Posts tagged “Deep Learning”

What it takes to run ML in production at scale - monitoring, versioning, deployment, and all the things that aren't training.

Moving from hand-crafted to learned feature descriptors for VPS - training, deployment, and performance gains.

Bringing synthetic data practices from Magic Leap to Meta - what scales, what doesn't, and new opportunities.

Techniques for transferring knowledge from synthetic to real data, and from one perception task to another.

Advanced techniques for neural network optimization on embedded systems - beyond basic quantization and pruning.

Designing a full-featured hand tracking system for V2 - gesture recognition, extended range, and the training data challenge.

Using extreme variation in synthetic data to bridge the sim-to-real gap - theory, practice, and hard-won lessons.

Deploying neural networks on power-constrained hardware - quantization, pruning, architecture search, and the gap between research and production.

The technical pipeline for real-time hand tracking - depth sensing, segmentation, keypoint detection, and skeleton fitting.