Facebook: Towards On-Device AI

Aim to accelerate the transition to a world where AI capabilities permeate all devices and sensors, proposals on topics related to efficient on-device AI systems, including, but not limited to the following:

• Extending on-device capabilities for vision, audio, speech, and natural language processing
• Distributing AI capabilities across the whole system stack from data capture at the edge to the cloud instead of performing all the compute in the cloud
• Machine learning techniques to optimize system tasks such as compression, scheduling, and caching
• On-device privacy-preserving learning
• Efficient machine learning models for edge devices
• Dynamic neural networks, such as mixture-of-expert networks
• Platform-aware model optimization
• Efficient hardware accelerator design
• Tools for architecture modeling, design space exploration, and algorithm mapping
• Efficient model execution on edge devices such as scheduling and tiling
• Emerging technologies such as near-sensor, near-memory, and near-storage computing

Funding: $75K.

Please contact Research Authority if planning to submit.

https://research.fb.com/programs/research-awards/proposals/towards-on-device-ai-request-for-proposals/