Scaling Smartly: Optimizing AI Infrastructure and Operations for Growth
Scaling AI is complex, but essential for long-term success. This track provides technical guidance on optimizing infrastructure, algorithms, and operations to efficiently scale AI.
Sessions will cover choosing hardware, software stacks, ML pipelines, and workflows to manage growing data volumes, model complexity, and user loads. Attendees will gain insider tips for scaling without compromising quality or control.
The track features scaling stories across industries like autonomous systems, personalization algorithms, cashierless stores, and more. Architects will gain practical takeaways to plan their growth roadmaps.
Get Involved – Call for Participation
We welcome AI architects and engineers to share scaling insights by moderating, speaking, or contributing. Help shape understanding by showcasing optimizations for data, infrastructure, pipelines, and governance.
- Distributed Training Techniques
- MLOps & DevOps Integration
- Performance Benchmarking
- Cost Optimization
- Monitoring & Observability
Share Your Expertise
Technical leaders who have scaled AI systems are needed to lead sessions sharing their experiences and stack choices. Help attendees understand tradeoffs and create scaling plans tailored to their needs.
Learn & Connect
Sessions emphasize actionable takeaways through scaling stories, interactive discussions, and activities. Architects will gain expertise to evaluate options, prove value, and scale AI smoothly.
Get Updates & Access Recordings
Sign up below to receive email updates as this track develops. Get notified of new sessions, community activities, and ways to participate. Members get exclusive access to session recordings, templates, and resources.