How AI-Powered Holograms Are Reimagining Fan Experiences at the Big Game - Ep. 288
Episode
38 min
Read time
3 min
Topics
Productivity, Relationships, Startups
AI-Generated Summary
Key Takeaways
- ✓Physical retail gap: 80% of US shopping still occurs in physical stores, not online, creating a massive opportunity for AI agents to bridge the digital-physical divide. Retailers lack data on in-store customer needs and behavior, while brands cannot provide the same intelligent, personalized assistance available through digital chatbots. Full-size holographic agents address this by offering real-time inventory checks, product recommendations, and seamless checkout experiences without requiring customers to wait for human staff or resort to mobile searches.
- ✓Technical performance requirements: Mission-critical AI agents require both efficiency and accuracy for real-time interactions. LiveX AI achieves six times faster average token speed using NVIDIA NIM microservices compared to traditional inference frameworks. This speed improvement enables multi-step AI agent workflows where each step involves language or vision models, allowing six interaction steps in the time competitors complete one. The system runs on-premise using two NVIDIA RTX 6000 GPUs with Blackwell architecture for simultaneous visual rendering and large model inference.
- ✓Super Bowl deployment scale: LiveX AI operates over 20 holographic AI agent activations across Super Bowl week 2026, spanning airports, fan zones, city halls, and concert venues. The agents, named Lyra, handle wayfinding, event information, emergency protocols, and crowd management for millions of fans. The system scales using both on-premise RTX workstations and cloud deployments to handle peak volumes, then scales down during lower traffic periods. This represents the first deployment of 4K high-quality, full-size holographic agents at this scale.
- ✓Production stack architecture: The system combines multiple model types including custom-trained models and third-party language models for languages the team cannot evaluate internally. LiveX AI uses NVIDIA Triton, TensorRT, NeMo, and Nematron across the stack, with models deployed on Kubernetes at Google Cloud for auto-scaling capabilities. The team optimizes at the kernel level using CUDA to maximize computational efficiency. On-premise deployment proves essential for crowded indoor events like NRF with 40,000 attendees where internet connectivity becomes unreliable.
- ✓Athlete-fan relationship evolution: Human-like AI agents enable celebrities and athletes to maintain authentic connections with fans at scale without physical presence. Sports teams prioritize fan experience above all else, seeking ways to provide lifetime memorable moments through interactions with players and team history. AI agents can represent individual athletes, answer questions about teams and leagues, facilitate celebration selfies with virtual characters, and create personalized experiences that previously required direct human interaction, fundamentally changing how fans engage with sports properties.
What It Covers
Jia Li, cofounder and chief AI officer of LiveX AI, explains how full-size holographic AI agents transform fan experiences at Super Bowl 2026 and retail environments. The company deploys human-like holograms running on NVIDIA RTX 6000 GPUs to provide real-time wayfinding, customer service, and personalized interactions across 20 activations during Super Bowl week.
Key Questions Answered
- •Physical retail gap: 80% of US shopping still occurs in physical stores, not online, creating a massive opportunity for AI agents to bridge the digital-physical divide. Retailers lack data on in-store customer needs and behavior, while brands cannot provide the same intelligent, personalized assistance available through digital chatbots. Full-size holographic agents address this by offering real-time inventory checks, product recommendations, and seamless checkout experiences without requiring customers to wait for human staff or resort to mobile searches.
- •Technical performance requirements: Mission-critical AI agents require both efficiency and accuracy for real-time interactions. LiveX AI achieves six times faster average token speed using NVIDIA NIM microservices compared to traditional inference frameworks. This speed improvement enables multi-step AI agent workflows where each step involves language or vision models, allowing six interaction steps in the time competitors complete one. The system runs on-premise using two NVIDIA RTX 6000 GPUs with Blackwell architecture for simultaneous visual rendering and large model inference.
- •Super Bowl deployment scale: LiveX AI operates over 20 holographic AI agent activations across Super Bowl week 2026, spanning airports, fan zones, city halls, and concert venues. The agents, named Lyra, handle wayfinding, event information, emergency protocols, and crowd management for millions of fans. The system scales using both on-premise RTX workstations and cloud deployments to handle peak volumes, then scales down during lower traffic periods. This represents the first deployment of 4K high-quality, full-size holographic agents at this scale.
- •Production stack architecture: The system combines multiple model types including custom-trained models and third-party language models for languages the team cannot evaluate internally. LiveX AI uses NVIDIA Triton, TensorRT, NeMo, and Nematron across the stack, with models deployed on Kubernetes at Google Cloud for auto-scaling capabilities. The team optimizes at the kernel level using CUDA to maximize computational efficiency. On-premise deployment proves essential for crowded indoor events like NRF with 40,000 attendees where internet connectivity becomes unreliable.
- •Athlete-fan relationship evolution: Human-like AI agents enable celebrities and athletes to maintain authentic connections with fans at scale without physical presence. Sports teams prioritize fan experience above all else, seeking ways to provide lifetime memorable moments through interactions with players and team history. AI agents can represent individual athletes, answer questions about teams and leagues, facilitate celebration selfies with virtual characters, and create personalized experiences that previously required direct human interaction, fundamentally changing how fans engage with sports properties.
Notable Moment
Li describes how retail customers already pull out phones to use chatbots when they cannot find products in stores, but those chatbots do not represent the brand, lack current inventory data, and often provide outdated information. This behavior reveals customers already prefer AI assistance over waiting for human staff, creating immediate demand for brand-controlled holographic agents with accurate real-time information.
Episode Transcript
Welcome to the NVIDIA AI podcast. I'm Noah Kravitz. Before we get started, a quick note to let you know that registration is open for GTC twenty twenty six in San Jose, California. NVIDIA GTC is the premier global AI conference where developers, researchers, and business leaders come together to explore the next wave of AI innovation. Visit nvidia.com/gtc for more information and to register. Jia Li is with us today. Jia is cofounder, president, and chief AI officer of LiveX AI, which builds human like AI agents, including one that fans attending Super Bowl week this year are interacting with, as we'll talk about in just a moment. Jia, welcome to the AI podcast, and thanks for taking the time to be with us. Thank you, Noah. This is a a great pleasure to discuss AI and AI agent and physical AI. Absolutely. I'm really excited to hear more about what LabX is working on. So let's get right into it. Maybe to start, can you tell us a little bit about your own background and your role at LabX AI? Thank you. Hi, everyone. I'm a AI technologist in the AI field since the not so popular days of AI. And, really exciting to see how everything has been evolving and myself having in small companies, like Snap when they were tiny, a hundred, two hundred people, and saw the company grow to over 3,000 people. I was leading AI and AR efforts there. And, also big company, like Google, I built, and cofounded the Google Cloud AI organization and, oversaw the products and full stack engineering there. And, obviously, I had the opportunity to, work with different industries, to see the real world impact. And, since then, I got super excited about the real world impact of AI and taught at Stanford. The latest, is, teaching the future of AI agents, which is very core to the future of AI interaction. And, of course, building my my own company and, LevX AI, as Noah introduced, is building the human like AI agents. And specifically, everybody has been talking about AI agents and has been talking about the physical AI. And, of course, digital world of AI is already fairly prominent at the moment, and we at Levesque AI really want to bridge the digital world and the physical world and bringing everyone the face of AI for all the b to c companies who want to provide a smooth and human like interaction with their users and customers. So I think I mispronounced I I apologize. It's LiveX AI, not LiveX. I think that's a very good question because, in a way, like, we would love to follow how the users and how people will pronounce our Okay. Misname. So, originally, the company started, with a vision of, hey. We want to make a positive impact to everyday life and everyday living. So, basically, that's, live act. Right. We want to improve the living experience, leveraging AI. …
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Books, tools, and gear mentioned in this episode
SignalCast may earn commission on purchases via these links. As an Amazon Associate, SignalCast earns from qualifying purchases.
Tools
by NVIDIA
“LiveX AI uses NVIDIA Triton, TensorRT, NeMo, and Nematron across the stack, with models deployed on Kubernetes at Google Cloud for auto-scaling capabilities.”
by NVIDIA
“LiveX AI uses NVIDIA Triton, TensorRT, NeMo, and Nematron across the stack, with models deployed on Kubernetes at Google Cloud for auto-scaling capabilities.”
by NVIDIA
“LiveX AI uses NVIDIA Triton, TensorRT, NeMo, and Nematron across the stack, with models deployed on Kubernetes at Google Cloud for auto-scaling capabilities.”
by NVIDIA
“LiveX AI achieves six times faster average token speed using NVIDIA NIM microservices compared to traditional inference frameworks.”
“LiveX AI uses NVIDIA Triton, TensorRT, NeMo, and Nematron across the stack, with models deployed on Kubernetes at Google Cloud for auto-scaling capabilities.”
by Google
“LiveX AI uses NVIDIA Triton, TensorRT, NeMo, and Nematron across the stack, with models deployed on Kubernetes at Google Cloud for auto-scaling capabilities.”
by NVIDIA
“The team optimizes at the kernel level using CUDA to maximize computational efficiency.”
by NVIDIA
“LiveX AI uses NVIDIA Triton, TensorRT, NeMo, and Nematron across the stack, with models deployed on Kubernetes at Google Cloud for auto-scaling capabilities.”
Gear
by NVIDIA
“The company deploys human-like holograms running on NVIDIA RTX 6000 GPUs to provide real-time wayfinding, customer service, and personalized interactions across 20 activations during Super Bowl week.”
by NVIDIA
“The system runs on-premise using two NVIDIA RTX 6000 GPUs with Blackwell architecture for simultaneous visual rendering and large model inference.”
other
company
- LiveX AIBy guest
“Jia Li, cofounder and chief AI officer of LiveX AI, explains how full-size holographic AI agents transform fan experiences at Super Bowl 2026 and retail environments.”
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