Partnerships

Save on your pass

Call to action
Your text goes here. Insert your content, thoughts, or information in this space.
Button

Back to speakers

Chris
Alexiuk
Product Research Engineer, Deep Learning
NVIDIA
Chris is a Product Research Engineer at NVIDIA with a deep passion for machine learning, generative AI, and LLMs. He’s as excited about sharing knowledge as he is about pushing the boundaries of what’s possible.
Button
20 November 2025 11:30 - 12:00
Panel | Building faster, more efficient agents - Accelerating adoption across your enterprise
If your agents can’t keep up, your adoption roadmap stalls. From latency spikes to scaling limits, performance bottlenecks can quickly turn promising prototypes into costly failures. In this panel, engineering leaders unpack the technical strategies for squeezing every drop of efficiency out of autonomous agents and show how speed gains directly translate into wider enterprise adoption and operational value. Expect practical insights on building for real-time decision-making, optimizing resource allocation, and integrating seamlessly across complex enterprise environments. Key takeaways: → Techniques for reducing latency and improving real-time responsiveness. → Optimizing resource allocation without compromising agent performance. → Architectures that scale efficiently across diverse workloads. → How performance improvements accelerate enterprise adoption.