Overview of event
AREA Research Webinar presented by Sruti Srinidh – PhD Student, Carnegie Mellon University & Christine Perey – Chair, AREA Research Committee.
Agenda
In this AREA Research webinar, we will describe an approach to produce AR experiences without manual intervention, specifically in scenarios where the AR objects provide guidance to the user about something in the physical world. We propose a cognitive assistant system that can understand, reason about and respond to the physical world in AR, allowing for in-context assistance, especially for step-by-step tasks.
We explore the system architectural needs, application requirements as well as the usability of such a technology, specifically in assisting with instruction-oriented use cases. Though LLMs are new and are still limited by accuracy, results have shown an improvement in response time of the AR assistant and only a small increase in task completion time
The system we will present explores the various challenges in building a platform that integrates LLMs with AR devices and examines the challenges we still have left to solve.
Who Should Attend
The webinar is tailored to AR project managers, architects, developers, and platform providers. Attendees will gain insights about:
- Workplace conditions most likely to produce the most reliable results using the approach, and which conditions could lead to errors.
- How AR platform providers would go about integrating the new LLM-assisted approach into commercial authoring platform.
- Clear benefits and limitations of one specific Multimodal LLM over others in different circumstances.