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1982: Nancy Burson's Composite Portraits

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1982: Nancy Burson's Composite Portraits

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Artist Nancy Burson created the first computer-generated composite portraits, developing the 'Human Race Machine' and aging software. Her groundbreaking work laid the foundation for morphing technology and facial recognition software used today in everything from social media filters to law enforcement.

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The release of the Dycam Model 1, the first commercially available digital camera, marked a crucial shift toward digital image processing. This development would later prove essential for AI image analysis and manipulation.

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Paul Viola and Michael Jones developed their revolutionary face detection framework, which became the foundation for modern facial recognition systems and AI-powered photography features.

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Instagram's launch marked a new era in digital photography, introducing AI-powered filters and image enhancement tools to the masses, forever changing how we process and share photos.

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2014: Generative Adversarial Networks (GANs)

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2014: Generative Adversarial Networks (GANs)

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Ian Goodfellow and colleagues introduced GANs, revolutionary AI systems that can generate and modify photographic images, leading to applications like DeepFake technology and AI art generation.

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Google released Deep Dream, an AI system that processes images to create dreamlike hallucinogenic effects, demonstrating AI's creative potential in image manipulation and artistic expression.

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NVIDIA released StyleGAN, a significant improvement in GAN technology that could generate incredibly realistic human faces, showing how AI could create photorealistic images from scratch.

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OpenAI introduced DALL-E, an AI system capable of creating unique images from text descriptions, revolutionizing the relationship between language and visual creation.

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Stability AI released Stable Diffusion, an open-source AI image generation model that democratized AI art creation and sparked discussions about the future of photography and artistic creation.

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Modern smartphones now incorporate advanced AI systems for computational photography, featuring capabilities like portrait mode, night sight, and automatic scene optimization, making AI an integral part of everyday photography.

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When it comes to anything AI related it hurts my soul. While I understand technological advances are going to happen I question at what cost? AI data bases pull a great deal of resources and they need fresh clean water as a part of their cooling mechanism they cannot use recycled water so how much resources, carbon footprint are we using and leaving by utilizing this process? I understand that my cell phone for instance has a form of AI built into the camera settings that if I choose to use it I am able.