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Source channel @githubtrending · Post #14988 · Jul 23

#python#deep_learning#diffusion#flax#flux#hacktoberfest#image_generation#image2image#image2video#jax#latent_diffusion_models#pytorch#score_based_generative_modeling#stable_diffusion#stable_diffusion_diffusers#text2image#text2video#video2video The Hugging Face Diffusers library is a powerful and easy-to-use tool for generating images, audio, and 3D molecular structures using advanced diffusion models. It offers ready-to-use pretrained models and flexible components like pipelines, schedulers, and model building blocks, allowing you to quickly create or customize your own diffusion-based projects. Installation is simple via pip or conda, and you can generate high-quality outputs with just a few lines of code. This library benefits you by making cutting-edge AI generation accessible, customizable, and efficient, whether you want to run models or train your own[1][2][5]. https://github.com/huggingface/diffusers

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AI & Law

@ai_and_law · Post #602 · 06/27/2025, 07:04 AM

🇺🇸Microsoft Faces Watchdog Pushback on AI Advertising Microsoft’s ambitious marketing of its Copilot AI features has come under scrutiny. The National Advertising Division (NAD) has recommended that the company revise or discontinue certain productivity claims tied to Microsoft 365 Copilot, citing a lack of objective evidence. While Microsoft cited impressive user perception stats—like 70% reporting increased productivity—the NAD found the study insufficient to support hard ROI claims. More than just numbers, the watchdog also flagged the branding itself. With "Copilot" used across multiple tools, including Business Chat, users may not understand what the product can, and cannot, do. NAD advised Microsoft to make material limitations clear and avoid conflating distinct features under a single name. As AI tools enter mainstream business settings, regulatory clarity around marketing promises is becoming non-negotiable. #AI#MicrosoftCopilot#AIAdvertising#AITransparency