https://www.galileo.ai/blog/agent-leaderboard
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Category: A.I.
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Flex 1 Alpha – a pre-trained base 8 billion parameter rectified flow transformer
https://huggingface.co/ostris/Flex.1-alpha
Flex.1 started as the FLUX.1-schnell-training-adapter to make training LoRAs on FLUX.1-schnell possible.
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Generative Detail Enhancement for Physically Based Materials
https://arxiv.org/html/2502.13994v1
https://arxiv.org/pdf/2502.13994
A tool for enhancing the detail of physically based materials using an off-the-shelf diffusion model and inverse rendering.
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Martin Gent – Comparing current video AI models
https://www.linkedin.com/posts/martingent_imagineapp-veo2-kling-activity-7298979787962806272-n0Sn
🔹 𝗩𝗲𝗼 2 – After the legendary prompt adherence of Veo 2 T2V, I have to say I2V is a little disappointing, especially when it comes to camera moves. You often get those Sora-like jump-cuts too which can be annoying.
🔹 𝗞𝗹𝗶𝗻𝗴 1.6 Pro – Still the one to beat for I2V, both for image quality and prompt adherence. It’s also a lot cheaper than Veo 2. Generations can be slow, but are usually worth the wait.
🔹 𝗥𝘂𝗻𝘄𝗮𝘆 Gen 3 – Useful for certain shots, but overdue an update. The worst performer here by some margin. Bring on Gen 4!
🔹 𝗟𝘂𝗺𝗮 Ray 2 – I love the energy and inventiveness Ray 2 brings, but those came with some image quality issues. I want to test more with this model though for sure.
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RigAnything – Template-Free Autoregressive Rigging for Diverse 3D Assets
https://www.liuisabella.com/RigAnything
RigAnything was developed through a collaboration between UC San Diego, Adobe Research, and Hillbot Inc. It addresses one of 3D animation’s most persistent challenges: automatic rigging.
- Template-Free Autoregressive Rigging. A transformer-based model that sequentially generates skeletons without predefined templates, enabling automatic rigging across diverse 3D assets through probabilistic joint prediction and skinning weight assignment.
- Support Arbitrary Input Pose. Generates high-quality skeletons for shapes in any pose through online joint pose augmentation during training, eliminating the common rest-pose requirement of existing methods and enabling broader real-world applications.
- Fast Rigging Speed. Achieves 20x faster performance than existing template-based methods, completing rigging in under 2 seconds per shape.
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Skywork SkyReels – All-in-one open source AI video creation based on Hynyuan
https://github.com/SkyworkAI/SkyReels-V1
All-in-one AI platform for video creation, including voiceover, lipsync, SFX, and editing. One click turn text to video & image to video. Turns idea into stunning video in minutes. Check Pricing Details. Start For Free. All-In-One Platform.
SkyReels-V1 is purpose-built for AI short video production based on Hynyuan. It achieves cinematic-grade micro-expression performances with 33 nuanced facial expressions and 400+ natural body movements that can be freely combined. The model integrates film-quality lighting aesthetics, generating visually stunning compositions and textures through text-to-video or image-to-video conversion – outperforming all existing open-source models across key metrics.
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Shanhai based StepFun – Open source Step-Video-T2V
https://huggingface.co/stepfun-ai/stepvideo-t2v
The model generates videos up to 204 frames, using a high-compression Video-VAE (16×16 spatial, 8x temporal). It processes English and Chinese prompts via bilingual text encoders. A 3D full-attention DiT, trained with Flow Matching, denoises latent frames conditioned on text and timesteps. A video-based DPO further reduces artifacts, enhancing realism and smoothness.
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InvokeAI Got a Copyright for an Image Made Entirely With AI. Here’s How
The image, called A Single Piece of American Cheese, was created using Invoke’s AI editing platform.
In a side by side look, you can see how the original (left, screenshotted from the time lapse creation video) was edited to become the final image (right).
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HumanDiT – Pose-Guided Diffusion Transformer for Long-form Human Motion Video Generation
https://agnjason.github.io/HumanDiT-page
By inputting a single character image and template pose video, our method can generate vocal avatar videos featuring not only pose-accurate rendering but also realistic body shapes.
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DynVFX – Augmenting Real Videoswith Dynamic Content
Given an input video and a simple user-provided text instruction describing the desired content, our method synthesizes dynamic objects or complex scene effects that naturally interact with the existing scene over time. The position, appearance, and motion of the new content are seamlessly integrated into the original footage while accounting for camera motion, occlusions, and interactions with other dynamic objects in the scene, resulting in a cohesive and realistic output video.
https://dynvfx.github.io/sm/index.html
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ByteDance OmniHuman-1
https://omnihuman-lab.github.io
They propose an end-to-end multimodality-conditioned human video generation framework named OmniHuman, which can generate human videos based on a single human image and motion signals (e.g., audio only, video only, or a combination of audio and video). In OmniHuman, we introduce a multimodality motion conditioning mixed training strategy, allowing the model to benefit from data scaling up of mixed conditioning. This overcomes the issue that previous end-to-end approaches faced due to the scarcity of high-quality data. OmniHuman significantly outperforms existing methods, generating extremely realistic human videos based on weak signal inputs, especially audio. It supports image inputs of any aspect ratio, whether they are portraits, half-body, or full-body images, delivering more lifelike and high-quality results across various scenarios.
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General OCR Theory – Towards OCR-2.0 via a Unified End-to-end Model – HF Transformers implementation
https://huggingface.co/stepfun-ai/GOT-OCR-2.0-hf
GOT-OCR2 works on a wide range of tasks, including plain document OCR, scene text OCR, formatted document OCR, and even OCR for tables, charts, mathematical formulas, geometric shapes, molecular formulas and sheet music.
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Arminas Valunas – “Coca-Cola: Wherever you are.”
Arminas created this using Juggernaut Xl model and QR Code Monster SDXL ControlNet.
His pipeline:
Static Images – Forge UI.
Upscaled with Leonardo AI universal upscaler.
Animated with Runway ML and Minimax.
Video upscale – Topaz Video AI.
Composited in Adobe Premiere.
Juggernaut Xl download here:
https://civitai.com/models/133005/juggernaut-xl
QR Code Monster SDXL:
https://civitai.com/models/197247?modelVersionId=221829 -
OpenAI releases o3-mini
https://openai.com/index/openai-o3-mini
OpenAI o3-mini is our first small reasoning model that supports highly requested developer features including function calling(opens in a new window), Structured Outputs(opens in a new window), and developer messages(opens in a new window), making it production-ready out of the gate.
o3-mini does not support vision capabilities, so developers should continue using OpenAI o1 for visual reasoning tasks.
ChatGPT Plus, Team, and Pro users can access OpenAI o3-mini starting today, with Enterprise access coming in February. o3-mini will replace OpenAI o1-mini in the model picker, offering higher rate limits and lower latency, making it a compelling choice for coding, STEM, and logical problem-solving tasks.
As part of this upgrade, we’re tripling the rate limit for Plus and Team users from 50 messages per day with o1-mini to 150 messages per day with o3-mini.Starting today, free plan users can also try OpenAI o3-mini by selecting ‘Reason’ in the message composer or by regenerating a response. This marks the first time a reasoning model has been made available to free users in ChatGPT.
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Running DeepSeek R1 Locally Due To Security Issues
DeepSeek Gets an ‘F’ in Safety From Researchers https://gizmodo.com/deepseek-gets-an-f-in-safety-from-researchers-2000558645
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