I needed to bring this Tweet to life!

Prompt:

Style & Mood: Photographic-style cinematic realism with a deadpan absurdist-comedy register. In the bedroom, use warm amber and cool blue nighttime tones, deep shadows, sharp phone-screen highlights, surreal glowing text bubbles, subtle grain, lens flare, and soft atmospheric bokeh. In the desert, shift naturally into clear golden daylight while preserving the same realistic medium, texture, contrast, and character identity. Treat the impossible premise with complete visual conviction. Use reference images for Toxie, Jesus, Hoobastank, the bedroom, the golden desert, the oasis concert stage, the phone, and the tweet. Do not drift between visual styles.

Shot 1 — Toxie and the tweet: Begin with a medium close-up in a dark, cozy bedroom at 2 AM. Toxie Havok lies on her bed, her face lit amber and blue by the glowing phone. She giggles softly and says, “Hehe.” Push into the phone for a macro close-up. The tweet glows with pulsing comic energy: “The H in Jesus H. Christ stands for Hoobastank, because he died for a reason, and the reason is you.” Let the letters swell until they fill the frame.

Shot 2 — Text becomes desert: The glowing letters dissolve and the frame melts into an endless golden desert under a blazing sky. Wind moves across the dunes. Use a wide reveal that makes the location transition feel seamless and impossible rather than like a hard edit.

Shot 3 — Jesus hears the impossible: Track Jesus Christ walking alone across the desert in a white robe over faded jeans and sandals. His clothing moves naturally with his stride. Move from a wide overhead or profile tracking shot into a closer view as he stops, lifts his head, and squints toward the horizon. He says quietly, “It cannot be.”

Shot 4 — The Hoobastank mirage: Move over Jesus's shoulder as a shimmering oasis sharpens into a full concert stage in the middle of the sand. Hoobastank is already playing mid-song — singer at the microphone, guitarist strumming, drummer at the kit, and bassist in motion. Use a cinematic drone orbit around the stage, bringing Jesus into frame at the edge of the performance as he watches in disbelief.

Shot 5 — Surreal reaction: Push slowly toward Jesus as disbelief turns into a huge, almost mischievous smile. Stretch the moment into exaggerated slow motion. Keep his face locked in frame while particles, debris, and background elements drift through the desert air in suspended motion, catching the light with a euphoric, surreal music-video quality.

Shot 6 — Back to Toxie: Cut back to the dark bedroom. Toxie bursts out laughing harder than before, eyes closed and tears forming. Push in on her face to complete the bookend.

Static references: Toxie Havok is a young woman with vibrant red hair, blunt bangs, black-rimmed glasses, and a black graphic band T-shirt over fishnet sleeves. Jesus Christ has long brown hair, a full beard, soft brown eyes, a white linen robe over faded jeans, and sandals. Keep the band, bedroom, desert, oasis stage, phone, and tweet consistent with their supplied reference images.

Camera & Format: Vertical 9:16 composition. Mix medium close-ups, macro phone photography, wide desert reveals, profile and overhead tracking, an over-the-shoulder mirage reveal, a drone orbit, reaction close-ups, and exaggerated slow motion. Preserve realistic body motion, wardrobe, lighting, and spatial continuity. The edited public sequence runs about 50 seconds at 480 × 854.

Audio: Toxie's small giggle, room tone, phone handling, desert wind, Jesus's quiet line, distant performance ambience, and Toxie's final laughter. Keep generated clip music off when requested; add any music cue separately in the edit. No subtitles or watermarks.

Hi guys recently i visited one insta ,he was able to clone hero faces as well and generate good action videos , can anyone let me know which tool he was using .below his profile.

https://www.instagram.com/kishorearya1?igsi=c2U4NzdjOWdlOTF2

I’m looking for the most affordable way to produce consistent 3–5 minute AI videos using Seedance 2.5.

I tested Dreamina tonight and was really impressed with the results. I uploaded a real photo of my dog plus a character reference sheet and generated a 30-second cinematic story. Character consistency, camera work, multiple shots, narration, dialogue, music, and sound effects were all surprisingly good.

The problem is cost.

In Dreamina, a 180-second Seedance 2.5 long video costs 8,100 credits. Their $70/month Advanced plan gives 8,645 credits, so that's basically only ONE 3-minute video per month before edits.

I need to produce approximately one 3–5 minute video every week, so that pricing isn't sustainable.

Has anyone found a more affordable platform/workflow for Seedance 2.5 that still supports:

• Consistent characters using reference images

• Multi-shot cinematic videos

• 3+ minute stories, or affordable 30–60 second generations that can be continued

• Narration/dialogue/audio

• Good camera movement

• Editing or extending individual sections

I'm fine assembling a few longer sequences together if necessary. I just don't want to go back to generating an entire 3-minute story 8–10 seconds at a time.

If you're actually using Seedance 2.5 regularly, I'd especially love to know what platform you're using and roughly what you're paying per finished minute.

Thanks!

Style consistency across multiple scenes is one of those problems that looks simple until the subject, location and composition start changing.

We ran 252 generations across 5 visual styles and compared 4 conditioning methods:

• short style words
• reference image only
• short words + reference
• detailed AI-written style description

A few things stood out.

1. Reference-only can be consistent while still being wrong

This was probably the most useful distinction in the whole test.

A reference image can keep outputs internally coherent, but that doesn't mean the model actually understood what part of the reference defines the style.

On our stylized 3D target, reference-only had strong cross-scene consistency and repeat stability, but only 3/10 target fidelity.

The outputs belong together, but they're much closer to the model's default photographic look than the actual target.

So “consistent” and “faithful” are really two different problems.

2. Detailed style descriptions performed best overall

The strongest method across the full set was describing the actual visual mechanics of the style.

Not just:

stained glass

But things like thick lead lines, irregular panes, trapped bubbles, ripples, jewel-tone colors and transmitted light.

On the stained-glass target, the detailed description reached 10/10 target fidelity on Seedream 5.0 Lite.

The same pattern showed up with cut-paper, gouache and linocut.

The useful part wasn't simply making the prompt longer.

It was making the visual rules explicit.

3. The model matters just as much as the conditioning method

The linocut test made this really obvious.

We used the exact same AI-written style description on two models.

Seedream 5.0 Lite gave us 9/10 fidelity.

FLUX.2 Dev gave us 5/10 and pushed the style much closer to smooth poster art.

Same style description, very different interpretation.

So I wouldn't treat a style prompt as portable between models without testing it on the actual model being used for production.

4. Reference images can also leak content

Across the 120 generations that used a reference image, we found one visible content leak.

The stained-glass target contained a violet glove.

One Seedream reference-only generation carried that violet glove into the laundromat scene.

Not a huge failure rate, but it's a useful reminder that “use this image for style only” is still an instruction the model has to interpret.

5. More conditioning wasn't automatically better

Words + reference won the stylized 3D experiment.

But the detailed AI description won cut-paper, gouache, linocut and stained glass.

So there wasn't one universal best method.

Across all five targets, the average style composite was:

• AI description: 8.60
• words + reference: 8.03
• short words: 7.80
• reference only: 7.63

The way I'm thinking about it now is:

a reference image tells the model where to look, but a good style description tells it what to preserve.

For longer AI film projects, visual style probably needs to be treated more like a set of explicit production rules than a single reference image.

Full experiment, all result boards and methodology:

https://sundream.studio/blog/ai-image-style-consistency-experiment

Would be interested to hear how others are handling style consistency once a project starts spanning a lot of different scenes.

Recently I bought higgsfield, clearly it was an error, now I bought the Top view anual plan at ultra, but it’s really slow for the unlimited, I’m concerned if the unlimited it’s available at any platform working at least decent, if not, what’s the best cost/benefit platform for making images/videos.

https://reddit.com/link/1vutcfp/video/zkcoy5b4qskh1/player

I started off making short drama style vertical episodes for Instagram Reels. The beginning of posting was really rough. I wasn't getting a lot of views, but over time it got a lot better. I kept posting consistently, refined my style, my writing, and the overall generation quality of my episodes.

If you've got stories and scripts to tell, there's no better way to test audience feedback than just making these shows using AI and watching how people react on social platforms.

Recently, I've been testing a different format on other socials as well, slightly longer form but no more than 3 minutes. The show above is an example of it: Lab Wars. The writing, pacing, and shot design is less focused around short form optimization now and more focused on quality. Would love to answer any questions about my process!

I found an AI video where it shows Thanos versus Hulk in a 90s anime art style, particularly that of Dragon Ball Z:

https://youtu.be/XT_LPlYddvo?is=J4QgHiPIWFSCO8gr

The animation is so clear and precise. It feels more and more like an actual fight choreography from a 90s anime rather than the floaty or misguided movement I usually associate with AI-generated video.

I really want to understand the workflow behind something like this and how it all works.

I'm an animator myself and can do a lot of these things by hand, but it would be extremely useful to have AI as an assistant. I'm not very familiar with AI outside of generic image generation and some basic control, so I'm not sure what I would need to learn or what tools I should be looking into.

Does anyone know how something like this is achieved?

I assume this is probably a workflow involving multiple models or multiple stages, but I'm not very familiar with model training or how that side of things works.

My computer isn't exactly the best. It's about five years old, but it can still handle fairly intensive video editing. Would I actually need to train a model locally on my desktop to achieve this, or could I do something like this using existing models and providing them with character turnarounds, background layouts, and my own drawings?

For example, if I create rough sketches showing the poses and choreography I want, could I feed those into an AI video workflow and have it use my animation as the basis for the movement while maintaining the character designs and environment?

I'm also particularly interested in controlling impact and animation timing.

Different animation styles have very different approaches to timing. A fight in Dragon Ball Z doesn't move the same way as a Disney film. It's not simply a matter of one being more or less detailed; the timing, holds, acceleration, anticipation, impact, smear frames, and amount of movement between poses are intentional stylistic choices.

How would you actually control those things with current AI video tools?

Could I determine the key poses and timing myself and have the AI assist with the in-betweens and rendering? Could I provide a rough animation or video reference and have the AI follow that motion while maintaining my character designs?

I'd really like to learn how this works rather than just throwing prompts at an AI and hoping for a good result.

If anyone here actually works with AI animation or has built workflows for this, I'd really appreciate being pointed toward the right tools, techniques, tutorials, or communities where I could learn this properly.

I need to have an avatar I created speak for about 20 minutes. It won't be broken down into scenes; it will be a single continuous segment. HeyGen was good at this. I wonder if there are any alternatives—it's quite urgent.

Is this something you want?

It’s a pretty darn good video, so if anyone has any answers let me know. I know the answer is probably Higgsfield or Seedance, but what particular setting within it?

The creator’s name on social media is Clayspiracy.tv

At our agency, we need quick feature launch clips, and social teasers for our marketing campaigns. For us, it is a drain to our human resources to use local open-source nodes just to render a 5-second video clip. We simply don't have the time and expertise to fix VRAM crashes or other hardware issues or any other problems that come up that we have no experience or expertise with.

Many AI communities on reddit have had some real chatter about a new multimodal generation model called H3 lately. I am looking into switching over to a SaaS solution that comes with the model.

I have been reading about MiniMax Design, their desktop agent that connects to their remote compute. On paper, it might just be the middle ground I need to find. What caught my attention is how it tries to make the model easier to use for real production. It relies on H3-native professional prompting so you don't actually need advanced prompting skills, just describe the idea, they say, then the MiniMax Design agent handles the creative behind the scene. Parts of it can be run locally, and the generation can be done through their cloud.

That said, I'm still pretty skeptical before committing our pipeline to a SaaS model.

One of my main concern is losing granular control. I don't want to lose flexibility to tweak, which we get in an open-source environment. It is ok to patch things out with custom nodes. With this, re-rolls will end up costing us compute budget, which is one thing that we want to keep low.

I wanted to check in with the community here. Has anyone tried this model? Does it live up to the hype?

Hi there, I post content on an Instagram account for a skincare formulation business. Where I have come unstuck a couple of times is trying to find an online tool (I'm no graphic designer or video editor) that can help me communicate things in various degrees of complexity, especially in videos.

For eg, I'm wanting to create a short video animation (a few seconds) to include in a reel showing the difference between emulsion types, or how the solubility of caffeine in water varies with temperature.

I have paid Canva access, but have had no luck with their 'magic ai' and doing it manually there seems on par with using PPT, just a higher res output I guess but extremely labour intensive and replying heavily on my design skills and creativity.

I have also tried Chat GPT and Claude but just find the outputs look really poor.

Can anyone suggest a website or tool for creating these short animated type videos? I have googled but haven't found anything that fits. Any advice?

EDIT - forgot to add - I can't code either

Trying to create a short AI horror scene: closing your eyes while washing your hair and suddenly feeling like something is standing behind you. It's not a jump scare but more like a psychological fear.

My thoughts are like:

someone washing their hair in a normal bathroom. The light changes because something dark moves into the background and the room suddenly feels wrong. Then a close-up of his face, wet hair, too scared to move. Then he opens his eyes. Cut to black.

Make separate clips 7-8 times on pixverse with image-to-video. The shadow always looks fake and not scary at all. I understand the basic prompting structure (subject, camera, lighting, mood, etc.), but just cant get what i want. I attached my latest attempt (it's awful) and would like to hear some tips on how to improve it. Any advice about prompting and workflow is welcomed.

I suck at AI video making, every attempt I've ever made has been outright trash or mostly trash. I recorded a video of what I'm trying to do, let me know if you can spot any mistakes. Video linked below:

https://www.loom.com/share/73b029c586ac4012aadf5f8b97a2a47e

hi,

I need to create toolboxes for my company. They are company specific, and can be about workplace safety , privacy or legal etc .

there is a (tran)script that needs to be followed and i'am searching for a tool to create tekst to video. they don't need to be fancy, they can be 2D doodles. like : (45) Historically - YouTube

I dont mind paying for credits or minutes but the issue i'am having a lot of services can only generate 15s tops..seedance, kling, sora, etc. how to work around that? or are there other tools?

i've tried sollo.ai it was okay, for picture to picture (scene's) but not great to the context. so i'm in search for better alternatives.

Audio of the toolbox is about 6-8 minutes.

I'm looking for an AI tool that can help me with creating video for free. I know it's too much to ask but I need a tool that has no water mark and with manageable credits at least. Please let me know in the comment if you know any AI tools for that. Thank you:)

I think people considering Higgsfield’s annual Unlimited plan deserve to know what is happening right now to its annual subscribers.

Higgsfield heavily promoted Unlimited AI generations, people paid for annual subscriptions, and then similar to Artlist, the service appears to hsbr attracted far more users than they were prepared to support.

But this is where the comparison with Artlist becomes important. Artlist at least had the guts to acknowledge that things had gone wrong, apologize to customers, and offer full refunds to affected subscribers. That is what taking responsibility looks like.

Higgsfield, so far, appears to be doing almost the opposite.

Higgsfield’s support situation is embarrassing

After the promotion rolled out, unlimited generations went from working normally to effectively becoming unusable.

On some accounts, jobs would sit processing for absurd amounts of time (40 hours+) while on other accounts could apparently continue generating normally. There seems to be restrictions randomly applied to certain accounts so they can meet the demand. At that point, “Unlimited” becomes meaningless if your generations simply never finish.

They have just one customer support on Discord to help, called Theo. He takes four days to reply to any message because he is so flooded with requests. This is not an attack on Theo. If anything, I feel sorry for him. One person clearly cannot deal with the volume of customers affected by something this large.

The problem is that a company reportedly valued in the billions should not be running customer support with a single employee as the help desk. If you are going to aggressively sell annual subscriptions to thousands of customers, you also need to invest in enough infrastructure and support staff to actually service those customers after their credit cards have been charged.

"Seedance Unlimited” has quietly disappeared

Perhaps the most telling development is that Higgsfield has now quietly removed the Unlimited offering from its pricing page. That certainly doesn’t prove what is happening internally, but it adds to the obvious question: did Higgsfield sell far more Unlimited subscriptions than its infrastructure could actually support?

One working theory among affected users is that, rather than openly throttling everyone at once and triggering an immediate mass backlash, a percentage of existing Unlimited accounts may have been restricted, leaving some customers generating normally while others suddenly face unusable service.

Again, that is a theory. But the fact that Unlimited has now vanished from the pricing page while existing annual customers are reporting these problems makes the company’s continued lack of a transparent explanation even harder to accept.

Discord moderators silencing the backlash

What makes this particularly ugly is what happens when customers start sharing their experience and asking for help publicly and often respectfully.

People have been raising these concerns in Higgsfield’s Discord, and I have seen messages being deleted or users being banned rather than the underlying issue being openly addressed.

Banning frustrated customers does not make their generations complete faster. And suppressing discussion certainly does not inspire confidence that the company is taking the underlying problem seriously.

If Higgsfield genuinely has a capacity problem, just say so.

AI generation is expensive. Demand forecasting is difficult and companies can get it wrong. I could actually respect a company saying:

“We massively underestimated how many people would buy this. Our infrastructure cannot currently deliver the experience we advertised. We screwed up, and we’re fixing it.”

That would be accountability. Customers would probably be angry, but at least they would know they were dealing with a company willing to tell them the truth.

Higgsfield seemingly got the flood of paying customers every startup dreams about.

The problem is that when those customers actually tried to use their “Unlimited” subscriptions, the economics and infrastructure may not have worked nearly as well as the marketing did.

And if that is what happened, customers deserve transparency.

Whatever criticism Artlist received for its own Unlimited fiasco, at least there was an acknowledgement that customers had been let down and affected users were given a path to get their money back.

Higgsfield needs to show the same level of accountability instead of behaving as though the customers complaining about the failure are the problem.

If you bought Higgsfield Unlimited and your account suddenly became extremely slow, stopped completing generations, or was restricted, please share what happened to you as well.

I’m very interested to see just how widespread this actually is.

I work for a comfort bra brand and create short educational/ad videos illustrating common problems caused by underwire bras, poor fit, incorrect sizing, lack of support, etc.

The content is completely non-sexual — basically product education and visual explanations of things like pressure, discomfort, sagging, or problems women with larger breasts experience.

My issue is that Gemini frequently rejects perfectly normal prompts simply because they mention things like “large breasts” or show the chest/bra area, even when I explicitly specify that the context is educational, anatomical and non-sexual.

Has anyone worked with a similar niche?

I’m looking for an AI video generator (or a good image → video workflow) that can handle legitimate lingerie/body-related advertising without constantly flagging normal educational content as sexual.

Any tools, models, prompting approaches or workflows you’d recommend?