COMPOSITION
DESIGN
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Kristina Kashtanova – “This is how GPT-4 sees and hears itself”Read more: Kristina Kashtanova – “This is how GPT-4 sees and hears itself”“I used GPT-4 to describe itself. Then I used its description to generate an image, a video based on this image and a soundtrack. Tools I used: GPT-4, Midjourney, Kaiber AI, Mubert, RunwayML This is the description I used that GPT-4 had of itself as a prompt to text-to-image, image-to-video, and text-to-music. I put the video and sound together in RunwayML. GPT-4 described itself as: “Imagine a sleek, metallic sphere with a smooth surface, representing the vast knowledge contained within the model. The sphere emits a soft, pulsating glow that shifts between various colors, symbolizing the dynamic nature of the AI as it processes information and generates responses. The sphere appears to float in a digital environment, surrounded by streams of data and code, reflecting the complex algorithms and computing power behind the AI” 
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IM3 Stained glassRead more: IM3 Stained glasshttp://imgur.com/a/GXUun#hO6wzrs Some people are asking how… here is a brief explanation on how I did it with photos…. 
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COLOR
LIGHTING
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Beeble Switchlight’s Plugin for Foundry NukeRead more: Beeble Switchlight’s Plugin for Foundry Nukehttps://www.cutout.pro/learn/beeble-switchlight/ https://www.switchlight-api.beeble.ai/pricing https://www.switchlight-api.beeble.ai https://github.com/beeble-ai/SwitchLight-Studio https://beeble.ai/terms-of-use https://www.switchlight-api.beeble.ai/docs 
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Arto T. – A workflow for creating photorealistic, equirectangular 360° panoramas in ComfyUI using FluxRead more: Arto T. – A workflow for creating photorealistic, equirectangular 360° panoramas in ComfyUI using Fluxhttps://civitai.com/models/735980/flux-equirectangular-360-panorama https://civitai.com/models/745010?modelVersionId=833115 The trigger phrase is “equirectangular 360 degree panorama”. I would avoid saying “spherical projection” since that tends to result in non-equirectangular spherical images. Image resolution should always be a 2:1 aspect ratio. 1024 x 512 or 1408 x 704 work quite well and were used in the training data. 2048 x 1024 also works. I suggest using a weight of 0.5 – 1.5. If you are having issues with the image generating too flat instead of having the necessary spherical distortion, try increasing the weight above 1, though this could negatively impact small details of the image. For Flux guidance, I recommend a value of about 2.5 for realistic scenes. 8-bit output at the moment   
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