Video Generation

Today's Stories

1. 1

   Processing platform for egocentric video launches, seeks lab partners

   A startup has built a platform that automates the data preparation (ETL) pipeline for egocentric and spatial video, converting raw footage into model-ready outputs for robotics and vision-language-action (VLA) model development. The team is openly recruiting research labs and companies to test the service for free. Teams building physical AI and teleoperation systems currently spend significant GPU time and engineering effort on video data preprocessing—a bottleneck the platform is designed to eliminate. By handling the data plumbing upstream, it frees computational resources and engineering cycles for core model work.

   The offer is limited to labs willing to provide feedback; interested teams are invited to comment or message directly to discuss participation. No pricing, availability date, or formal launch timeline is stated.

2. 2

   Midjourney acquires astrology app Co-Star

   Midjourney, an AI lab known for image and video generators, has acquired the social astrology app Co-Star. Deal terms were not disclosed. Co-Star's team of about two dozen employees has joined Midjourney. Co-Star has about 4.3 million monthly active users and uses AI and human writing to generate horoscopes and astrological compatibility assessments. The acquisition signals Midjourney's expansion beyond its core image-generation business into consumer-facing apps, following its efforts to build medical and spa divisions.

   Midjourney currently operates primarily through Discord with no standalone app. Co-Star's team's experience building consumer apps suggests Midjourney may finally develop its own standalone application.

3. 3

   Black Forest Labs launches FLUX 3 multimodal model spanning video, audio, robotics

   Black Forest Labs announced FLUX 3, a unified multimodal model trained in a single architecture that handles image, video, audio generation, and action prediction. The company also unveiled FLUX-mimic, a video-action robotics model built on FLUX 3 and tested with Audi for real factory deployment on a single on-premises GPU. FLUX 3 reproduces and extends capabilities previously demonstrated separately by other frontier labs (Gemini Omni, Grok Imagine, Seedance 2.0), with the team committing to open an open-weights developer version. The robotics application signals that video world modeling can directly transfer to robot control, potentially lowering barriers for labs building competitive open models without reliance on closed ecosystems.

   FLUX 3 Video is currently in early access. The model's ability to unify image, video, audio, and robotics control in one architecture—trained jointly rather than as separate modules—will shape whether multimodal systems become industry standard or remain fragmented by task.

4. 4

   AI Videos Shake Trust in Real Videos Even When Labeled, Study Finds

   Researchers conducted a two-phase study with 100 participants comparing those exposed to AI-generated videos against a control group watching human-generated videos. The AI-exposure group then viewed human-generated content alongside the control group, and reported increased doubt about the authenticity of subsequent videos, reduced confidence in their judgment, greater perceptual disruption, and lower social connectedness—despite clear disclosure that the synthetic content was AI-generated. The findings reveal that simply labeling AI-generated videos does not prevent them from undermining viewers' trust in real videos. This suggests that the psychological and perceptual effects of seeing realistic synthetic content carry over to genuine footage, even when viewers know the source. For platforms and content creators, this indicates the need for strategies beyond detection and disclosure to protect how people experience and trust visual media.

   The research highlights that design and policy approaches must address the experiential and psychological impacts of AI-generated video exposure, not just focus on distinguishing fake from real. The study was presented at the 2026 CHI Conference on Human Factors in Computing Systems.

5. 5

   Black Forest Labs releases Flux 3 with native audio video generation

   German AI company Black Forest Labs released Flux 3, a multimodal foundation model that learns from images, video, and audio together. The model can generate videos with native audio up to 20 seconds long for the first time, supporting text-to-video, image-to-video, video-to-video, keyframe-based transitions, multilingual dialogue, and agent-driven links between clips. In early evaluations using 10-second clips at 720p, Flux 3 was preferred over multiple rivals: 93 percent over Luma Ray 3.2, 77 percent over Runway Gen-4.5, and 69 percent over Grok Imagine Video. Against stronger competitors, it matched or came close to Seedance 2.0 and Gemini Omni Flash (each at 52 percent preference), which already serve major production workflows. BFL also developed Flux-mimic, a video-action model being tested on production tasks at Audi, suggesting the architecture extends to robotics applications.

   Flux 3 Image is set to launch in early access within the next few weeks, with improvements to complex prompts and multilingual text rendering. Action prediction will initially be offered through select partners. BFL plans open-weight access to the multimodal backbone under the name 'Flux 3 Dev,' with longer-term work on a single model combining perception, action, and language prediction.

6. 6

   Creator makes feature-length film using LLM, calls it a failure

   A content creator used an LLM (Claude Fable 5) to produce a feature-length movie adaptation of William Hope Hodgson's The House on the Borderland, which they uploaded to their YouTube channel alongside music videos and AI-generated albums. The experiment tests whether large language models can sustain creative output across a full-length project without human intervention—a question that bears on what kinds of creative work remain beyond current AI capabilities, even when given time and permission to operate independently.

   The creator frames the result as a failure despite releasing it, noting they judged it only by YouTube channel standards rather than film as a whole category; they attribute the shortcoming not to the LLM's agency or planning, but to other factors they discuss in the full piece.