harpreet

Call for Speakers! Are you working on robotics research, an open source project or commercial app in the physical AI space? Consider speaking at the upcoming Nov 9 - Buffalo Physical AI Workshop and Meetup! Visit hubs.ly/Q04CnZRT0 to submit your talk. (Select “Nov 9 - Buffalo” in the dropdown.) Event details: hubs.ly/Q04CnYSv0 #PhysicalAI #Robotics #ComputerVision #MachineLearning #FiftyOne

🚀 Introducing Voxel51 3.0 — an end-to-end multimodal platform for physical AI, right in your browser - voxel51.com/blog/voxel51-3-0… We’ve unified search, curation, annotation, and evaluation into a single platform! 🔹 Time-series multimodal support — work seamlessly across sensor streams, video, and more 🔹 Unified annotation — one workflow for all your data types 🔹 Agentic Labeling — VLM-powered labeling that does the heavy lifting for you 🔹 Voxel51 Agent — chains workflows together using 45+ MCP tools, 80+ operators, and 18 skills 🔹 Data provenance — full activity logs, sample edit history, and dataset versioning for complete traceability 🔹 Model-agnostic and free to try. 👉 Get started at app.voxel51.com #Voxel51 #PhysicalAI #MultimodalAI #ComputerVision #AIAgents #DataAnnotation #MachineLearning

Exact-duplicate search misses mirrored, cropped, or filtered copies of your images — different bytes, same picture - voxel51.com/blog/image-copy-… That’s train/test leakage, wasted labeling spend, and licensing headaches waiting to happen. Voxel51’s fix: combine two signals that fail in different places. 🔹 pHash — reads pixel layout, breaks on mirrors/crops 🔹 CLIP — reads meaning, fooled by look-alikes 🔹 A rule you control to combine them (“any” vs “all”) 🔹 Every link shown as a graph, with evidence 🔹 Scored against ground truth with native evaluation Check out @DataScienceHarp's post! #ComputerVision #MachineLearning #OpenSource #AI #DataCuration

Failure mining in robotics: find one failure, surface every similar one - voxel51.com/blog/failure-min… Most robotics teams find failures by scrubbing hours of recordings by hand. This Voxel51 post shows a faster workflow in FiftyOne: * Start with one confirmed failure (a robot drops a cloth mid-fold) and mark it with a temporal tag * Use segment-level embedding similarity search to surface every visually similar moment across the dataset — not whole episodes, but 5-second windows * Embeddings find similar situations, not failures — a dropped cloth and a deliberately placed one look nearly identical. Scoping the search to episodes already flagged as failed cut candidates from 16 down to 2 * Review and confirm the real failures, then tag + save them as a reusable set for retraining or evaluation The result: a repeatable loop — find, search, narrow, confirm, tag — that turns a messy pile of recordings into a growing, labeled failure dataset. #Robotics #PhysicalAI #MachineLearning #ComputerVision #DataCuration #AI #FiftyOne #Voxel51 #RoboticsAI #DataFlywheel

Tokyo's most accident-prone intersection, turned into a dataset you can actually explore. Check out this lightning talk from @DataScienceHarp on the Hard Intersections Multimodal Dataset from Dynamic Map Platform Co., Ltd. - huggingface.co/datasets/dyna… * 6 synchronized camera views (full 360°) * 29 classes of road infrastructure — labeled entirely by models, zero manual annotation * Trajectory data at 200Hz * HD maps in 5 industry formats * ~35M-point aggregated LiDAR All in one interactive viewer with FiftyOne. No exporting. No jumping between tools. #ComputerVision #AutonomousVehicles #FiftyOne #OpenSource

VLA models don't learn from folders of images. They learn from episodes—vision, state, and action locked to one clock, frame by frame - voxel51.com/blog/lerobot-v3-… We loaded 11 LeRobot v3.0 datasets into FiftyOne so you can inspect them before you download. * Single Franka arms to full humanoids * Real teleoperation + pure simulation * Fingertip tactile sensing (20 streams) * From 10 to 27,500 episodes What we found digging in: * InternData-A1 is 100% synthetic—and looks photorealistic * droid_3d's depth streams silently drop (importer can't decode the dtype) * Licenses vary within a single export Look at your data before you train on it. Check out @DataScienceHarp 's post. #PhysicalAI #Robotics #VLA #LeRobot