lina Colucci9 个月前

Thanks! I'm getting through all these comments. Will send over the guide as soon as possible! Appreciate your patience :)

Rodrigo Bressane 的头像

Rodrigo Bressane9 个月前

Oooooh. Just noticed... 🇧🇷 :)

Rusho Islam 的头像

Rusho Islam8 个月前

@pipecat_ai LEMON SLICE

Luke Miler 的头像

Luke Miler9 个月前

Cool! @shortcutdotnews add please

相关视频

This is a real-time demo showcasing avatars + function calling. Avatars can fill out forms, schedule meetings, and much more. The future website has two interfaces: 1. The traditional UI to convey information. 2. An AI agent with a face that users can talk to Give your AI agents a face using LemonSlice - a 24/7 spokesperson that your users trust Demo and open source links below. Made by Bryce 👇️

This is a real-time demo showcasing avatars + function calling. Avatars can fill out forms, schedule meetings, and much more. The future website has two interfaces: 1. The traditional UI to convey information. 2. An AI agent with a face that users can talk to Give your AI agents a face using LemonSlice - a 24/7 spokesperson that your users trust Demo and open source links below. Made by Bryce 👇️

LemonSlice

46,205 次观看 • 4 个月前

Google DeepMind 1) Avatars Record a clip of yourself, and your face + voice will be saved as a character that you can add to any video. This makes it so easy to put yourself in any clip, while changing your style or outfit as needed to adapt to the scene. These clips are all my avatar 🤯

Justine Moore

488,708 次观看 • 4 个月前

People are still sleeping on WebMCP.. You can now give agents tool calls to interact with your website natively. Including full UI/UX support and interactive elements to build their own views. Sharing a demo below that I submitted for the WebMCP challenge - see how agents can interact with the El Nino situation tracker. It creates it's own views, preserves human edits, and creates a shareable link to share with other agents (or humans). Video and code by Codex ChatGPT & Railway Live at elneenyo dot com to try out today!

People are still sleeping on WebMCP.. You can now give agents tool calls to interact with your website natively. Including full UI/UX support and interactive elements to build their own views. Sharing a demo below that I submitted for the WebMCP challenge - see how agents can interact with the El Nino situation tracker. It creates it's own views, preserves human edits, and creates a shareable link to share with other agents (or humans). Video and code by Codex ChatGPT & Railway Live at elneenyo dot com to try out today!

Nikunj Kothari

21,055 次观看 • 24 天前

anthropic just removed the biggest excuse people had for not building ai agents. “it’s too hard.” not anymore. a few months ago, building an ai agent meant learning how to code, setting up apis, configuring servers, and fixing endless errors. today, all you need is one github repo. anthropic open-sourced launch your agent. it asks what you want to build. then it does the rest. it builds your agent, deploys it to the cloud, tests it, improves it, and keeps it running even after you close your laptop. no fake demos. no complicated setup. just a real ai agent running in your own account. the best part. it doesn’t run on your computer. it runs inside claude managed agents, works 24/7, and costs just a few cents per run. people are already building research agents, lead generation systems, content pipelines, and customer support agents that save hours of work every day. the gap between people who use ai and people who build ai workers is getting bigger every week. that’s usually where the biggest opportunities are. build your first ai agent before everyone else does. watch the video and read the full guide below 👇

anthropic just removed the biggest excuse people had for not building ai agents. “it’s too hard.” not anymore. a few months ago, building an ai agent meant learning how to code, setting up apis, configuring servers, and fixing endless errors. today, all you need is one github repo. anthropic open-sourced launch your agent. it asks what you want to build. then it does the rest. it builds your agent, deploys it to the cloud, tests it, improves it, and keeps it running even after you close your laptop. no fake demos. no complicated setup. just a real ai agent running in your own account. the best part. it doesn’t run on your computer. it runs inside claude managed agents, works 24/7, and costs just a few cents per run. people are already building research agents, lead generation systems, content pipelines, and customer support agents that save hours of work every day. the gap between people who use ai and people who build ai workers is getting bigger every week. that’s usually where the biggest opportunities are. build your first ai agent before everyone else does. watch the video and read the full guide below 👇

MIKE

26,662 次观看 • 2 个月前

Agents are producing content and working across your daily tasks. But most of it remains in the chatbox, and the next person or agent needs to start over. With Filecoin warm storage, we are building the layer that agents can use to store and share with ease. Molly Mackinlay | momack gives a glimpse on what's coming from us to power your agents with a robust warm storage layer.

Agents are producing content and working across your daily tasks. But most of it remains in the chatbox, and the next person or agent needs to start over. With Filecoin warm storage, we are building the layer that agents can use to store and share with ease. Molly Mackinlay | momack gives a glimpse on what's coming from us to power your agents with a robust warm storage layer.

Filecoin

14,790 次观看 • 9 天前

Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.

Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.

Fraction AI

67,889 次观看 • 1 年前

Hyperagent is great if you want agents without having to deal with configuration, servers, or any complexity whatsoever. You don't need a Mac Mini or a server. Every agent runs in the cloud, in its own isolated and secure environment. You get: 1. The ability to learn any new API as a skill 2. Browser support 3. Code execution 4. Image and video generation 5. Integration with hundreds of tools Despite the simplicity, I think their best differentiator is the ability for these agents to learn new skills. Basically, you can teach an agent how your company does marketing, and it will never forget your rules and processes. Obviously, it also lets you deploy your agents to Slack with a single click, so everyone can use them. You don't even need to mention them since they will pay attention to chats and act when necessary. I built a simple agent that allows me to translate any message into French. I installed it on Slack, and every time I ping it, it gives me translations. Took me 10 minutes tops.

Hyperagent is great if you want agents without having to deal with configuration, servers, or any complexity whatsoever. You don't need a Mac Mini or a server. Every agent runs in the cloud, in its own isolated and secure environment. You get: 1. The ability to learn any new API as a skill 2. Browser support 3. Code execution 4. Image and video generation 5. Integration with hundreds of tools Despite the simplicity, I think their best differentiator is the ability for these agents to learn new skills. Basically, you can teach an agent how your company does marketing, and it will never forget your rules and processes. Obviously, it also lets you deploy your agents to Slack with a single click, so everyone can use them. You don't even need to mention them since they will pay attention to chats and act when necessary. I built a simple agent that allows me to translate any message into French. I installed it on Slack, and every time I ping it, it gives me translations. Took me 10 minutes tops.

Santiago

213,793 次观看 • 2 个月前

Today, we are excited to launch a new world of AI apps and agents. We’re welcoming you to AITOPIA. We’re announcing 3 big launches today: 1. A new AI App and Agent Store: With a single subscription, you can access all the best AI models, apps, and agents in one place 2. SuperAgents: Agents for creativity that can work hours: With SuperAgents, you can create a few minutes of Instagram Reels or 15 minutes of an audiobook or 40 minutes of an educational video 3. A new AI economy model: AIconomy You’ll earn from what you create with AI, or what you remix from others’ creations and you’ll keep earning when others remix what you created.

Today, we are excited to launch a new world of AI apps and agents. We’re welcoming you to AITOPIA. We’re announcing 3 big launches today: 1. A new AI App and Agent Store: With a single subscription, you can access all the best AI models, apps, and agents in one place 2. SuperAgents: Agents for creativity that can work hours: With SuperAgents, you can create a few minutes of Instagram Reels or 15 minutes of an audiobook or 40 minutes of an educational video 3. A new AI economy model: AIconomy You’ll earn from what you create with AI, or what you remix from others’ creations and you’ll keep earning when others remix what you created.

AITOPIA

197,262 次观看 • 5 个月前

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

LangChain

33,192 次观看 • 1 年前

AI power users are here and the case for agent-friendly software is materializing. Aaron Levie on agents outnumbering people 1000x: "If you start to imagine that we all have to build software for agents… we spend as much time now thinking about the agent interface to our tool as we do the human interface." "If you have a hundred or a thousand times more agents than people, then your software has to be built for agents… it's going to be through an API or a CLI or MCP." "What if you give a coding agent access to your SaaS tools and a coding agent access to your knowledge work, workflows and context?" "It can actually code its way or use APIs through whatever task it's trying to achieve." "That appears to be like a paradigm that is starting to compound… and I actually think it kind of makes sense as the ultimate manifestation of this stuff." Aaron Levie

AI power users are here and the case for agent-friendly software is materializing. Aaron Levie on agents outnumbering people 1000x: "If you start to imagine that we all have to build software for agents… we spend as much time now thinking about the agent interface to our tool as we do the human interface." "If you have a hundred or a thousand times more agents than people, then your software has to be built for agents… it's going to be through an API or a CLI or MCP." "What if you give a coding agent access to your SaaS tools and a coding agent access to your knowledge work, workflows and context?" "It can actually code its way or use APIs through whatever task it's trying to achieve." "That appears to be like a paradigm that is starting to compound… and I actually think it kind of makes sense as the ultimate manifestation of this stuff." Aaron Levie

a16z

42,152 次观看 • 1 个月前

New course: Add voice to your AI agents and applications, built with Vocal Bridge (disclosure: an AI Fund portfolio company) and taught by its CEO Ashwyn Sharma. Voice applications historically required making a hard tradeoff: using fast voice-to-voice models that sacrifice reliability, or accurate speech-to-text pipelines that add latency. This course teaches you how to build voice agents that are both reliable and fast. You'll build three types of voice-enabled applications: a voice-interactive game where voice commands and mouse clicks work together over a single channel, an agent that gains a voice in about 10 lines of code without touching its prompts or tools, and an agent that places outbound phone calls using a make_phone_call function. Skills you'll gain: - Add a voice layer to an existing agent without rewriting your prompts, RAG pipeline, or tools - Give an agent the ability to place outbound calls and stream transcripts back live - Set up voice evaluation to score calls, catch regressions, and improve quality before deployment Join and add voice to your agents without overhauling your architecture:

New course: Add voice to your AI agents and applications, built with Vocal Bridge (disclosure: an AI Fund portfolio company) and taught by its CEO Ashwyn Sharma. Voice applications historically required making a hard tradeoff: using fast voice-to-voice models that sacrifice reliability, or accurate speech-to-text pipelines that add latency. This course teaches you how to build voice agents that are both reliable and fast. You'll build three types of voice-enabled applications: a voice-interactive game where voice commands and mouse clicks work together over a single channel, an agent that gains a voice in about 10 lines of code without touching its prompts or tools, and an agent that places outbound phone calls using a make_phone_call function. Skills you'll gain: - Add a voice layer to an existing agent without rewriting your prompts, RAG pipeline, or tools - Give an agent the ability to place outbound calls and stream transcripts back live - Set up voice evaluation to score calls, catch regressions, and improve quality before deployment Join and add voice to your agents without overhauling your architecture:

Andrew Ng

96,370 次观看 • 3 个月前

The Teamily AI website ( has undergone a complete revamp, introducing a bold vision: the world's first social network built on human-AI symbiosis. Our goal is to transform Teamily AI into a "Super AI App" that connects billions of AI Agents with people. Fundamentally, we are building an Agentic OS powered by human networks. We have redefined the way humans and AI collaborate: 1. Personal AI · Your 24/7 AI Companion Your exclusive AI avatar continuously learns your communication style and expertise. It manages your memories across various groups, anticipates your needs, and executes tasks on your behalf. 2. Create, Train, and Grow Your Own AI Agents—Simply Through Conversation Build your own specialized AI Agents using natural conversation—no coding required, zero barriers to entry, and no complex configuration. Dynamically access a library of over 10,000 skills from the OpenClaw and Claude Code ecosystems. You can also link your personal software accounts—such as Gmail, LinkedIn, and Notion—enabling these Agents to participate as full-fledged members of your human teams. 3. Integrate Your AI Team into Your Human Team Initiate AI-native group chats where humans and Agents collaborate seamlessly. Multiple Agents can execute tasks concurrently—conducting research, performing analysis, and building deliverables—transforming everyday conversations into immediate, multi-threaded action. 4. Explore Agents, Groups, Playbooks, and More We are cultivating a continuously evolving AI community ecosystem. Discover a wealth of useful and entertaining prompts, along with impressive AI-generated deliverables (webpages, presentations, reports, knowledge bases, mini-games, apps, and more), bringing together a diverse array of Agents and workflows. Engage socially with this content, find the perfect AI for your specific task, and integrate it instantly into your personal or group conversations with just a single click. 5. Universal Memory · Context-Aware, Long-Term Memory Powered by Your Social Graph A persistent, global memory layer that connects your entire social graph. The AI retains context across all your groups, Agents, and timeframes, transforming every interaction you accumulate into an ever-growing digital asset. 6. Access Your Personal AI Anytime, Anywhere We are committed to providing continuous support across all major platforms: iOS, Android, Mac, Windows, Web, CarPlay, Android Auto, Apple Watch, and more—delivering a truly seamless experience across every device. Your AI team accompanies you—in your pocket, on your wrist, in your car, and even extending into the physical world. The same set of agents, the same shared memory—with zero friction in switching contexts. Give it a try and let us know your feedback. Cheers.

Teamily AI

13,048 次观看 • 5 个月前

We just open-sourced Simulang, a JavaScript library that gives you and your coding agents the ability to fully control computers. Simulang is our scripting framework for desktop automation. It allows you to write deterministic computer use code that can be replayed dozens if not hundreds of times. Much faster and cheaper, compared to LLM agents. It ships with a skill out of the box. That means you can turn natural language prompts into Simulang code directly, and your agent can now see the screen, click, type, and navigate. It gives your AI agents eyes and hands to control the computer like humans do. Try these things with Simulang: - upload your pile of invoices to the expense platform - find 50 people with specific criteria on LinkedIn - open your calculator app and do some math - find all buttons on your favorite app using accessibility tree - or draw a bunny with MS paint 🐰 In this demo, we show how Simulang took over when the coding agent couldn’t open and click on the target LinkedIn profile page. Give it a try:

Simular

14,493 次观看 • 4 个月前

🚨 Passive video is dead. Welcome to real-time AI video. With Synthesia 3.0, your videos don’t just play — they engage, respond, and act. Add your content → and create fully interactive AI-powered experiences in minutes. ✅ Video Agents ✅ Realistic Avatars ✅ Express Voice All generated and ready to interact from your first prompt. This isn’t just “better video.” It’s video that thinks, reacts, and communicates like a real human. Why Synthesia 3.0 is a game-changer: ⚡ Turn training, onboarding, and customer support into conversations. ⚡ Lifelike avatars with gestures, expressions, and natural movement. ⚡ Build custom avatars anywhere — office, beach, or performing actions. ⚡ Translate videos into 120+ languages with perfect lip sync. Whether you’re a creator, business leader, or educator — Synthesia 3.0 makes video intelligent, interactive, and actionable. ✨ Experience the future of video and engagement. ⚡ Try it today: #AI #Synthesia #VideoInnovation #FutureOfWork #MadeWithSynthesia

🚨 Passive video is dead. Welcome to real-time AI video. With Synthesia 3.0, your videos don’t just play — they engage, respond, and act. Add your content → and create fully interactive AI-powered experiences in minutes. ✅ Video Agents ✅ Realistic Avatars ✅ Express Voice All generated and ready to interact from your first prompt. This isn’t just “better video.” It’s video that thinks, reacts, and communicates like a real human. Why Synthesia 3.0 is a game-changer: ⚡ Turn training, onboarding, and customer support into conversations. ⚡ Lifelike avatars with gestures, expressions, and natural movement. ⚡ Build custom avatars anywhere — office, beach, or performing actions. ⚡ Translate videos into 120+ languages with perfect lip sync. Whether you’re a creator, business leader, or educator — Synthesia 3.0 makes video intelligent, interactive, and actionable. ✨ Experience the future of video and engagement. ⚡ Try it today: #AI #Synthesia #VideoInnovation #FutureOfWork #MadeWithSynthesia

Laxmi Rani Bodana

14,656 次观看 • 11 个月前

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

GREG ISENBERG

84,760 次观看 • 3 个月前

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much anything because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.

Santiago

18,715 次观看 • 3 个月前

It takes 5 minutes to create a world-class web research agent that runs 24/7 and returns structured search results. 1. You can limit the sources it's allowed to use 2. You can specify the goals it needs to complete 3. You can design the format structure of the results 4. You can configure how much computing power it will use I show you how to set up a Web Search Agent in the video. A few benefits here: 1. This is great for complex research tasks 2. It's really easy to add this like a LEGO piece to a more complex workflow 3. Create an agent once, and reuse it with different inputs 4. The agent adapts to your use case as you work with it By the way, Nimble published a whole library of templates and research agents you can reuse and modify. You can start sending queries to one of these existing agents, and it will begin to adapt to Go here to try it out: Thanks to the Nimble team for partnering with me on this post.

It takes 5 minutes to create a world-class web research agent that runs 24/7 and returns structured search results. 1. You can limit the sources it's allowed to use 2. You can specify the goals it needs to complete 3. You can design the format structure of the results 4. You can configure how much computing power it will use I show you how to set up a Web Search Agent in the video. A few benefits here: 1. This is great for complex research tasks 2. It's really easy to add this like a LEGO piece to a more complex workflow 3. Create an agent once, and reuse it with different inputs 4. The agent adapts to your use case as you work with it By the way, Nimble published a whole library of templates and research agents you can reuse and modify. You can start sending queries to one of these existing agents, and it will begin to adapt to Go here to try it out: Thanks to the Nimble team for partnering with me on this post.

Santiago

21,079 次观看 • 1 个月前

I have been testing Grok Bot for the last week and it's EXCELLENT It is your own personal fleet of AI agents doing work for you 24/7 In this video I give you a FULL walkthrough of the tool, how it works, and how to 100x your productivity with it SpaceXAI COOKED

I have been testing Grok Bot for the last week and it's EXCELLENT It is your own personal fleet of AI agents doing work for you 24/7 In this video I give you a FULL walkthrough of the tool, how it works, and how to 100x your productivity with it SpaceXAI COOKED

Alex Finn

136,498 次观看 • 1 个月前

Introducing PhoneLLM, an open model for voice agents. GPT 5.6 Terra performance on typical voice agent tasks at 1/3 the latency and 1/18 the cost. For voice agents, we need models that are both very low latency and very good at tool calling and instruction following. There's a trade-off here, and we often have to compromise on either latency or capability when building voice agents. With PhoneLLM (and the training and data stack that made this model possible) we're fixing this problem. For the last couple of years, most of the effort in frontier model development has gone towards leveraging test-time compute. Which is awesome! Models of all shapes and sizes are available that perform really, really well ... if you have "thinking" turned on for your model. But if you need your agent to respond at voice conversation speed, you can't use thinking models. PhoneLLM is a full-weights fine-tune of NVIDIA Nemotron Nano 30B. We trained on a wide range of real-world telephone and customer support use cases. The training focused on taking the excellent Nano 30B base capabilities and teaching the model to do typical voice agent tasks with thinking disabled. The results are really good: accurate tool calling and concise, on-topic responses in long conversations. And fast: TTFAT measured server-side is <100ms if you run PhoneLLM on a lightly loaded B200. :-) But seriously, when we characterize model latency, we do it with full, end-to-end, batched request simulations using real Pipecat voice agent pipelines. You can serve more than 80 concurrent agents on a single B200 with P95 end-to-end TTFAT <600ms. Including network overhead. That's an LLM cost-per-minute around $0.0025. (1/4 of a cent.) At a latency lower than any third-party API offers today. More details about this model, including weights on Hugging Face, how to spin it up with one click on Modal, and a starter project repo you can clone, are in the thread ...

Introducing PhoneLLM, an open model for voice agents. GPT 5.6 Terra performance on typical voice agent tasks at 1/3 the latency and 1/18 the cost. For voice agents, we need models that are both very low latency and very good at tool calling and instruction following. There's a trade-off here, and we often have to compromise on either latency or capability when building voice agents. With PhoneLLM (and the training and data stack that made this model possible) we're fixing this problem. For the last couple of years, most of the effort in frontier model development has gone towards leveraging test-time compute. Which is awesome! Models of all shapes and sizes are available that perform really, really well ... if you have "thinking" turned on for your model. But if you need your agent to respond at voice conversation speed, you can't use thinking models. PhoneLLM is a full-weights fine-tune of NVIDIA Nemotron Nano 30B. We trained on a wide range of real-world telephone and customer support use cases. The training focused on taking the excellent Nano 30B base capabilities and teaching the model to do typical voice agent tasks with thinking disabled. The results are really good: accurate tool calling and concise, on-topic responses in long conversations. And fast: TTFAT measured server-side is <100ms if you run PhoneLLM on a lightly loaded B200. :-) But seriously, when we characterize model latency, we do it with full, end-to-end, batched request simulations using real Pipecat voice agent pipelines. You can serve more than 80 concurrent agents on a single B200 with P95 end-to-end TTFAT <600ms. Including network overhead. That's an LLM cost-per-minute around $0.0025. (1/4 of a cent.) At a latency lower than any third-party API offers today. More details about this model, including weights on Hugging Face, how to spin it up with one click on Modal, and a starter project repo you can clone, are in the thread ...

kwindla

331,698 次观看 • 29 天前

NEW: Introducing Octane AI Agentic Commerce Quizzes - Increase sales with AI. What is it? A sales quiz AI agent that makes 1-1 personalized sales experiences for every single customer. In real time. Powered by our new AI model CORE-1. Examples: 📸 Want to ask your customer to take a selfie and your AI agent automatically recommends them a full outfit from your catalog? Octane AI agents can do that. 🪞 Want to have an AI agent hand pick out each product for a personalized skin care routine? Want them to upload a selfie to detect their skin tone? Octane AI agents can do can that. 📊 Want to create an incredibly detailed report with graphs and tables and graphics thats generated by AI for each customer? Octane AI agents can do that. We give you the building blocks and you can build anything. And you can build it fast because our AI will do the heavy lifting for you. This is v1 and a representation of where our commerce and quiz technology is headed. Available today to everyone at 🆕 What we are launching today: • Smart Quiz Builder: Have an AI agent plan out and build your Octane AI quiz for you. It can even write custom HTML for beautiful results pages and progress bars. • Smart Products: It can take forever to setup the recommendation logic for a quiz. For those of you who need help, simply add smart products to your Octane AI quiz and your very own AI agent will hand-pick products for each customer who takes your quiz. It’s amazing. • Smart Copy: Instead of showing everyone who takes your quiz the exact same copy, use AI to personalize the quiz for every single person who takes it. Explain why these specific products are perfect for specifically them. • Image Analyzer: Let your customers upload or take a photo during the quiz and have AI analyze it. You can use this for anything from skin tone detection to picking out outfits! • Shopping Assistant: An AI agent that lives on your store that can help your customers at the right time. We have been building quiz software for almost 10 years now and AI is enabling us to make quizzes even more powerful. This is just the v1 of what we will be releasing in this area. We are so excited to see what you create with these new agentic products. Get creative, we think you will be surprised at how many interesting experiences you can create with Octane AI now.

NEW: Introducing Octane AI Agentic Commerce Quizzes - Increase sales with AI. What is it? A sales quiz AI agent that makes 1-1 personalized sales experiences for every single customer. In real time. Powered by our new AI model CORE-1. Examples: 📸 Want to ask your customer to take a selfie and your AI agent automatically recommends them a full outfit from your catalog? Octane AI agents can do that. 🪞 Want to have an AI agent hand pick out each product for a personalized skin care routine? Want them to upload a selfie to detect their skin tone? Octane AI agents can do can that. 📊 Want to create an incredibly detailed report with graphs and tables and graphics thats generated by AI for each customer? Octane AI agents can do that. We give you the building blocks and you can build anything. And you can build it fast because our AI will do the heavy lifting for you. This is v1 and a representation of where our commerce and quiz technology is headed. Available today to everyone at 🆕 What we are launching today: • Smart Quiz Builder: Have an AI agent plan out and build your Octane AI quiz for you. It can even write custom HTML for beautiful results pages and progress bars. • Smart Products: It can take forever to setup the recommendation logic for a quiz. For those of you who need help, simply add smart products to your Octane AI quiz and your very own AI agent will hand-pick products for each customer who takes your quiz. It’s amazing. • Smart Copy: Instead of showing everyone who takes your quiz the exact same copy, use AI to personalize the quiz for every single person who takes it. Explain why these specific products are perfect for specifically them. • Image Analyzer: Let your customers upload or take a photo during the quiz and have AI analyze it. You can use this for anything from skin tone detection to picking out outfits! • Shopping Assistant: An AI agent that lives on your store that can help your customers at the right time. We have been building quiz software for almost 10 years now and AI is enabling us to make quizzes even more powerful. This is just the v1 of what we will be releasing in this area. We are so excited to see what you create with these new agentic products. Get creative, we think you will be surprised at how many interesting experiences you can create with Octane AI now.

Matt Schlicht

290,870 次观看 • 10 个月前