#videogeneration

What Changed Wan-AI has released Wan-Dancer-14B, a novel image-to-video generation model...

The Toolchain That Makes It Possible The core workflow is model-chaining: you use one AI...

What Changed Robbyant has introduced LingBot-Video, an open-source large-scale...

What Changed Traditional large models often rely on Chain-of-Thought (CoT) reasoning, a...

What Changed Few-step autoregressive (AR) video diffusion models offer low-latency...

Seedance 2.0 costs $0.04–$0.07/s vs Wan $0.10/s: 30–60% cheaper, adds 4K + 3 tiers. Per-clip math, real specs, and A/B both on one ofox call.

A pair of papers argues the field of interactive video AI is forking: one track pushes world models toward game-engine-like simulators with explicit state, the other reframes video as a persistent world plus a stream of events for real-time interacti

Originally published at norvik.tech Introduction Explore the implications of PixVerse's...

GenCeption repurposes a pre-trained video generative diffusion model as a feed-forward perception system, matching specialist vision models on depth, surface normals, pose and segmentation while using 7x to 500x less training data - and generalizing

The Problem Nobody Talks About Everyone's posting AI-generated videos — characters...

A new paper introduces Vidu S1, a video model that generates interactive 540p video at up to 42 frames per second on consumer GPUs and lets users reshape the scene on the fly with voice commands, without the drift that usually breaks long AI video.

A new benchmark tests whether video AI systems can track what happens to parts of a scene the camera isn't currently showing. Across 23 models, the answer is mostly no — and making the models larger made the problem worse, not better.