Keyword rules couldn't read context at 2M videos/day. Vector embeddings cut validation from 30s to 0.011s per video.
A brand safety platform for global digital video serving 20 of Korea's largest firms and 10 Fortune 500 companies, processing 2 million videos daily, the equivalent of 60 years of content every 24 hours.
Fragmented, function-specific pipelines and rule-based keyword detection couldn't capture semantic context at video scale, creating high latency and...
AI platform for video brand safety and context-aware ad placement.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Pyler's Video brand safety 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.
Processing trillion-token datasets took months. A native vector engine cut deduplication costs 5x and doubled processing speed.
Captioning 10,000 images consumed 333 hours of human effort. AI now completes the workflow in under 15 hours.
Keyword filters missed toxic sarcasm. Analysts now deploy GenAI safety models via SQL in one day, scanning millions of posts instantly.
Teams manually reviewed tens of thousands of creatives image-by-image. Now, AI vision models verify policy compliance instantly.
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.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Keyword rules couldn't read context at 2M videos/day. Vector embeddings cut validation from 30s to 0.011s per video.
A brand safety platform for global digital video serving 20 of Korea's largest firms and 10 Fortune 500 companies, processing 2 million videos daily, the equivalent of 60 years of content every 24 hours.
Fragmented, function-specific pipelines and rule-based keyword detection couldn't capture semantic context at video scale, creating high latency and...
AI platform for video brand safety and context-aware ad placement.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Pyler's Video brand safety 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.
Processing trillion-token datasets took months. A native vector engine cut deduplication costs 5x and doubled processing speed.
Captioning 10,000 images consumed 333 hours of human effort. AI now completes the workflow in under 15 hours.
Keyword filters missed toxic sarcasm. Analysts now deploy GenAI safety models via SQL in one day, scanning millions of posts instantly.
Teams manually reviewed tens of thousands of creatives image-by-image. Now, AI vision models verify policy compliance instantly.
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.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.