JoyAI-Video-Edit: Real-Time Open-Ended Video Editing with Autoregressive Diffusion

Real-time video editing requires low-latency causal generation with bounded computational resources while preserving source fidelity and long-term temporal consistency. We present JoyAI-Video-Edit, a 16B-parameter autoregressive diffusion framework for real-time, open-ended video editing without access to future frames or a predefined video duration. Our method combines chunk-wise autoregressive adaptation, Source-Anchored Distribution Matching Distillation (SA-DMD), and Long-Horizon Autoregressive Distillation to reduce train--inference mismatch, preserve source fidelity during two-step generation, and mitigate accumulated temporal drift. Extensive automatic and human evaluations show that JoyAI-Video-Edit substantially outperforms existing streaming editors and remains competitive with strong offline systems on both short and long videos. The complete system achieves end-to-end 720p video editing at approximately 30 FPS on a single Nvidia B200 GPU. Code is available at https://github.com/jd-opensource/JoyAI-Video-Edit.

Toward Automated Formation of Composite Micro-Structures Using Holographic Optical Tweezers

Holographic Optical Tweezers (HOT) are powerful tools that can manipulate micro and nano-scale objects with high accuracy and precision. They are most commonly used for biological applications, such as cellular studies, and more recently, micro-structure assemblies. Automation has been of significant interest in the HOT field, since human-run experiments are time-consuming and require skilled operator(s). Automated HOTs, however, commonly use point traps, which focus high intensity laser light at specific spots in fluid media to attract and move micro-objects. In this paper, we develop a novel automated system of tweezing multiple micro-objects more efficiently using multiplexed optical traps. Multiplexed traps enable the simultaneous trapping of multiple beads in various alternate multiplexing formations, such as annular rings and line patterns. Our automated system is realized by augmenting the capabilities of a commercially available HOT with real-time bead detection and tracking, and wavefront-based path planning. We demonstrate the usefulness of the system by assembling two different composite micro-structures, comprising 5 $\mu m$ polystyrene beads, using both annular and line shaped traps in obstacle-rich environments.