Загрузка видео...

Не удалось загрузить видео

Возникла проблема при загрузке этого видео. Это может быть связано с временными проблемами сети или видео может быть недоступно.

На главную

Introducing ✨Generative Interfaces where LLMs respond to users by proactively generating UIs that enable adaptive interaction 🎹 Piano practice tools, 🤖 neural net animations, and more🪄

Diyi Yang

22,048 subscribers

30,378 просмотров • 11 месяцев назад •via X (Twitter)

Здоровье и велнес Наука и технологии Образование

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Using monkey brain data to operate robotic arms! 🙉 Project Jenkins explores brain-computer interfaces by decoding neural activity into robotic movement and generating synthetic brain data from motion patterns. Using neural recordings from a macaque monkey named Jenkins, researchers developed models to decode brain signals into robotic arm movements and encode movement data into simulated neural activity. The project utilizes robotic arms and an interactive web console for real-time brain data generation from joystick inputs. The research paves the way for adaptive brain-computer interfaces by modeling brain activity more flexibly. Congrats to authors Dima Yanovsky, and Andrii Zahorodnii! 🦾

Using monkey brain data to operate robotic arms! 🙉 Project Jenkins explores brain-computer interfaces by decoding neural activity into robotic movement and generating synthetic brain data from motion patterns. Using neural recordings from a macaque monkey named Jenkins, researchers developed models to decode brain signals into robotic arm movements and encode movement data into simulated neural activity. The project utilizes robotic arms and an interactive web console for real-time brain data generation from joystick inputs. The research paves the way for adaptive brain-computer interfaces by modeling brain activity more flexibly. Congrats to authors Dima Yanovsky, and Andrii Zahorodnii! 🦾

Lukas Ziegler

21,613 просмотров • 1 год назад

Education is getting its biggest upgrade in decades. We’re launching Feynman-2 — our new system for learning that remembers your progress, solves with you, and gives you tools to put your learning into practice. Visual generative content, highly accurate responses powered by web search, memory-based practice, and much more. Live now on Opennote →

Education is getting its biggest upgrade in decades. We’re launching Feynman-2 — our new system for learning that remembers your progress, solves with you, and gives you tools to put your learning into practice. Visual generative content, highly accurate responses powered by web search, memory-based practice, and much more. Live now on Opennote →

Abhi

90,968 просмотров • 1 год назад

Andrej Karpathy explains why he thinks of LLMs as "people spirits." He describes them as simulations of people. The technical machinery is a transformer neural network that processes text in chunks, applying equal computing power to each piece. The system learns by reading billions of web pages and books. After training, it becomes a machine that can mimic how humans write and communicate. The key insight is that training on human content gives these models an emergent human-like psychology. This explains why LLMs often respond in surprisingly human ways. This framework opens up both their strengths and limitations. They simulate human patterns because that's their training data, but they remain statistical simulations rather than conscious beings. Understanding LLMs as "people spirits" helps set proper expectations for these tools and explains their uncannily human behavior.

Andrej Karpathy explains why he thinks of LLMs as "people spirits." He describes them as simulations of people. The technical machinery is a transformer neural network that processes text in chunks, applying equal computing power to each piece. The system learns by reading billions of web pages and books. After training, it becomes a machine that can mimic how humans write and communicate. The key insight is that training on human content gives these models an emergent human-like psychology. This explains why LLMs often respond in surprisingly human ways. This framework opens up both their strengths and limitations. They simulate human patterns because that's their training data, but they remain statistical simulations rather than conscious beings. Understanding LLMs as "people spirits" helps set proper expectations for these tools and explains their uncannily human behavior.

Aish

16,309 просмотров • 1 год назад

Commenting in Webflow just got a serious glow-up, thanks to some powerful updates built to streamline how you collaborate. Here’s what’s new: 💻 Now, you can enable custom code – like animations and forms – to run in both preview and comment modes, allowing everyone to provide feedback with full context. ⌨️ Review and refine content, right where it lives with on-canvas CMS commenting. ⚡️We’ve partnered with Zapier and Make to allow you to surface Webflow comment activity in tools like Slack, Asana, Jira, Notion, and more! 📝 We released comments APIs and a webhook to allow you to build integrations that connect Webflow comments to other tools. To learn more about these updates check out the blog here:

Commenting in Webflow just got a serious glow-up, thanks to some powerful updates built to streamline how you collaborate. Here’s what’s new: 💻 Now, you can enable custom code – like animations and forms – to run in both preview and comment modes, allowing everyone to provide feedback with full context. ⌨️ Review and refine content, right where it lives with on-canvas CMS commenting. ⚡️We’ve partnered with Zapier and Make to allow you to surface Webflow comment activity in tools like Slack, Asana, Jira, Notion, and more! 📝 We released comments APIs and a webhook to allow you to build integrations that connect Webflow comments to other tools. To learn more about these updates check out the blog here:

Webflow

11,829 просмотров • 1 год назад

Harness powerful new AI integrations, Cinema 4D native file support, and a new Render Network Cinema 4D Wizard that simplifies sending jobs from Octane and Redshift C4D workflows to unlimited high performance GPUs on the Render Network New Render Network jobs using Flux by Blackforest Labs, Dream Machine by Luma Labs, Runway ML and others are available starting today using Render Credits, with more coming soon: an AI upscaling tools by Topaz Labs,,Skybox 360, an innovative text-to-360 8K HDRI image generator, plus a python-based launcher built to frictionlessly send Generative neural jobs to thousands of concurrent GPUs on the Render Network.

Harness powerful new AI integrations, Cinema 4D native file support, and a new Render Network Cinema 4D Wizard that simplifies sending jobs from Octane and Redshift C4D workflows to unlimited high performance GPUs on the Render Network New Render Network jobs using Flux by Blackforest Labs, Dream Machine by Luma Labs, Runway ML and others are available starting today using Render Credits, with more coming soon: an AI upscaling tools by Topaz Labs,,Skybox 360, an innovative text-to-360 8K HDRI image generator, plus a python-based launcher built to frictionlessly send Generative neural jobs to thousands of concurrent GPUs on the Render Network.

Jules Urbach

51,651 просмотров • 1 год назад

Introducing the Generative UI Research Canvas ✨ Every agent needs a powerful UI Combine LangChain, Tavily, Tako and CopilotKit🪁 and you get a LangChain-based research agent with a Generative UI-driven frontend. When agents can explore the underlying data, research becomes more trustworthy and useful. How does this work? - LangChain manages the agent workflow and tool orchestration. - Tako converts retrieved data into structured, visual components - Tavily provides agentic search - CopilotKit renders those components in the UI and keeps the user in the loop while the agent is working So instead of a boring and static report, the output is an interactive research canvas that evolves as the agent runs. 2026 is the year where users want to see the output, not read it... Generative UI makes this possible for agentic applications. Tutorial: Open-Source Repo: Docs:

Introducing the Generative UI Research Canvas ✨ Every agent needs a powerful UI Combine LangChain, Tavily, Tako and CopilotKit🪁 and you get a LangChain-based research agent with a Generative UI-driven frontend. When agents can explore the underlying data, research becomes more trustworthy and useful. How does this work? - LangChain manages the agent workflow and tool orchestration. - Tako converts retrieved data into structured, visual components - Tavily provides agentic search - CopilotKit renders those components in the UI and keeps the user in the loop while the agent is working So instead of a boring and static report, the output is an interactive research canvas that evolves as the agent runs. 2026 is the year where users want to see the output, not read it... Generative UI makes this possible for agentic applications. Tutorial: Open-Source Repo: Docs:

Atai Barkai

11,997 просмотров • 5 месяцев назад

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:

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

170,404 просмотров • 1 год назад

Today, we're launching C1 by Thesys on Product Hunt and giving away up to 5M free tokens if you retweet this and sign up within 24 hours. C1 is the world’s first Generative UI API that augments LLMs to respond with interactive UI like charts, forms, cards, and more in real-time, instead of plain text. Integrates seamlessly with any LLM, framework or MCP in just 2 lines of code - Fully customisable to match your brand - Supports custom components - Renders instantly with no latency Ship rich, interactive AI apps 10× faster, with 80% less UI overhead.

Rabi Shanker Guha

71,754 просмотров • 9 месяцев назад

We partnered with artists, designers, and builders to create new AI tools that solve real problems in their creative workflows. Here’s what’s new: — Introducing Google Pics in Google Workspace: A brand-new image creation & editing tool. Move and resize objects, add text, and translate just by hovering and clicking — Big updates to صافي النيه😉: 1) You can now create with Gemini Omni Flash in Google Flow 2) Google Flow Agent is a multi-step creative partner that reasons and plans complex tasks with you. 3) Google Flow tools are custom tools you can “vibe code” for animations, video effects, text layering & more — Design live with Stitch by Google: Now, you can use text or voice prompts to edit layouts in real time then export those designs straight to code — More creative control in صافي النيه😉Music: Edit songs section by section, remix the style of full songs, and create music videos with our new Gemini Omni Flash model

Google AI

13,953,239 просмотров • 2 месяцев назад

I see a lot of negative feedback about Apple’s new UI updates. But you are missing the point. It’s not about glass effects or making every UI element transparent / shiny. It’s about liquidity, depth, and movement. UI that feels alive. We are entering a new era of interface design. What was once static, flat, and fixed is becoming dynamic, adaptive, dimensional. Flat design is over. And flat screens will be too. Sooner than you think. I think Apple’s new UI system is less about a visual update. It’s the first real step toward multimodal interfaces. Where components aren’t bound to a rigid screen but float, shift, and respond. They appear where you need them, and disappear where you don’t. It’s about removing unnecessary clutter and making human-computer interaction feel… well, more human. Just because we’ve spent the last decade staring at opaque UI components doesn’t mean it’s the optimal way to interact with computers. Sure, it’s not perfect, but it’s the first real step into a new era of UI. The future is screenless. And dynamic components are the new screens.

I see a lot of negative feedback about Apple’s new UI updates. But you are missing the point. It’s not about glass effects or making every UI element transparent / shiny. It’s about liquidity, depth, and movement. UI that feels alive. We are entering a new era of interface design. What was once static, flat, and fixed is becoming dynamic, adaptive, dimensional. Flat design is over. And flat screens will be too. Sooner than you think. I think Apple’s new UI system is less about a visual update. It’s the first real step toward multimodal interfaces. Where components aren’t bound to a rigid screen but float, shift, and respond. They appear where you need them, and disappear where you don’t. It’s about removing unnecessary clutter and making human-computer interaction feel… well, more human. Just because we’ve spent the last decade staring at opaque UI components doesn’t mean it’s the optimal way to interact with computers. Sure, it’s not perfect, but it’s the first real step into a new era of UI. The future is screenless. And dynamic components are the new screens.

Felix Haas

653,521 просмотров • 1 год назад

New course: Build agents that respond to users with not only plaintext, but custom UIs like charts, forms, and whiteboards, generated on demand and displayed right in the chat. This short course is built in partnership with CopilotKit🪁 and taught by Atai Barkai, co-founder of CopilotKit. You'll learn three approaches: Your agent can pick from custom components you build, like charts and forms. It can compose new layouts from a set of building blocks you provide, like rows, cards, and text. Or it can incorporate existing third-party apps, like a whiteboard or a calendar, right inside the conversation. Skills you’ll gain: - Build agents that render custom components like charts and forms on demand - Build an app where the agent and user collaborate on shared data, beyond just the chat window - Place third-party apps like maps, calendars, and whiteboards right in your interface Join and build agents that give users something to see and act on!

New course: Build agents that respond to users with not only plaintext, but custom UIs like charts, forms, and whiteboards, generated on demand and displayed right in the chat. This short course is built in partnership with CopilotKit🪁 and taught by Atai Barkai, co-founder of CopilotKit. You'll learn three approaches: Your agent can pick from custom components you build, like charts and forms. It can compose new layouts from a set of building blocks you provide, like rows, cards, and text. Or it can incorporate existing third-party apps, like a whiteboard or a calendar, right inside the conversation. Skills you’ll gain: - Build agents that render custom components like charts and forms on demand - Build an app where the agent and user collaborate on shared data, beyond just the chat window - Place third-party apps like maps, calendars, and whiteboards right in your interface Join and build agents that give users something to see and act on!

Andrew Ng

210,187 просмотров • 2 месяцев назад

✨ Introducing Attio Sequences When we spoke to dozens of GTM leaders this year about the future of CRM, one message came through loud and clear: sellers should be able to focus on building relationships, not managing tools. Today, we're taking another step toward making that vision a reality with Attio Sequences. Built where your data lives, Sequences powers intelligent email sequences that respond to real prospect signals - whether it's trial usage, product milestones, or any key moment in the prospect journey. Like every piece of our platform, Sequences makes the whole more powerful: Objects gave you the data model, Automations gave you the workflows, and now Sequences gives you intelligent customer engagement. No more context switching. No more manual tracking. Your team can focus on what matters: building customer relationships and driving growth. Read the full update here 👉

✨ Introducing Attio Sequences When we spoke to dozens of GTM leaders this year about the future of CRM, one message came through loud and clear: sellers should be able to focus on building relationships, not managing tools. Today, we're taking another step toward making that vision a reality with Attio Sequences. Built where your data lives, Sequences powers intelligent email sequences that respond to real prospect signals - whether it's trial usage, product milestones, or any key moment in the prospect journey. Like every piece of our platform, Sequences makes the whole more powerful: Objects gave you the data model, Automations gave you the workflows, and now Sequences gives you intelligent customer engagement. No more context switching. No more manual tracking. Your team can focus on what matters: building customer relationships and driving growth. Read the full update here 👉

Attio

148,954 просмотров • 1 год назад

Build and customize complex AI applications with a flexible framework in this new short course, Building AI Applications with Haystack. Created in collaboration with deepset, makers of Haystack, and taught by Tuana, who is the developer relations lead for Haystack at deepset. Generative AI technology is changing rapidly and it can be challenging to integrate APIs from different LLMs, vector databases, and various tools such as web search. In this course, you will learn how to use the Haystack framework to make your development process more modular, allowing you to manage complexity and focus more on building your application. In detail, you’ll: - Build a RAG pipeline using Haystack’s main building blocks – components, pipelines, and document stores. - Create custom components in your pipeline by building a Hacker News summarizer that extends your app’s ability to access APIs. - Use conditional routing to create a branching pipeline with a fallback to web search mechanism when the LLM does not have the necessary context to respond to the user's query. - Build a self-reflecting agent for named entity recognition that loops using an output validator custom component. - Create a chat agent using OpenAI's function-calling capabilities which allow you to provide Haystack pipelines as tools to the LLM, enhancing that agent's capabilities. By the end of this course, you will learn a high-level orchestration framework that can help make your applications flexible, extendible, and maintainable, even as the technology stack changes, new user needs arise, and you add new features to your application. Please sign up here:

Build and customize complex AI applications with a flexible framework in this new short course, Building AI Applications with Haystack. Created in collaboration with deepset, makers of Haystack, and taught by Tuana, who is the developer relations lead for Haystack at deepset. Generative AI technology is changing rapidly and it can be challenging to integrate APIs from different LLMs, vector databases, and various tools such as web search. In this course, you will learn how to use the Haystack framework to make your development process more modular, allowing you to manage complexity and focus more on building your application. In detail, you’ll: - Build a RAG pipeline using Haystack’s main building blocks – components, pipelines, and document stores. - Create custom components in your pipeline by building a Hacker News summarizer that extends your app’s ability to access APIs. - Use conditional routing to create a branching pipeline with a fallback to web search mechanism when the LLM does not have the necessary context to respond to the user's query. - Build a self-reflecting agent for named entity recognition that loops using an output validator custom component. - Create a chat agent using OpenAI's function-calling capabilities which allow you to provide Haystack pipelines as tools to the LLM, enhancing that agent's capabilities. By the end of this course, you will learn a high-level orchestration framework that can help make your applications flexible, extendible, and maintainable, even as the technology stack changes, new user needs arise, and you add new features to your application. Please sign up here:

Andrew Ng

53,788 просмотров • 1 год назад

VIDEO | WazirX is betting on crypto futures trading, AI-driven products and enhanced customer experience to drive growth, as the crypto exchange seeks to win back market share and accelerate its comeback following last year's court-approved restructuring, which was triggered by a USD 235 million cyber heist. Founder Nischal Shetty said that WazirX is gearing to launch "WazirX AI", an artificial intelligence-powered assistant that will allow users to interact with the trading platform through natural language commands rather than navigating complex trading interfaces. "I think that's the future, where instead of trying to learn how a trading interface operates, where the stop losses are, how do you fill up a form...I think the more natural way of trading for people will be where you just instruct your AI to do things for you, and it does it," he said.

VIDEO | WazirX is betting on crypto futures trading, AI-driven products and enhanced customer experience to drive growth, as the crypto exchange seeks to win back market share and accelerate its comeback following last year's court-approved restructuring, which was triggered by a USD 235 million cyber heist. Founder Nischal Shetty said that WazirX is gearing to launch "WazirX AI", an artificial intelligence-powered assistant that will allow users to interact with the trading platform through natural language commands rather than navigating complex trading interfaces. "I think that's the future, where instead of trying to learn how a trading interface operates, where the stop losses are, how do you fill up a form...I think the more natural way of trading for people will be where you just instruct your AI to do things for you, and it does it," he said.

Press Trust of India

26,643 просмотров • 1 месяц назад

Ladies and gentlemen introducing our upcoming special mint by our Salvor OG community member 🔺krlja🔻 first ever generative collection BOMB OFF with all mint fees proceeds to BUYING BACK SALVOR $ART tokens that were lost during his compromise. Inspired by the idea around creating entertaining characters with pun-names using the word BOMB, has created a 400 pieces collection with memorable characters including Spongebomb, James Bomb, Bomb Marley, Bombnald Duck and much more for you to find out!! Here are the mint details: 📐 Size: 400 pieces ⏰ Date: January 13th 2026 🪄 Mint price: WL1.5 AVAX/Public 2.5 AVAX 🗺️ Location: Our SPECIAL MINT will feature EXTRA BOOST MULTIPLIER and supported by SALVOR LENDING to best incentivize our launchpad supporters

Ladies and gentlemen introducing our upcoming special mint by our Salvor OG community member 🔺krlja🔻 first ever generative collection BOMB OFF with all mint fees proceeds to BUYING BACK SALVOR $ART tokens that were lost during his compromise. Inspired by the idea around creating entertaining characters with pun-names using the word BOMB, has created a 400 pieces collection with memorable characters including Spongebomb, James Bomb, Bomb Marley, Bombnald Duck and much more for you to find out!! Here are the mint details: 📐 Size: 400 pieces ⏰ Date: January 13th 2026 🪄 Mint price: WL1.5 AVAX/Public 2.5 AVAX 🗺️ Location: Our SPECIAL MINT will feature EXTRA BOOST MULTIPLIER and supported by SALVOR LENDING to best incentivize our launchpad supporters

Salvor 🚢🔺

12,982 просмотров • 6 месяцев назад

AI instead of UI The last few years radically changed how we think about digital products & product design process in general. What we are witnessing right now is a transition where AI is no longer just a feature; it is becoming the infrastructure of interaction. For decades, UI design was rooted in the concept of “Happy Path,” a series of static, linear screens (routes from A to B) designed to funnel users toward a goal. This “one-size-fits-all” approach assumes that all users have the same mental model, which is far from the truth. The rise of AI tools like ChatGPT and Gemini is showing that we are moving into an era of Generative Interfaces. Instead of a designer pre-determining every button and menu, the interface is synthesized in real-time based on user actions. Back in 2019, Gleb Kuznetsov and I were working on the concept of morphing Interface, the idea of a UI that adapts its structure based on user intent. The great thing about this UI is that it was highly dynamic: different users saw different content/contextual actions based on their behavior. This concept was crazy in 2019, but it is highly relevant to the modern state of the product design process. And I strongly believe that it represents the future of UI design. We will move beyond the “AI chatbox" crutch Yes, many products today treat AI as a sidecar (think of Copilots or chatbots pinned to the side of a traditional dashboard), but this is a transitional phase. Why? Because adding a chat window to a 20-year-old software layout is like putting a jet engine on a horse-drawn carriage. That's why the future isn't "AI as an add-on"; it is AI as the Operating System. AI will power generative interfaces that are rooted in anticipatory design: UI won’t wait for a command; it will surface tools based on the user's current environmental context and historical behavior. This evolution changes the very nature of product design, and we will move away from designing pages/screens and toward designing systems of logic.

AI instead of UI The last few years radically changed how we think about digital products & product design process in general. What we are witnessing right now is a transition where AI is no longer just a feature; it is becoming the infrastructure of interaction. For decades, UI design was rooted in the concept of “Happy Path,” a series of static, linear screens (routes from A to B) designed to funnel users toward a goal. This “one-size-fits-all” approach assumes that all users have the same mental model, which is far from the truth. The rise of AI tools like ChatGPT and Gemini is showing that we are moving into an era of Generative Interfaces. Instead of a designer pre-determining every button and menu, the interface is synthesized in real-time based on user actions. Back in 2019, Gleb Kuznetsov and I were working on the concept of morphing Interface, the idea of a UI that adapts its structure based on user intent. The great thing about this UI is that it was highly dynamic: different users saw different content/contextual actions based on their behavior. This concept was crazy in 2019, but it is highly relevant to the modern state of the product design process. And I strongly believe that it represents the future of UI design. We will move beyond the “AI chatbox" crutch Yes, many products today treat AI as a sidecar (think of Copilots or chatbots pinned to the side of a traditional dashboard), but this is a transitional phase. Why? Because adding a chat window to a 20-year-old software layout is like putting a jet engine on a horse-drawn carriage. That's why the future isn't "AI as an add-on"; it is AI as the Operating System. AI will power generative interfaces that are rooted in anticipatory design: UI won’t wait for a command; it will surface tools based on the user's current environmental context and historical behavior. This evolution changes the very nature of product design, and we will move away from designing pages/screens and toward designing systems of logic.

Nick Babich

53,320 просмотров • 5 месяцев назад

LimX Dynamics just released LimX Luna, officially described by the company as the first mass-deliverable full-size female humanoid robot. 🤖 This is not aimed at warehouses; it is built for malls, theme parks, auto shows, brand events, and other commercial spaces where attention is the product. Luna stands 160 cm tall, has 27 body DoF excluding end effectors, and combines whole-body motion control with voice, vision, facial expressions, gesture interaction, and motion imitation. The sharper part is the content stack: users can upload dance videos, build scenes with zero-code tools in LimX Studio, and run synchronized shows with up to 200 robots. That makes Luna less like a one-off demo machine and more like a programmable entertainment platform for foot traffic, performances, and social clips. For humanoids, this is a useful shift: not only “can it do labor,” but “can it create a consumer experience people actually stop to watch.”

RoboHub🤖

13,909 просмотров • 1 месяц назад

Today we’re introducing Superhuman Docs, the evolution of Coda (Superhuman Docs) into the best place for teams and AI to work together. I co-founded Coda to reimagine the modern document and enable anyone to make a doc as powerful as an app. Superhuman Docs builds on that mission, and is reimagined for how teams work with AI now. With Superhuman Docs, AI is no longer a solo experience. Docs AI works with you the way a teammate would, with full context of everything your team has built: your data, your briefs, your roadmaps, your connected tools. You can ask it to summarize a sprint, draft a decision record from your meeting notes, or pull a competitor analysis into a new page, and that work stays right where your teammates can pick it up. I’m incredibly proud of the team for bringing Docs to life! There’s so much more we’re launching, including a way to create custom interfaces on top of your data just by describing it. We’re also introducing Superhuman Databases for teams to manage up to 1 million rows, launching Docs MCP to open it up to the AI tools you already use, and debuting a brand new Mac app. We’ve been building toward this moment for a long time, and Docs starts rolling out today. If you’re an existing Coda user, everything you rely on in your docs will remain the same, and if you’re new, now is a great time to jump in.

Shishir

22,007 просмотров • 15 дней назад