Generative AI for Creative Content
Empower your creative artist and take your content creation to the next level with generative ai tools powered by Amazon SageMaker
Overview
Generative AI is transforming how content is created and consumed. Media and Entertainment companies face an insatiable demand for personalized and engaging content to serve their audiences across channels. Using models like Stable Diffusion where images and video can be generated with just a simple text prompt allows businesses to automate content creation at scale. This helps creators improve efficiency in meeting content demand by automating repetitive tasks, optimizing campaigns, and providing a hyper-personalized experience for the end customer. The business value is clear through increased content output, cost savings, improved personalization, and enhanced customer experience. Whether generating social media posts, product photos, marketing emails or even footage for a film, Generative AI is poised to revolutionize content creation in M&E. However, generative AI models that simply generate content from scratch are not enough. Raw content generation lacks efficiency and usefulness for most practical applications. Content creators need fine-grained control over style, layout, and other attributes to produce high-quality, tailored content. In many cases, companies already have existing content assets that need to be modified, remixed, and refined. Generative AI will be far more appealing if it can satisfy these additional capabilities.
Inpainting
Magic eraser uses Segment Anything Model (SAM) from Meta Research to create a segmentation mask of an object simply by clicking on the image. Once the object has been segmented, it will use a second model, Resolution-robust Large Mask Inpainting with Fourier Convolutions (LaMa), to “erase” the object. What really happened is that removed object is filled with a seamless and natural-looking background that blends in perfectly with the surrounding environment.
Outpainting
Magic fill/replace uses the same segmentation model to delect the object of interest on the Image. Step 2 is replaced with Stable Diffusion inpaint model. With this new model, the tool can generate any content in the segmented areas based on text prompt. This enables the ability to 1) remove anything when no text was supplied, 2) fill anything given text, and 3) replace the background when we flip the mask color.
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Testimonials
Engineering Manager
Alice Howard
AIGreenSolutions is a trailblazer in the realm of emerging solutions and AI use cases. As a forward-thinking professional constantly seeking innovative approaches to enhance efficiency and productivity.
Interior Designer
Nathan Marshall
From the very onset, AIGreenSolutions distinguished themselves with their commitment to staying on the cutting edge of technology. Our team of experts exhibited a profound understanding of emerging solutions and artificial intelligence, seamlessly integrating these advancements into practical use cases that addressed your unique business challenges.
Architect
Ema Romero
Equally commendable is AIGreensolution's emphasis on transparency and collaboration. Throughout our engagement, we maintained open lines of communication, keeping you informed at every stage of the process. This collaborative spirit instilled trust and confidence in our capabilities, making the entire journey smooth and enjoyable.
Manager
Ann Smith
What sets AIGreenSolution apart is its unwavering commitment to ongoing innovation. In an ever-evolving technological landscape, we remain at the forefront, continuously exploring new possibilities and refining solutions to stay ahead of the curve. This proactive approach instills confidence and assures clients that we are not just investing in today's solutions but in the promise of tomorrow's advancements.
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we offer comprehensive, custom services across the artificial intelligence spectrum.
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