One of the biggest bottlenecks in deploying visual AI and computer vision is annotation, which can be both costly and time-consuming. Today, we’re introducing Verified Auto Labeling, a new approach to AI-assisted annotation that achieves up to 95% of human-level performance while

🚗📷 How can Vision-Language Models transform computer vision in industry? At #ODSCWest, @DataScienceHarp (@voxel51) leads a workshop on Visual AI for vehicle damage detection using the CarDD dataset + FiftyOne. 📅 Oct 28–30 | SF 🔗 https://t.co/yOUUJIgI1i #VisualAI #VLMs

🔗 Full case study here: https://t.co/foJfEfkaud ➡️ Want to go deeper? Join us on Sept. 10 for the first in a series of virtual events to hear talks from experts on the latest developments at the intersection of Visual AI, Manufacturing and Robotics: https://t.co/dqMCzJhwVY

This allowed them to: ✅ Efficiently organize 20TB+ of data ✅ Handle millions of customer objects ✅ Eliminate repetitive data transformations Matt Shaffer, VP of Artificial Intelligence and Co-founder at @RiosCorporation says: “Everything we do from the MLOps side interacts

.@RIOSCorporation helps enterprises across a number of different industries automate their factories through flexible AI-powered robotic solutions. But every deployment required subtle changes in the data schema—costing engineers hours just to prep data for training. They

Speakers and topics include: - "Towards Robotics Foundation Models that Can Reason" by Jiafei Duan from @UW / @Ai2 - "Beyond Academic Benchmarks: Critical Analysis and Best Practices for Visual Industrial Anomaly Detection" by Aimira Baitieva from @Valeo - "The Digital

Robots that can explain their own failures and novel anomaly detection methods are just some of the breakthroughs redefining how Visual AI powers manufacturing and robotics. Join us for an exciting look at the latest developments in this space during the third event in our

@nvidiaomniverse Get the full details here: https://t.co/LPQlTwNBxX 📅 Join our upcoming webinar on Sept. 4 at 9AM PT to learn how companies like Porsche are advancing AV development by leveraging FiftyOne to build next-generation datasets and models: https://t.co/9dl8186Mf7

@nvidiaomniverse Now developers can: 👉 Ingest datasets from various AV pipelines as well as from public datasets, such as NuScenes or Waymo Open Dataset 👉 Validate their datasets for consistency by visually inspecting the data 👉 Catch and correct misalignments before they derail model

Fragmented, incomplete, and unvalidated data have been slowing down AV and ADAS development for years. The datasets of the future will need to evolve to reactive, replayable scenes that can simulate completely new events. But with the new integration between @nvidiaomniverse

If you want to go deeper, join us Sept. 10 for Visual AI in Manufacturing & Robotics, where industry experts will share real-world strategies for anomaly detection, complex industrial optimization, and more. Register here: https://t.co/dqMCzJhwVY

Detecting a tiny defect, an abnormal scan, or a suspicious event can be the difference between safety and failure across manufacturing, healthcare, and security. But anomaly detection can be a challenge due to the high dimensionality of the data and the complexity of the

Computer vision is reshaping industries—from defect detection in manufacturing to behavioral analytics in retail. But turning these technologies into enterprise-ready solutions takes more than just a good model. On Aug 28, join us for our virtual event "Scaling Computer Vision

Here’s the lineup: 👉 "Bringing Specialist Agents to the Physical World to Improve Manufacturing Output" by Clinton J. Smith, PhD, @RIOSCorporation 👉 "Accelerating Robotics with Simulation" by @bgxc, @Lightwheel 👉 "Anomalib 2.0: Edge Inference and Model Deployment" by Samet

From stalled productivity to safety hazards, the gap between potential and reality in manufacturing and robotics is huge. Visual AI is closing it. Join us for Day 2 of our virtual meetup series on Visual AI in Manufacturing and Robotics on Sept. 11 to hear how experts are

📖 Read the full post by @dan_gural here: https://t.co/SZcKe2iAT2 And don’t miss our upcoming webinar on Sept 4 at 9AM PT to learn how Porsche is advancing its AV development by leveraging the power of Voxel51 and Databricks. Register here:

With @databricks + @Voxel51, teams can finally bring structure to unstructured data and uncover the edge cases that matter most: 👉 Search millions of frames to pinpoint long-tail scenarios instantly 👉 Uncover patterns and outliers you might not even know to look for using

In the autonomous vehicle industry, 99% accuracy can be meaningless if a model fails in one critical scenario. The hardest problems hide in edge cases, like a pedestrian crossing in the rain at night or a cyclist partially obscured in a crosswalk. These rare events are exactly

Traditional annotation is slowing down the race to fully autonomous vehicles. On Sept. 4, join @Porsche, Voxel51, and @databricks for an exclusive look at how cutting-edge VLMs, automated data pipelines, and human-in-the-loop feedback loops are transforming the way AV systems

@BoschGlobal @Tesla @SamsungDSGlobal If you're ready to go deeper, join us Sept. 10 for Visual AI in Manufacturing & Robotics, where industry experts will share real-world strategies for anomaly detection, complex industrial optimization, and more. 📅 Save your spot here:

Our new whitepaper breaks down: ➡️ Common failure modes in visual AI defect detection & how to avoid them ➡️ How leaders like @BoschGlobal, @Tesla & @SamsungDSGlobal use AI to slash costs & boost defect detection accuracy ➡️ Best practices for resilient, high-performing systems