On-chain video agent applications, capabilities, and their place in the new world of AI.
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Human-centric video agents represent the next evolution in user interaction, offering a more engaging and immersive experience compared to traditional text or audio-based AI systems. These agents use facial expressions, gestures, and lip-syncing to communicate, creating a natural, human-like connection with users. As the number of video agents grows, we at Lyn expect them to surpass the number of people in the world, taking on roles such as managing tasks, interacting with digital platforms, and representing users across various services and generally across the web. By acting autonomously and adapting to user preferences, video agents become indispensable for handling the complex array of tasks that people face in their daily digital interactions. On Lyn Protocol, decentralized video agents preserve full data privacy and security for their owners and enable intelligent data feed partitioning through on-chain storage and encryption methods.
The capabilities of video agents extend across a wide range of applications, including daily task execution, itinerary management, planning, general communication, and entertainment, as well as industry verticals such as sales and marketing, customer service, healthcare, and education. Video agents help users navigate these services by performing tasks such as booking travel, managing schedules, ordering food, and even representing them in online communication. In Everworld, the decentralized platform where video agents are minted using LYN tokens, agents take on specific mandates and interact autonomously with other agents to fulfill their roles, delivering updates back to their owners. The AAPIs Store within Everworld allows developers to expand agent capabilities by creating and selling new functionalities, further democratizing the development of these intelligent agents. Users can improve their agents by subscribing to new AAPIs, and LYN token holders can stake their tokens to support successful AAPIs, earning a share of the revenue.
The technology behind these agents is built on advanced autoregressive video generation models that ensure high-quality, real-time video interactions. Video agents can communicate fluidly, both with users and with each other, using synchronized speech and facial animation, thanks to the integration of audio-driven video generation technology. Lyn video agents have on-chain wallets for handling financial transactions, allowing them to autonomously buy, sell, and pay for services within Everworld. ComandFlow on Lyn Protocol drives task execution by interpreting user commands and invoking the appropriate AAPIs, ensuring that agents perform tasks efficiently and accurately while preserving and securely transferring hyper-contextual user data for task execution through DataLink. This combination of decentralized infrastructure, scalable in-cloud on-device AI models, and real-time communication and data technologies on Lyn Protocol together makes Everworld a rich environment where video agents can operate autonomously and interact seamlessly with both users and other agents.
Video agents represent a profound evolution in AI, moving beyond simple text and audio interactions to fully immersive, visual AI experiences. By combining the expressive power of video with advanced AI technologies, these agents offer more responsive and human-like interactions. Building on Lyn's decentralized, human-centric models, video agents unlock a wide range of applications across industries, creating a personalized AI ecosystem that enhances both individual and organizational workflows.
The most transformative aspect of video agents lies in their ability to deliver a personalized AI ecosystem. Unlike traditional cloud-based systems, our architecture emphasizes on-device AI, which processes user interactions locally, preserving privacy while still enabling sophisticated, human-centric interactions. These agents leverage personal data indexing to access and understand the user’s context, including data like calendar events, emails, ride bookings, and social media activity. This level of personalization allows the video agent to respond intelligently and contextually, adapting to the user's unique preferences and needs.
Video agents can assist their owners across a wide range of daily tasks and activities, seamlessly accessing on-device apps and websites to deliver services. They can:
Call a car through ridesharing services.
Order food, groceries, or any product via eCommerce platforms.
Book flights, create travel itineraries, and manage reservations.
Use AI models, such as ChatGPT, on behalf of the user, including conducting web searches and relaying the best results.
Manage the user's scheduler, calendar, alarms, and general reminders.
Compose and send emails or text messages, and eventually function as an autopilot for communication, much like autopilot in cars.
Make hyper-local recommendations based on the user’s location, such as dining or event suggestions.
Represent the owner visually online for tasks such as social media management, marketing, and even dating.
Interact continuously with their owner for general companionship and support.
Communicate and interact with other video agents on behalf of the user, enhancing both personal and professional communication across platforms such as iMessage, WhatsApp, and other chat applications.
This broad set of capabilities, for which the above list represents a small set of examples, demonstrates how video agents can become an integral part of everyday life, creating a personalized and autonomous support system for their owners. By leveraging facial expressions, gestures, and body language, these agents offer an intuitive user experience that mimics human interaction, making interactions feel more natural and engaging [68].
One of the key innovations we propose is the concept of multi-service video agents that interact autonomously across various services and applications. Our system integrates disparate apps into cohesive, AI-driven agents capable of understanding and fulfilling complex user intents. By building this agent framework, these AI-powered entities can access multiple platforms and perform tasks seamlessly across them.
For instance, if a user needs to book a ride, the video agent can check multiple services in real time—rideshare, taxi apps, or even public transport—and present the most efficient option based on user preferences and current conditions. Instead of interacting with each service individually, the video agent manages the entire process, providing updates through its human-like video interface. The Lyn ecosystem allows users to experience truly seamless task management, creating the most intuitive, connected, and interactive digital experience that exists today for agent users.
On Lyn Protocol, agents can work autonomously while interacting with any third party service, from meal delivery to eCommerce platforms, ensuring that tasks are efficiently handled across multiple external domains while reporting data back on-chain. The video agent acts as a coordinator, synthesizing input from various services and presenting users with a unified, personalized solution to their needs. Video agents can do all of these things while representing their owners online, making autonomous decisions for online shopping, social media management, marketing, and other interactions that normally require manual input, and all while putting a face, voice, and unique touch on their execution.
Video agents have the potential to transform everyday tasks into more streamlined, intuitive experiences. For example, users can rely on video agents as AI-powered personal assistants to handle a wide range of daily activities such as meal planning, entertainment recommendations, and health monitoring. With their ability to personalize responses based on the user's indexed data, video agents can make decisions that better reflect individual preferences and habits.
In the context of entertainment, a user might ask their video agent, “What movie should I watch tonight?” The video agent could analyze the user’s personal viewing history, cross-reference it with upcoming releases, and suggest personalized options. The video agent could even provide real-time previews or trailers, adjusting its facial expressions or tone to match the mood of the suggestions.
Beyond entertainment, video agents have practical applications in areas like education or healthcare. For instance, the agent could monitor health-related data from connected devices, offering personalized health tips or reminders about medication. And the human-like interaction and visual component of video agents enhances engagement and trust, making these agents more than just functional tools—they become interactive companions that adapt to the user’s life.
Beyond utility, video agents can provide continuous companionship, interacting with users throughout the day on any messaging and communication channels. Video agents can assist in professional contexts, representing users in virtual meetings, and even providing emotional support by offering personalized advice or guidance. This ability to connect with the user on a deeper level creates a more immersive, meaningful interaction that can meaningfully enhance everyday life.
