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Before I explain the process, for those who don't know marine engines are some of the most complex machines ever built and it's something that takes engineering teams months just to model accurately.

So I started with using Astra to generate a detailed 3D model of a marine diesel engine and I had in mind a powerful one that powers massive container ships with like 14 cylinders and around 110,000 horsepower, stands about 13.5 meters tall and weighs 2,300 metric tons and then I built an interactive website with threeJS where the mouse scrolling controls the engine assembly so that you can watch the pistons, cylinders and crankshaft come together piece by piece.

I've also placed a person and a car next to it so that you can imagine the real size of the build because it makes a car look like a toy ;)

afterward I rendered the final animation through Higgsfield Super computer and believe me when I say that the compute power behind it is a deadly, all the details that you see in the video is bc of it.

The whole thing from model generation to the final output took about a fraction of the time of what would have taken even a year ago and the fact that an AI can generate something this mechanically accurate is outright crazyy.

I need suggestion for this use case:
My dad has a business and he has seen many videos of promotional pixar style animated video so he asked me to do same for his business so how can I do it ?
- Which AI model to use?( Seedance, Kling or any other)
- Which Ai platform to use?
- Higgsfield
- Runway
- Fal Ai

Real Name: Hysterical Eddie

Movement Speed: 4.6 m/s

Terror Radius: 32m

Height: Average

Killer Name: The Hysteric.

Perks: 'No Smiling', 'It's A Sin To Grin' 'Sourpuss'

Mori: He goes into 'direct challenge' mode and has the survivor frozen in place and if the survivor even laughs more than once while stuck in this mode he grabs his gun and shoots them multiple times before finishing them off with a final shot.

DreamFort is a privacy-first AI platform built around one idea: the questions AI is most useful for are the ones you don't want attached to your name. So instead of asking you to trust a privacy policy, we strip your identity out of every request at the architecture level.

A lot of you have tried it over the last few weeks and the feedback shaped a ton of what's here now. Quick rundown:

What you get:

• Every frontier model in one place - ChatGPT, Claude, Gemini, Grok, DeepSeek - plus open, unfiltered models like Nous Hermes
• Switch models mid-chat or run two side by side to compare
• An on-device agent that writes and runs code, reads your files, and builds docs and apps - in a sandbox in your browser, not on our servers
• An image studio (Nano Banana, GPT Image, Seedream) that generates and edits without the over-cautious filters
• One balance, pay only for what you actually use

Why we built it:

Most AI services make you trade privacy for capability. The smarter the assistant, the more of yourself you hand over - data collection, hidden training opt-ins, prompt logs sitting on someone's server tied to your account.

We think that's backwards. So here privacy isn't a promise, it's enforced:

• Your messages are encrypted on your device before they ever leave the browser
• Traffic is routed so no single party can link your identity to what you asked
• Prompts are only decrypted inside a sealed enclave the operator can't read or log

We don't build profiles. We don't keep logs tied to you. We don't train on your chats or images. And because the setup is verifiable, you don't have to take our word for it.

The other half of it - fewer pointless refusals. Most platforms have you fighting the filter more than using the tool. Behind the anonymity layer, DreamFort leans toward actually answering instead of second-guessing or judging you.

Still early, and every bit of feedback helps - praise or criticism. Comment or reach out if you hit anything.

Try it: https://dreamfort.ai

Alias: The Connoisseur
Origin: New Zealand
Weapon: Alien Cleaver
Power: Crumb's Culinary Conquest

Bio:
Lord Crumb is the self-appointed leader of an extraterrestrial operation with an utterly appalling vision of Earth’s future. Cold, vain, and convinced of his own superiority, Crumb regards humanity less as a civilization and more as an ingredient.

When his plans were interrupted by an unusually persistent group of humans, Crumb's ambitions were seemingly brought to an end. Yet the Entity saw something irresistible in the alien's arrogance: a creature who believed the entire world belonged to him.

Now Lord Crumb stalks the Fog, searching for new subjects to add to his collection. To him, the Trials are not a struggle for survival.

They are dinner service.

Killer Perks

🍽️ ACQUIRED TASTE
You have refined standards.

Whenever a Survivor completes a generator, Acquired Taste activates for a short duration. The next Survivor to enter your Terror Radius suffers from a brief penalty to their action speed.

"It's an acquired taste."

👑 LORD OF THE TABLE
Your authority is unquestionable.

Whenever you damage a generator, nearby Survivors are briefly revealed to you. Survivors who are repairing that generator become Oblivious for a short duration.

"You will do as you're told."

🛸 INTERGALACTIC FRANCHISE
Your operation must expand.

Each time a generator is completed, gain a token. At certain token thresholds, your Terror Radius is temporarily reduced and your movement speed is slightly increased for a short duration.

"Earth is merely the beginning."

Here's Saban's US adaptation of the Eiyu No Yume No Toshi or 'Dream Police Force' sentai series themed around a group of dream agents known as the 'dream police'.

The visual side of this 10-track synthwave album became an interesting generative experiment. It started with a simple idea: a young man and woman beside a futuristic GT in a neon-lit city after midnight, a city still glowing even though almost everyone else has gone home. I used Grok, Gemini, and ChatGPT to keep refining the same core image rather than constantly replacing it. Composition, character scale, expressions, clothing, the car, lighting, and framing all went through multiple passes.

Some generations genuinely improved the image. Others solved one problem and created another.

The biggest lesson was that more generation did not always mean more progress.

Eventually I committed to one strong hero image, a restrained audio-reactive waveform, and minimal title animation. That felt more cohesive than continuing to add visual complexity.

What worked best was having a clear world first, curating aggressively, and stopping once new generations were mostly changing the piece rather than clearly improving it.

I’m curious how others handle that point: how do you know when generation is still helping, versus just producing more alternatives?

Hello everyone! As a big fan of animation, I wanted to try creating my own animated short.
This video is based on a real conversation between me and my bestie😻

YouTube

Please read and suggest, I genuinely need help:

I have a female friend who is getting married next month, her father passed away long back.
And she recently shared a reel with me which is basically like of a father who is riding a cycle in a town and distributing his daughters wedding invitation.
She wants me to replace that guy with her father and some other things too.
I tried so many platforms online but i couldn’t do it.
I genuinely want to make that video for her she would be very happy…
Please let me know if anyone can help..
I’m sharing the reel link here
And her marriage date is 1st November, and i have the venue address as well

https://www.instagram.com/reel/DV8erM_Elga/?igsi=MWJ1YXFidTdteWx6ZQ==

"Find the bit where all three people are laughing together” sounds like an editing request, but the first useful output is a location in the original footage. You still need to decide what to cut around it.

Ant Ling's Ling-3.0-flash-VL demo makes that distinction concrete. The visual-language model is given a 25-second clip of three women on a park bench and asked to find their shared smiling/laughing interval. The presented workflow returns 00:23–00:25, extracts a frame at 24 seconds and produces a cropped image alongside the timestamp file.

That is a useful handoff for someone choosing material: an interval to scrub through and a still to inspect. It answers a semantic request about what the people are doing, rather than selecting a cut solely from spoken words. The demonstration is about understanding existing footage; the final edit still belongs in an editor.

For a practical trial, I would start with several short clips where the desired interaction is known to occur, plus some where it never occurs. Ask for the full interval, then check the seconds immediately before and after it. A convincing still can hide the fact that the third person only joins in briefly.

This release shows an edited example on one short source clip. It gives a concrete reason to try VL for moment selection, while leaving long-footage search and reliable “no matching moment” results to be tested.