Luma Labs might just have taken the lead in computer generated video with their Ray2 model.
It now uses image to video, an update from text to video.
See Theoretically Media for more.
My take: wow. Just wow! (How about lip sync next, eh?)
Riffusion has just opened a public beta and it rocks!
Riffusion is the brainchild of Hayk Martiros and Seth Forsgren.
“Our goal is to make everyone into a musician and bring a future where music is interactive and personalized.”
TechCrunch reported their $4M seed funding in October 2023.
My take: damn! Not only will this create full songs, it will also create stems you can download for further modification in your DAW of choice.
There is a new open source Text to Speech generator in town called Kokomo-82M.
As far as I can determine, it’s being developed by one person, Hexgrad, based on earlier models.
Apparently, this is something you can install and run locally on your own computer.
You can try it out online here. You can also compare various open source models at the TTS Arena.
My take: note that this does not clone voices or emote (at all.) Perhaps in the next version?
Haydn Rushworth has just released COMPARED: 10 AI Emotions – Minimax / Hailuo.ai 12V-01-live vs KLING, VIDU, Runway.
He compares Minimax with Runway, Vidu and Kling.
His conclusions?
Runway was the most sedate whereas Kling was all over the place. Vidu was good, but Minimax was his favourite.
Tao Prompts also compares Sora, Kling, Minimax and Runway.
He concludes that Runway doesn’t tend to add much emotion at all.
My take: it appears that Minimax may be the best platform to generate video from images at the close of 2024. What will 2025 bring us?
Caleb Ward of Curious Refuge has released 2024’s best summary of how to Create Consistent Realistic Characters Using AI.
He suggests using Fal.AI to train a custom LoRA ( fal.ai/models/fal-ai/flux-lora-fast-training ) with at least 10 images of the subject. Then use this model to generate images ( fal.ai/models/fal-ai/flux-lora ) and increase their resolution using an up-res tool. Finally, you can now move on to animating them.
CyberJungle, the Youtube channel of Hamburg-based Senior IT Product Manager Cihan Unur, also posted How to Create Consistent Characters Using Kling AI.
He details how to train a LoRA on Kling using at least eleven videos of your character. Admittedly, this pipeline is a little more involved. He also suggests FreePik as another option.
My take: basically, if you can imagine it, you can now create it.
Glibatree (Ben Schade) recently implored on YouTube: Do THIS to Create Amazing Poses in Midjourney!!!
The problem with a lot of image generators is that they love selfies: front-facing portraits. But what if you want a profile? Ben has a two-step work-around:
“Generate a close-up photo of your subject’s ear and then use the editor to zoom out and create the rest of the image.”
He explains:
“The reason this works is because what Midjourney needed was a pattern interrupt. Take advantage of its usual way to generate images by finding the usual way to generate an image with a more unusual focus. It’s better to choose a focus that is already often viewed from the angle we want.
The point is we can generate any of these things using extremely simple prompts and get very unusual angles to be seeing a person from. And then starting from there once we have the angle well defined we can simply zoom out and make our chosen feature less prominent by changing our prompt to something else and so in the new image the angle we wanted is extremely well defined not by tons of keywords but by the part of the image we already generated.”
This works for Expressions as well. He explains:
“If we start with a photo of just a smile or just closed eyes or just a mischievous smirk, Midjourney will spend all of its effort to create a high quality closeup version of the exact expression we wanted that now, in just one more generation, we can apply to our character by simply zooming out.”
My take: thank you, Ben, for cracking the code!
Tim of Theoretically Media has a great review of FaceFusion 3.0.0 on YouTube:
In it he discusses:
A huge bonus to this pipeline is face_editor. See 14:02 for tools to alter the many elements on faces, such as smiles, frowns and eye lines. Even age.
My take: we are way beyond deep fakes now. The ability to change expression is extremely powerful! Every performance can be altered.
Tim Simmons from Theoretically Media just released a new look at Kling AI’s new 1.5 model:
In it he relates what’s new:
“1080p Professional Mode: Kling 1.5 now generates videos at 1080p resolution when using Professional Mode. While it costs more credits, the output quality is significantly better and sets a new standard for AI video generation.
Motion Brush: Kling has introduced Motion Brush, a long-awaited tool in the AI video generation space. Currently, it’s only supported in the 1.0 model but will be available in 1.5 soon. Stay tuned!
End Frames: End frames have been introduced in the 1.0 model and are coming soon to the 1.5 model, allowing for smoother transitions and more control over your videos.
Using Negative Prompts: Improve your outputs by adding negative prompts to filter out undesired elements. Copy and paste the following negative prompts into your settings:
ARTIFACTS, SLOW, UGLY, BLURRY, DEFORMED, MULTIPLE LIMBS, CARTOON, ANIME, PIXELATED, STATIC, FOG, FLAT, UNCLEAR, DISTORTED, ERROR, STILL, LOW RESOLUTION, OVERSATURATED, GRAIN, BLUR, MORPHING, WARPING”
Of particular note is the emotion it’s able to generate.
Plus, Tim signals that Kling is about to add a full-featured Video Editor. Stay tuned indeed!
My take: of course, some will lament these advances. Yes, tasks that workers once spent their lives performing are now accomplished immediately. Looking at you, Medieval scribe, hot metal typesetter, telephone exchange operator. More job transformation is sure to come. We are well into the Digital Age and its promise is bearing increasingly wondrous fruit.
CyberJungle, the Youtube channel of Hamburg-based Senior IT Product Manager Cihan Unur, recently posted a great video on consistent generated characters.
There are lots of great insights in this 20-minute video. Two outstanding takeaways:
First: a prompting guide for Flux.1. At 15:28 he reveals three prompting styles: list, natural language and hybrid.
Second: a guidance guide for Flux.1. At 17:18 he shows Photorealistic and Cinematic images with a wide scope of guidance values. He posits:
“The essence of guidance setting is a compromise or a balance between photo realism and prompt understanding.”
See 18:36 for the Photorealistic results. He prefers a level of two.
See 19:54 for the Cinematic guidance level he prefers: again two.
My take: to me, too often generated images look over-the-top and so ideal, they’re unrealistic. The key seems to be dialing the guidance down to two. Who knew? Now, you do.
Last week we explored the latest Generated Video (GV) pipeline. This week Seattle’s Yutao Han, aka Tao Prompts, goes further and illustrates How to Create Ai Videos of Yourself!
The goal here is to consistently end up with the same real person in multiple generated video clips.
“In this tutorial we’ll learn how to use the Flux image generator to train a custom AI model specifically for your own face and generate AI photos of yourself. Then we’ll animate those photos with the Kling AI video generator, which in my opinion generates the best AI videos right now.”
In a nutshell, the process is:
My take: it seems week by week we’re getting closer to truly usable generated video that rivals (or even surpasses) Hollywood’s CGI/VFX. Imagine being able to train more than one LORA model into Flux for Kling. I have it on good authority that that is just around the corner.