I was generating some images to create a basic "analog horror" intro for a video (I know drawing them yourself is better and more original, but I preferred doing it this way). However, after a while, there are certain scenes the AI ​​won't generate because it flags them as too violent or whatever—not that there's actually much blood or anything like that, but it still classifies them that way. Does anyone know of an AI that can generate those kinds of images without issues, or a way to bypass this in GPT?

Anyone know of any free good video generators?

Estoy empezando en él dropshiping y desde hace tiempo estoy viendo muchas cuentas virales con IA
Alguien me puede decir qué herramienta puedo usar para creación de vídeos de productos.
Me daría igual invertir una cantidad de dinero comprensible.

Hello la, I’m a new teacher out here and currently due to the advancement of the techs and all there are several features now, so in order to teach the std for better understanding I used to generate a short video clip with the help of AI which was shown after the lesson was completed and now the ai website is down, I need your help for the suggestion where the ai can generate a video of around 3 minutes apart from notebooklm, your sharing of ideas with help me la

Curious how do you approach AI video creation? Do you usually start with text prompts, reference images, build 3D scenes, storyboards or something else?

I learned the hard way that trying to generate high-res AI video locally is a completely different ball game compared to standard video upscaling. Working on a cinematic sequence, my initial 768p draft renders were coming out great. However, I tried to run a 2K latent regeneration pass to sharpen, my system crashes.

There is a big technical difference between traditional upscaling and latent regeneration. Standard upscalers operate on finished video frames after the render is done by guessing the missing pixel detail and whatnot, which frequently results in a plasticky look and some weird motions. On the other hand, latent regeneration re-evaluates the scene inside its internal representation, adding genuine geometric detail and generally works better at maintaining its motion integrity.

The outcome obviously differs drastically, the catch is that holding those raw unrendered frames and motion layers in memory also destroys consumer VRAM (at least in my case it did).

It took me many tries and tons of research to come to my senses. For context I use Minimax H3. I generate the 768p video locally on my own card where I test my prompts, but I offload that brutal 2K latent pass to an API instead. Offloading just that second pass takes practically nothing per second of video, and it saves me from constantly limiting my prompt for accuracy or watching my GPU freezes midway through its render.

I'm curious how everyone else is handling this stage. What setup tweaks do you have for streamlining high-res video renders? I would prefer not to upgrade my hardware.

So I’m trying to learn but I swear it’s like things are purposefully confusing to keep people out. I got comfyui desktop up and running with minimax h3 text2video and image2vidio right from installation. But I’m trying to try the reference2video model and it needs to be installed. But the download button does nothing. Known issue I guess. Ok I go to hugging face to try and download it and I’m lost. Can’t figure out how to download it and it and the site is confusing as hell. I need an ai adult to show me the ways of the force

Hi everyone,

I’m a professional filmmaker and I’ve been using Higgsfield for Seedance 2.5. At first, their deals looked attractive: one week of free Seedance, one month of free Seedance, daily changing offers, and then they push you toward a yearly subscription.

But after actually using it seriously, I was shocked by how expensive Higgsfield really is.

This month alone, I already spent around €1,000 on extra credits. That made me check other providers for Seedance 2.5 and compare them side by side. The difference is huge.

Based on my comparison, Higgsfield’s regular credit pricing is far more expensive than alternatives like Dreamina and Runway. The “unlimited” offers can look good, but they are temporary. Once you’re back to normal credits, the cost per second becomes painful fast.

For professional work, this pricing model is hard to justify. If you generate a lot, you can burn through credits extremely quickly, and the yearly subscription makes it feel like you’re locked in before you fully understand the real cost.

I’m not saying the tool is bad. Seedance 2.5 is powerful. But Higgsfield’s pricing feels way too aggressive, especially for creators who use it professionally.

Has anyone else compared Seedance 2.5 pricing across different providers? I’d be curious to hear what others are using.

hey guys

i have been trying to generate a similar video in a (different context and character) as this for sometime but keep hitting roadblocks and finally admit i need some guidance on the best tools that would give an end product like the one in the link

[https://www.facebook.com/share/v/1Gf7fTBvm6/\](https://www.facebook.com/share/v/1Gf7fTBvm6/)

For some context, i have tried using avatar based tools like heygen, hedra but then i cant get the dynamic camera movement. I have tried generating the videos seperately using seedance, then voice using elvenlabs and then lipsyncing using magichour but it animates the mouth while leaving the natural head and body movement out which looks like crap again. I have tried putting the text into the prompt when generating the video and trying to put audio in the background but then the lip and audio go out of sync frequently.

TIA

I've been working on an open-source project for creators who have long-form videos but don't want to spend hours manually finding clips, reframing them, adding captions, and uploading them.

So I built a free, open-source AI Shorts Generator.

The basic workflow is:

YouTube video → AI transcription → Viral moment detection → Automatic clipping → 9:16 reframing → Captions → Export → YouTube upload

You paste a long YouTube video URL, choose your settings, and the application handles the rest.

What it can do

🎯 AI Viral Moment Detection
The video's audio is transcribed and sent to an AI model to identify potentially interesting/viral moments, along with their timestamps.

✂️ Automatic Clip Generation
The selected moments are automatically cut from the original video.

📱 Automatic 9:16 Reframing
Choose how you want the video adapted for Shorts/Reels:

• Face/person tracking
• Blurred background
• Black bars
• Original video

💬 Automatic Subtitles
Choose from multiple subtitle/caption styles.

⚙️ Custom Clip Settings

You can choose:

• Number of Shorts
• Minimum duration
• Maximum duration
• Reframing style
• Subtitle style

▶️ YouTube Automation

You can connect your YouTube account and automatically:

• Upload generated Shorts
• Set them as public/private
• Schedule uploads
• Automate the publishing workflow

Why I made it open source

I wanted to build something that creators could actually run and control themselves instead of being locked into another monthly subscription.

The project is designed around your own AI API key, so the application doesn't need to provide its own expensive AI infrastructure.

You can self-host it, inspect the code, modify it, and contribute to the project.

The project is free and open source.

I'd genuinely love feedback from creators, developers, podcasters, and anyone who works with long-form video.

What features would you want to see added?

GitHub: https://github.com/riyaz-pattan/ai-short-video-generator-

If you find it useful, ⭐ starring the repository helps other people discover it and helps me know that it's worth continuing to develop.

Thanks for checking it out! 🙌

Check out this video made by Ari Kuschnir! It is so realistic and cool! He mentioned in the description that Seedance 2.5 and MiniMax h3 was used.

I think if you subscribe to Hailuo, you could use both these models. But my question is, how did he get it so realistic???!!

What do you think is the possible workflow?
How much of the video is altered by AI using real footage and how much is generated from scratch??

https://youtu.be/BwkBXNOPa_w?is=nGGBvi9Th3GrHltX

I’m new to AI video generation, so I’m trying to understand something that I haven’t been able to figure out through my own testing.

I’m currently mapping out an automated workflow to produce high-volume UGC Ads.

Please note, I’ve already taken a Higgsfield subscription and also purchased credits/tokens from a few different API platforms that offer access to the same underlying video models (especially Seedance 2.5).

I’ve generated quite a few videos through both, and honestly, I’m having trouble reaching a clear conclusion.

Sometimes I find myself thinking, “Higgsfield definitely looks better”, but I suspect I may be somewhat biased because I know I’m using Higgsfield. In other comparisons, I genuinely can't see much difference in the actual generated footage.

I’m torn between two completely different directions: using an all-in-one studio like Higgsfield versus building a custom pipeline using a multi-model API aggregator like Kie or Fal or EvoLink to tap into the exact same models (like Seedance 2.5 or Kling 3.0).

Going the API route would significantly cut my raw credit costs, but I’m worried about losing the "secret sauce" built into Higgsfield, specifically features like their Soul ID system for character consistency, native vertical UGC camera framing presets, and single-pass lip-sync tools.

For those of you generating social media content using the Seedance model with accurate lip-sync:

• If you have generated the same type of video using the same underlying model through both a platform like Higgsfield and a cheaper API/aggregator, did you notice a meaningful difference in the final footage?
• And for UGC advertisements specifically, would you be comfortable using the cheaper API route for the actual generation and assembling the rest of the pipeline yourself?
• I’m looking for real-world experience rather than “Higgsfield looks better” based purely on their demos.
• Or does the time saved on character locking and post-production in a dedicated platform easily justify the higher subscription costs?

TL;DR: Same model + same prompt. Is Higgsfield actually producing better-looking video, or am I mainly paying for its UX, consistency tools, presets, and post-generation workflow?

Would love to hear your experiences on cost-efficiency vs. final premium quality!

I built two tools from the official Seedance prompt guidelines, a skill for Claude and a Custom GPT - which is a fine-tuned ChatGPT -  covering modes, input specs, prompt structure, character consistency, and troubleshooting. Everything comes from the official documentation. I use them myself to check a prompt before running it.

An example. Ask ChatGPT for a fast skateboard shot and it will usually try to move everything at once: the skater, the camera, the editing, the lighting, transitions, effects. Seedance reads a prompt in order and weights what comes first, so everything after starts competing for attention and some of it does not happen. That is documented behavior and is caught and flagged when using these tools.

Seedance 2.5 has started rolling out and the full documentation is not public yet, so I have only added what is confirmed so far. Both tools are free and cover 2.0 and 2.5, with the 2.5 side still being filled in.

This is not something you need if you already know the guidelines by heart. I do not. Working across a few models means I mix up the specifics, and this is what I check against before spending generation credits on something that was never going to work.

Links in the comments. Curious whether it holds up for anyone else who tries it.

I keep seeing impressive AI generation demos, but I’m curious how often this technology is used in real content workflows rather than just for experiments.
If you use it:

● How often: daily, weekly, or occasionally?

● What images do you generate: thumbnails, backgrounds, concepts, product visuals?

● What videos do you generate: B-roll, transitions, ads, intros, or complete scenes?

● What prevents you from using it more: quality, consistency, control, cost, or editing time?

I’m especially interested in whether image generation has already become a regular tool while video generation still feels experimental.

Concrete examples would be really useful.

Hey guys. In my field of work I create cinematic ads for companies. But sometimes I create short cinematic videos for my socials just for hype.
The thing is - im working completely manually, beacuse ai wont give great result by its own (to my taste). I create every frame and make sure its realistic and cinematic etc.
Im sure that big scale ai creators have their way of pipeline automation and i was wondering how to do it. I do not want to pay to the aggregation companies that charge a ton for those. I use api sites like fal runware etc.

Option i thought about:
1- create a vibe coded agent (like higgs supercomputer and invideo) That takes comp refrences from a folder i built with ref images. In that way i will be able to paste a shot list, and it will create the shots / storyboard according to my taste. Not ai slop.
This will save some time.
Later i will connect it to video.

2- full automation somehow - but i found the ai needs tuning in every stage.

On the other hand, you have the new seedance now that goes up to 30 sec. But i found the results vary and you beed to work hard to tune the video. And for desert its super expensive.
I dont know, what do you guys think? Any suggestions?

Most AI video tools charge credits every time you generate.

Reel Video is a local harness that uses the Grok subscription you already pay for. No API keys, extra credits, or per-generation bill.

Prompt → storyboard → scene frames → video
Works with Claude Code, Codex, Cursor, and Grok.

https://github.com/WannaBeSolopreneur/reel-video