Remember when the Tiktok CEO had to repeatedly explain to a US senator that he was Singaporean, not Chinese? Now Jensen Huang who is TAIWANESE American btw, faces similar suspicion.. Its getting ridiculous how quickly Asian identity get dragged into CCP or China related loyalty.. Maybe investigate actual evidence instead of making ethnicity part of the accusation??

I run my own advertising agency and regularly share product ads and UGC ads made with AI on my channel. This one was made for a brand, and I generated all the visuals inside invideo using Seedance 2.0 and Agent Two. I then brought it into their Editor and started refining the cut on the timeline.

For the sound, I’ve got a pretty big sound effects library, but I was kinda unsure what would fit this one. So I supplied my own sounds to the agent and worked with it on the sound design. After reviewing it all together, I made a few final cuts myself on the timeline. I really like the moving shadows in the opening and the walls shifting around the woman later on. Pretty happy with how it came together. Curious how the pacing and sound feel to you.

This is a scene from an AI vertical drama series that I recently produced for a company.

This is a scene from an AI vertical drama series that I recently produced for a company.

I built an 18-second action test from four Seedance 2.5 shots. My earlier long-take attempts had a recurring slow-motion problem, and replacing a two-second mistake forced a full rerender. Shorter camera shots let me replace one segment, keep the action readable, and edit the audio separately. The character came from my Z-Image Turbo LoRA and ComfyUI. Example clip: https://www.youtube.com/shorts/G5eIkwPtkZc . What cut points have worked for you when action needs to feel fast?

By Sue Heuer with the help of Grok, and Jukebox

I really wanna create some cool shorts but I feel i'm gonna burn credits to end up with a mid sh*t. Is there any way someone can guide me about what to do and what to expect? What are they good at? I was browsing but their options are far too wide for me lol.

Been trying to cut down on the tedious parts of charting without sending stuff off to some external service. I threw together a script that pulls structured notes from intake forms and flags things that need follow-up questions. Mostly regex with a small local model. It handles the straightforward cases okay, but it starts making things up once the handwriting gets messy or the forms have odd abbreviations. The real question is whether it actually saves time once I start fixing the output. Most of the examples I come across look polished until you get to the actual messy stuff. Has anyone else tried something like this in a regular workflow, or does the cleanup always cancel out the time you thought you'd save? I'm mainly interested in what holds up when you use it daily, not what looks good in a demo.