Designed for AI professionals pushing compute and intelligence to the sources of data, the Edge AI track is a one-stop shop for all things distributed and embedded.
Tackling performance, efficiency, and cost trade-offs at the application, model, and hardware layers, this track is for the pioneers driving the art of small AI forward.
How Will You Benefit?
1. See first-hand how product managers and embedded engineers are infusing devices with AI and take home best-in-class optimization techniques that will help you squeeze the most performance out of your compute resources.
2. Map out how the inference market is developing, and see how realtime AI serving will be delivered to end users across the globe. Benefit from our unique blend of server-focused and edge-focused attendees who have been attending since 2018!
3. Meet the engineers doing the most with the least. Learn where Edge AI delivers bang for its buck, from a brain trust of world-class engineers and developers pushing the boundaries of AI development.
Who Will You Meet?
Agenda Highlights:
- Edge AI Enterprise Use Cases: Real world deployments and results from Edge AI use cases in industries such as manufacturing, healthcare, retail, automotive, and security/surveillance.
- On-Device AI: Deploying multimodal LLMs on devices, trade-offs in accuracy, performance and adaptability in embedded AI…
- Cloud-Edge Infra: The development of the real-time inference market, reducing cost with hybrid computing, integrating edge AI into the IoT.
- Edge Hardware: Balancing performance and efficiency in realtime systems, optimizing memory for embedded AI accelerators, overcoming hardware integration and interoperability challenges…