# Lyn

## Lyn

- [Introducing Lyn](https://lynlabs.gitbook.io/lyn/lyn-docs/introducing-lyn.md): The video-based super-agential multimodal ecosystem.
- [Our Vision for Video AI and Human-Centric Agential Video](https://lynlabs.gitbook.io/lyn/lyn-docs/our-vision-for-video-ai-and-human-centric-agential-video.md): Photorealistic, human-centric synchronous video agents that can change human lives for the better.
- [Decentralized Video AI Layer](https://lynlabs.gitbook.io/lyn/lyn-docs/decentralized-video-ai-layer.md)
- [Video Agent Generation: Diffusion Based Model](https://lynlabs.gitbook.io/lyn/lyn-docs/video-agent-generation-diffusion-based-model.md): A novel approach for powerful, controllable human-like video generation.
- [Text-to-Speech Synthesis Using Diffusion Bridge Model](https://lynlabs.gitbook.io/lyn/lyn-docs/video-agent-generation-diffusion-based-model/text-to-speech-synthesis-using-diffusion-bridge-model.md): A model that outperforms autoregressive and diffusion models for high quality output that is structured, noiseless, and quick on inference.
- [Real-time Conversational Generation: A Framework for Voice-driven Facial Animation](https://lynlabs.gitbook.io/lyn/lyn-docs/video-agent-generation-diffusion-based-model/real-time-conversational-generation-a-framework-for-voice-driven-facial-animation.md): A state-of-the-art approach that bridges the gap between high-quality video generation and the latency challenges of real-time interaction.
- [Decentralized Video Agent Applications and Capabilities](https://lynlabs.gitbook.io/lyn/lyn-docs/decentralized-video-agent-applications-and-capabilities.md): On-chain video agent applications, capabilities, and their place in the new world of AI.
- [Autoregressive Modeling with Vector Quantization](https://lynlabs.gitbook.io/lyn/ai-modeling-research/autoregressive-modeling-with-vector-quantization.md): Features and approaches of the first-of-its-kind foundational video AI model powering video agents in the Lyn ecosystem.
- [Hierarchical Spatial-Temporal Video Generation Architecture](https://lynlabs.gitbook.io/lyn/ai-modeling-research/autoregressive-modeling-with-vector-quantization/hierarchical-spatial-temporal-video-generation-architecture.md): Encoding video into multi-scale latent video tokens and decoding video tokens back into the pixel 21 domain.
- [Efficient Autoregressive Video Generation via Token Masking](https://lynlabs.gitbook.io/lyn/ai-modeling-research/autoregressive-modeling-with-vector-quantization/efficient-autoregressive-video-generation-via-token-masking.md): Efficient modeling of complex spatial-temporal dynamics in video data.
- [Autoregressive Text-to-Visual Generation via Hybrid Architecture](https://lynlabs.gitbook.io/lyn/ai-modeling-research/autoregressive-modeling-with-vector-quantization/autoregressive-text-to-visual-generation-via-hybrid-architecture.md): A unique hybrid architecture of Mamba and Transformer for visual generation.
- [From Video to Movie: Composite Video Editing and RHF for Quality](https://lynlabs.gitbook.io/lyn/ai-modeling-research/from-video-to-movie-composite-video-editing-and-rhf-for-quality.md): A new framework extending from autoregressive video generation for industry-leading video edit precision, and RHF-based generation quality.
- [VideoGen-of-Thought](https://lynlabs.gitbook.io/lyn/ai-modeling-research/from-video-to-movie-composite-video-editing-and-rhf-for-quality/videogen-of-thought.md): A novel approach to the generation of long, consistently structured and homogenous content.
- [Supercharging MLLMs and LVLMs](https://lynlabs.gitbook.io/lyn/ai-modeling-research/supercharging-mllms-and-lvlms.md): Multi-modal Robustness benchmark (MMR) and Text-relevant Visual Token Selection (TVTS) developed for a better, open video AI.
- [Everlyn's Data Pre-processing Pipeline](https://lynlabs.gitbook.io/lyn/technical-designs/everlyns-data-pre-processing-pipeline.md): A proprietary data pre-processing pipeline developed in-house for best-in-class speed and performance.
- [Towards Intelligent Video Captioning and Annotation](https://lynlabs.gitbook.io/lyn/technical-designs/everlyns-data-pre-processing-pipeline/towards-intelligent-video-captioning-and-annotation.md)
- [$LYN Overview](https://lynlabs.gitbook.io/lyn/technical-designs/usdlyn-overview.md): LYN token is at the foundation of the Lyn ecosystem, supporting activity and transactions for all video agents on the platform.
- [Supplementary Information](https://lynlabs.gitbook.io/lyn/technical-designs/supplementary-information.md): Additional info referenced throughout the Lyn Gitbook.
- [Definitions](https://lynlabs.gitbook.io/lyn/technical-designs/supplementary-information/definitions.md): Definitions of the techniques and technical terminology in the research sections of the Lyn Gitbook.
- [References](https://lynlabs.gitbook.io/lyn/technical-designs/supplementary-information/references.md): Cited works referenced throughout the Lyn Gitbook.