Engineers spent 90% of time on data prep. New pipelines flipped that to 90% modeling and cut tuning from 7 days to 1 hour.
A generative AI company building advanced voice models and deepfake detection tools for banking and law enforcement, dealing with datasets that ballooned to over 60 terabytes.
Engineers spent 90% of their time on manual data preparation and file transfers rather than model building, leaving high-performance accelerators...
“Google Cloud was the natural fit to modernize infrastructure with AI-optimized tools and architecture.”
Generative AI platform for voice cloning, text-to-speech, and deepfake detection.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Resemble AI's Voice model training is part of this use case:
Related implementations across industries and use cases
Processing 2T tokens on CPUs took days. GPU acceleration cut prep to hours, unlocking a 5% accuracy gain.
Voice integration demanded 400 lines of code. A pre-built framework cuts that to 40, enabling rapid agent deployment.
Processing test batches dragged for 30 hours. Vertex AI now runs the pipeline 23x faster, querying billions of nature images in seconds.
Processing 2T tokens on CPUs took days. GPU acceleration cut prep to hours, unlocking a 5% accuracy gain.
Fragile data pipelines bottlenecked engineers. Now, built-in workflows let teams ship internal AI tools without managing infrastructure.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Engineers spent 90% of time on data prep. New pipelines flipped that to 90% modeling and cut tuning from 7 days to 1 hour.
A generative AI company building advanced voice models and deepfake detection tools for banking and law enforcement, dealing with datasets that ballooned to over 60 terabytes.
Engineers spent 90% of their time on manual data preparation and file transfers rather than model building, leaving high-performance accelerators...
“Google Cloud was the natural fit to modernize infrastructure with AI-optimized tools and architecture.”
Generative AI platform for voice cloning, text-to-speech, and deepfake detection.
Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.
Resemble AI's Voice model training is part of this use case:
Related implementations across industries and use cases
Processing 2T tokens on CPUs took days. GPU acceleration cut prep to hours, unlocking a 5% accuracy gain.
Voice integration demanded 400 lines of code. A pre-built framework cuts that to 40, enabling rapid agent deployment.
Processing test batches dragged for 30 hours. Vertex AI now runs the pipeline 23x faster, querying billions of nature images in seconds.
Processing 2T tokens on CPUs took days. GPU acceleration cut prep to hours, unlocking a 5% accuracy gain.
Fragile data pipelines bottlenecked engineers. Now, built-in workflows let teams ship internal AI tools without managing infrastructure.
Accountants manually scoured mailboxes to assemble 15 subsidiary workbooks. Now, staff-built AI agents pull invoice data for instant review.
Surging calls caused long holds and overtime. A 24/7 AI voice agent handles routine payroll, freeing 700 HR partners for advisory work.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.