https://huggingface.co/spaces/fancyfeast/joy-caption-alpha-two

https://pinokio.computer

https://www.patreon.com/posts/create-from-with-115147229

https://www.thinkdiffusion.com

https://www.voxon.co

Here’s the journey of crafting a compelling paper:

1️. ABSTRACT
This is your elevator pitch.
Give a methodology overview.
Paint the problem you’re solving.
Highlight key findings and their impact.

2️. INTRODUCTION
Start with what we know.
Set the stage for our current understanding.
Hook your reader with the relevance of your work.

3️. LITERATURE REVIEW
Identify what’s unknown.
Spot the gaps in current knowledge.
Your job in the next sections is to fill this gap.

4️. METHODOLOGY
What did you do?
Outline how you’ll fill that gap.
Be transparent about your approach.
Make it reproducible so others can follow.

5️. RESULTS
Let the data speak for itself.
Present your findings clearly.
Keep it concise and focused.

6️. DISCUSSION
Now, connect the dots.
Discuss implications and significance.
How do your findings bridge the knowledge gap?

7️. CONCLUSION
Wrap it up with future directions.
What does this mean for us moving forward?
Leave the reader with a call to action or reflection.

8️. REFERENCES
Acknowledge the giants whose shoulders you stand on.
A robust reference list shows the depth of your research.

https://zju3dv.github.io/envgs

Odyssey and a Pixar co-founder, Ed Catmull (also an investor), just dropped Explorer, a revolutionary 3D world generator that turns any image into an editable 3D world.

https://odyssey.systems/introducing-explorer

https://animateai.pro

https://www.producthunt.com/posts/animate-ai

https://aidemos.meta.com/videoseal

https://www.maginative.com/article/meta-releases-video-seal-an-open-source-watermarking-tool-for-ai-video

https://github.com/facebookresearch/videoseal

https://github.com/TencentARC/BrushEdit

https://github.com/Genesis-Embodied-AI/Genesis

https://genesis-world.readthedocs.io/en/latest

Genesis is a physics platform designed for general purpose Robotics/Embodied AI/Physical AI applications. It is simultaneously multiple things:

1. A universal physics engine re-built from the ground up, capable of simulating a wide range of materials and physical phenomena.
2. A lightweight, ultra-fast, pythonic, and user-friendly robotics simulation platform.
3. A powerful and fast photo-realistic rendering system.
4. A generative data engine that transforms user-prompted natural language description into various modalities of data.

PDF under the post

(more…)

https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-orin/nano-super-developer-kit

https://www.pencil2d.org

https://natrongithub.github.io

https://www.shotcut.org

https://snap-research.github.io/wonderland

https://deepmind.google/technologies/veo/veo-2

https://zixuan-ye.github.io/stylemaster

https://kaist-viclab.github.io/splinegs-site

https://github.com/comfyanonymous/ComfyUI

https://github.com/ltdrdata/ComfyUI-Manager

https://www.thinkdiffusion.com

https://comfyworkflows.com

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https://docs.google.com/document/d/1u7_-LdTyXhv_00M1SPnnJohsGS-PVe0lkbosEX4gsrE

https://pika.art

https://developer.nvidia.com/blog/high-fidelity-3d-mesh-generation-at-scale-with-meshtron/

Meshtron provides a simple and scalable, data-driven solution for generating intricate, artist-like meshes of up to 64K faces at 1024-level coordinate resolution. This is over an order of magnitude higher face count and 8x higher coordinate resolution compared to existing methods.

https://speedysplat.github.io

https://substack.com/inbox/post/153106976

https://techcrunch.com/2024/12/14/what-are-ai-world-models-and-why-do-they-matter/

A model that can generate the next frame of a 3D scene based on the previous frame(s) and user input, trained on video data, and running in real-time.

World models enable AI systems to simulate and reason about their environments, pushing forward autonomous decision-making and real-world problem-solving.

The key insight is that by training on video data, these models learn not just how to generate images, but also:

• the physics of our world (objects fall down, water flows, etc)
• how objects look from different angles (that chair should look the same as you walk around it)
• how things move and interact (a ball bouncing off a wall, a character walking on sand)
• basic spatial understanding (you can’t walk through walls)

Some companies, like World Labs, are taking a hybrid approach: using World Models to generate static 3D representations that can then be rendered using traditional 3D engines (in this case, Gaussian Splatting). This gives you the best of both worlds: the creative power of AI generation with the multiview consistency and performance of traditional rendering.

https://diamond-wm.github.io

https://stereo4d.github.io

Alexander Brazie gameplay design

https://zju3dv.github.io/longvolcap

https://jalammar.github.io/illustrated-transformer

https://tensor.art

https://www.linkedin.com/feed/update/urn:li:activity:7272708823654576129