Mago
Video style transfer
Memory limits blocked pro-grade video. Using A100 GPUs and Gemini, Mago cut render times by 40% and boosted resolution by 60%.
- Stylization success rate increased from 71% to 93%
Processing test batches dragged for 30 hours. Vertex AI now runs the pipeline 23x faster, querying billions of nature images in seconds.
A media art studio preparing a permanent exhibition powered by an AI model trained on one of the world's largest datasets of the natural world.
Processing the massive image archive was prohibitively slow, with test batches taking 30 hours to complete. Previous captioning tools produced only...
“With Unsupervised, we proved that a machine could dream. Now, with the Large Nature Model, we are teaching it to understand. This transition — from abstract hallucinations to scientific accuracy — is only possible because of the speed and intelligence of this new infrastructure. It allows us to close the gap between human vision and machine capability, creating a partnership that is finally free from limitations.”
Media arts and design studio specializing in AI-driven architectural installations.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Supported the studio in building its new data processing technique on Google Cloud.
Related implementations across industries and use cases
Memory limits blocked pro-grade video. Using A100 GPUs and Gemini, Mago cut render times by 40% and boosted resolution by 60%.
Models missed plot twists hidden in dialogue. Fusing text and video data now automates narrative summaries in four languages.
Captioning 10,000 images consumed 333 hours of human effort. AI now completes the workflow in under 15 hours.
Models missed plot twists hidden in dialogue. Fusing text and video data now automates narrative summaries in four languages.
Captioning 10,000 images consumed 333 hours of human effort. AI now completes the workflow in under 15 hours.
Manually illustrating vintage assets would have tripled production time. Now, a 3-person team uses AI to generate and animate the visuals.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Processing test batches dragged for 30 hours. Vertex AI now runs the pipeline 23x faster, querying billions of nature images in seconds.
A media art studio preparing a permanent exhibition powered by an AI model trained on one of the world's largest datasets of the natural world.
Processing the massive image archive was prohibitively slow, with test batches taking 30 hours to complete. Previous captioning tools produced only...
“With Unsupervised, we proved that a machine could dream. Now, with the Large Nature Model, we are teaching it to understand. This transition — from abstract hallucinations to scientific accuracy — is only possible because of the speed and intelligence of this new infrastructure. It allows us to close the gap between human vision and machine capability, creating a partnership that is finally free from limitations.”
Media arts and design studio specializing in AI-driven architectural installations.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Supported the studio in building its new data processing technique on Google Cloud.
Related implementations across industries and use cases
Memory limits blocked pro-grade video. Using A100 GPUs and Gemini, Mago cut render times by 40% and boosted resolution by 60%.
Models missed plot twists hidden in dialogue. Fusing text and video data now automates narrative summaries in four languages.
Captioning 10,000 images consumed 333 hours of human effort. AI now completes the workflow in under 15 hours.
Models missed plot twists hidden in dialogue. Fusing text and video data now automates narrative summaries in four languages.
Captioning 10,000 images consumed 333 hours of human effort. AI now completes the workflow in under 15 hours.
Manually illustrating vintage assets would have tripled production time. Now, a 3-person team uses AI to generate and animate the visuals.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.