🤔 The video raises the question of whether SDXL has failed.
🔍 SDXL's development and performance are crucial for the future of image and video AI.
🎨 SDXL promises better artwork, tools for complex composition, and simpler language input.
📢 SDXL was not as much of a leap as expected, being on par or slightly better than community-driven models.
💻 SDXL's hardware requirements and upscaling process make it slow and unsuitable for most users.
😔 Some users found SDXL's release disappointing, hoping for more creativity.
⭐️ SDXL falls short of expectations and feels like a slightly improved version of SD 1.5.
🎨 Community models and other software options offer more flexibility and artistic authenticity compared to SDXL.
🌟 Mid Journey stands out for its warm artistic feel and application of artistic concepts in creating images.
📊 The SDXL models are not as good as the SD 1.5 models due to differences in their base, resulting in a less natural aesthetic.
💻 SDXL requires a good GPU, limiting its accessibility for many users.
🔬 Improvements in training the SDXL models could lead to better and more consistent results.
🌐 There is a desire to have SDXL models with lower minimum resolution to increase accessibility.
✅ The acceptance and usage of SDXL within the community is an important factor to consider.
📈 The SDXL model has significantly fewer downloads compared to other popular AI models.
⏱️ It is important to consider the time and iterations that have passed for the SDXL model.
🖼️ The video presents a comparison between an SD 1.5 image and an SDXL image.
🔍 The detailed improvement in the SDXL image compared to SD 1.5 is questionable.
🎨 The authenticity and ease of training different artistic styles are more important factors for AI usage in images and videos.
⚙️ The ability to control the content and compatibility of the model with hardware are crucial considerations.
📸 The SDXL model has limitations in terms of image quality and results.
⚙️ SD 1.5 offers interesting tricks for image enhancement and upscaling.
🗣️ Community feedback is important in training future open-source models and improving user interaction.
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