BREAKING NEWS
LATEST POSTS
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Brian Gallagher – Why Almost Everybody Is Wrong About DeepSeek vs. All the Other AI Companies
Benchmarks don’t capture real-world complexity like latency, domain-specific tasks, or edge cases. Enterprises often need more than raw performance, also needing reliability, ease of integration, and robust vendor support. Enterprise money will support the industries providing these services.
… it is also reasonable to assume that anything you put into the app or their website will be going to the Chinese government as well, so factor that in as well.
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One-Prompt-One-Story – Free-Lunch Consistent Text-to-Image Generation Using a Single Prompt
https://byliutao.github.io/1Prompt1Story.github.io
Tneration models can create high-quality images from input prompts. However, they struggle to support the consistent generation of identity-preserving requirements for storytelling.
Our approach 1Prompt1Story concatenates all prompts into a single input for T2I diffusion models, initially preserving character identities.
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What did DeepSeek figure out about reasoning with DeepSeek-R1?
https://www.seangoedecke.com/deepseek-r1
The Chinese AI lab DeepSeek recently released their new reasoning model R1, which is supposedly (a) better than the current best reasoning models (OpenAI’s o1- series), and (b) was trained on a GPU cluster a fraction the size of any of the big western AI labs.
DeepSeek uses a reinforcement learning approach, not a fine-tuning approach. There’s no need to generate a huge body of chain-of-thought data ahead of time, and there’s no need to run an expensive answer-checking model. Instead, the model generates its own chains-of-thought as it goes.
The secret behind their success? A bold move to train their models using FP8 (8-bit floating-point precision) instead of the standard FP32 (32-bit floating-point precision).
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By using a clever system that applies high precision only when absolutely necessary, they achieved incredible efficiency without losing accuracy.
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The impressive part? These multi-token predictions are about 85–90% accurate, meaning DeepSeek R1 can deliver high-quality answers at double the speed of its competitors.Chinese AI firm DeepSeek has 50,000 NVIDIA H100 AI GPUs
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CaPa – Carve-n-Paint Synthesisfor Efficient 4K Textured Mesh Generation
https://github.com/ncsoft/CaPa
a novel method for generating hyper-quality 4K textured mesh under only 30 seconds, providing 3D assets ready for commercial applications such as games, movies, and VR/AR.
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Fal Video Studio – The first open-source AI toolkit for video editing
https://github.com/fal-ai-community/video-starter-kit
https://fal-video-studio.vercel.app
- 🎬 Browser-Native Video Processing: Seamless video handling and composition in the browser
- 🤖 AI Model Integration: Direct access to state-of-the-art video models through fal.ai
- Minimax for video generation
- Hunyuan for visual synthesis
- LTX for video manipulation
- 🎵 Advanced Media Capabilities:
- Multi-clip video composition
- Audio track integration
- Voiceover support
- Extended video duration handling
- 🛠️ Developer Utilities:
- Metadata encoding
- Video processing pipeline
- Ready-to-use UI components
- TypeScript support
FEATURED POSTS
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SourceTree vs Github Desktop – Which one to use
Sourcetree and GitHub Desktop are both free, GUI-based Git clients aimed at simplifying version control for developers. While they share the same core purpose—making Git more accessible—they differ in features, UI design, integration options, and target audiences.
Installation & Setup
- Sourcetree
- Download: https://www.sourcetreeapp.com/
- Supported OS: Windows 10+, macOS 10.13+
- Prerequisites: Comes bundled with its own Git, or can be pointed to a system Git install.
- Initial Setup: Wizard guides SSH key generation, authentication with Bitbucket/GitHub/GitLab.
- GitHub Desktop
- Download: https://desktop.github.com/
- Supported OS: Windows 10+, macOS 10.15+
- Prerequisites: Bundled Git; seamless login with GitHub.com or GitHub Enterprise.
- Initial Setup: One-click sign-in with GitHub; auto-syncs repositories from your GitHub account.
Feature Comparison
(more…)Feature Sourcetree GitHub Desktop Branch Visualization Detailed graph view with drag-and-drop for rebasing/merging Linear graph, simpler but less configurable Staging & Commit File-by-file staging, inline diff view All-or-nothing staging, side-by-side diff Interactive Rebase Full support via UI Basic support via command line only Conflict Resolution Built-in merge tool integration (DiffMerge, Beyond Compare) Contextual conflict editor with choice panels Submodule Management Native submodule support Limited; requires CLI Custom Actions / Hooks Define custom actions (e.g., launch scripts) No UI for custom Git hooks Git Flow / Hg Flow Built-in support None Performance Can lag on very large repos Generally snappier on medium-sized repos Memory Footprint Higher RAM usage Lightweight Platform Integration Atlassian Bitbucket, Jira Deep GitHub.com / Enterprise integration Learning Curve Steeper for beginners Beginner-friendly - Sourcetree
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Tencent Hunyuan3D 2.1 goes Open Source and adds MV (Multi-view) and MV Mini
https://huggingface.co/tencent/Hunyuan3D-2mv
https://huggingface.co/tencent/Hunyuan3D-2mini
https://github.com/Tencent/Hunyuan3D-2
Tencent just made Hunyuan3D 2.1 open-source.
This is the first fully open-source, production-ready PBR 3D generative model with cinema-grade quality.
https://github.com/Tencent-Hunyuan/Hunyuan3D-2.1
What makes it special?
• Advanced PBR material synthesis brings realistic materials like leather, bronze, and more to life with stunning light interactions.
• Complete access to model weights, training/inference code, data pipelines.
• Optimized to run on accessible hardware.
• Built for real-world applications with professional-grade output quality.
They’re making it accessible to everyone:
• Complete open-source ecosystem with full documentation.
• Ready-to-use model weights and training infrastructure.
• Live demo available for instant testing.
• Comprehensive GitHub repository with implementation details.
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PBR Color Reference List for Materials – by Grzegorz Baran
“The list should be helpful for every material artist who work on PBR materials as it contains over 200 color values measured with PCE-RGB2 1002 Color Spectrometer device and presented in linear and sRGB (2.2) gamma space.
All color values, HUE and Saturation in this list come from measurements taken with PCE-RGB2 1002 Color Spectrometer device and are presented in linear and sRGB (2.2) gamma space (more info at the end of this video) I calculated Relative Luminance and Luminance values based on captured color using my own equation which takes color based luminance perception into consideration. Bare in mind that there is no ‘one’ color per substance as nothing in nature is even 100% uniform and any value in +/-10% range from these should be considered as correct one. Therefore this list should be always considered as a color reference for material’s albedos, not ulitimate and absolute truth.“