Skyrim.AI
3D video production
Processing 24 8K cameras choked CPUs. A direct-to-GPU pipeline eliminated specialized hardware, enabling real-time 3D sports capture.
- Development time reduced by 1 year
RF congestion and cloud lag choked live feeds. Edge AI now identifies jockeys and prioritizes bandwidth for active shots instantly.
A live sports broadcaster streams over 70,000 horse races annually from 130 racetracks across three linear television networks.
Traditional wireless setups suffered from RF congestion in crowded venues, while cloud alternatives introduced unacceptable latency for real-time...
Verizon's Live video production is part of this use case:
Telecommunications provider of wireless, internet, and television services for consumers.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Used its LiveVision solution to deploy an AI model for real-time object detection on racing footage
Related implementations across industries and use cases
Processing 24 8K cameras choked CPUs. A direct-to-GPU pipeline eliminated specialized hardware, enabling real-time 3D sports capture.
Producers manually matched timestamps. Now, teams edit transcripts directly, and AI generates social clips without video skills.
A one-second delay was too slow for live sports. Cloud inference now delivers stats 10x faster, powering 60+ AI initiatives.
Processing 24 8K cameras choked CPUs. A direct-to-GPU pipeline eliminated specialized hardware, enabling real-time 3D sports capture.
Vague feedback on unrecorded streams slowed fixes. AI now diagnoses live issues instantly, lifting user satisfaction 30%.
Security fears fragmented AI usage. Now, clear guardrails and automated Slack nudges empower teams to accelerate design and code reviews.
Manually illustrating vintage assets would have tripled production time. Now, a 3-person team uses AI to generate and animate the visuals.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
RF congestion and cloud lag choked live feeds. Edge AI now identifies jockeys and prioritizes bandwidth for active shots instantly.
A live sports broadcaster streams over 70,000 horse races annually from 130 racetracks across three linear television networks.
Traditional wireless setups suffered from RF congestion in crowded venues, while cloud alternatives introduced unacceptable latency for real-time...
Verizon's Live video production is part of this use case:
Telecommunications provider of wireless, internet, and television services for consumers.
NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.
Used its LiveVision solution to deploy an AI model for real-time object detection on racing footage
Related implementations across industries and use cases
Processing 24 8K cameras choked CPUs. A direct-to-GPU pipeline eliminated specialized hardware, enabling real-time 3D sports capture.
Producers manually matched timestamps. Now, teams edit transcripts directly, and AI generates social clips without video skills.
A one-second delay was too slow for live sports. Cloud inference now delivers stats 10x faster, powering 60+ AI initiatives.
Processing 24 8K cameras choked CPUs. A direct-to-GPU pipeline eliminated specialized hardware, enabling real-time 3D sports capture.
Vague feedback on unrecorded streams slowed fixes. AI now diagnoses live issues instantly, lifting user satisfaction 30%.
Security fears fragmented AI usage. Now, clear guardrails and automated Slack nudges empower teams to accelerate design and code reviews.
Manually illustrating vintage assets would have tripled production time. Now, a 3-person team uses AI to generate and animate the visuals.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.