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Anya Rossi

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we've been testing astra across domains and are finding some surprises and specific areas it is reliable exciting zero-shot knowledge wins happening here, mainly understanding which player scored! a lot goes into that: - knowing in/out of court and service box - who hit last - understanding a point ended - game knowledge of missed first-serve doesn't result in a point other cool things here you get out of the box - understanding the stroke - tracking player to assign points would be easy to add - stroke counts - heat map - point durations

we've been testing astra across domains and are finding some surprises and specific areas it is reliable exciting zero-shot knowledge wins happening here, mainly understanding which player scored! a lot goes into that: - knowing in/out of court and service box - who hit last - understanding a point ended - game knowledge of missed first-serve doesn't result in a point other cool things here you get out of the box - understanding the stroke - tracking player to assign points would be easy to add - stroke counts - heat map - point durations

59,191 views • 1 month ago

No data, no problem introducing agentic synthetic data generation with Cosmos 3 share a few examples, generate more data, automate model training, automatically deploy the latest version with no downtime in a benchmark run with Corning Incorporated's optical fiber manufacturing engineering team, a model trained on 8 real defect images plus synthetic examples generated by Cosmos reached 0.95 mean average precision and perfect recall on the toughest defect class, beating a baseline trained on real data alone. "The Roboflow Agent powered by NVIDIA allows us to generate the training data we need, fine-tune our models, and strengthen model performance and inspection quality while increasing the speed, scalability, and adoption of next-generation technologies,” - Jeremy Knopf, chief information officer, Corning Optical Communications

No data, no problem introducing agentic synthetic data generation with Cosmos 3 share a few examples, generate more data, automate model training, automatically deploy the latest version with no downtime in a benchmark run with Corning Incorporated's optical fiber manufacturing engineering team, a model trained on 8 real defect images plus synthetic examples generated by Cosmos reached 0.95 mean average precision and perfect recall on the toughest defect class, beating a baseline trained on real data alone. "The Roboflow Agent powered by NVIDIA allows us to generate the training data we need, fine-tune our models, and strengthen model performance and inspection quality while increasing the speed, scalability, and adoption of next-generation technologies,” - Jeremy Knopf, chief information officer, Corning Optical Communications

39,416 views • 5 months ago

New tutorial on how to use Astra for training smaller models Astra is powerful but too expensive for many use cases most Astra demos don't make sense as production applications so we made a tutorial showing how you can use Astra's vision capabilities to train smaller more efficient models like RF-DETR Preview here, full tutorial in next post

New tutorial on how to use Astra for training smaller models Astra is powerful but too expensive for many use cases most Astra demos don't make sense as production applications so we made a tutorial showing how you can use Astra's vision capabilities to train smaller more efficient models like RF-DETR Preview here, full tutorial in next post

14,274 views • 1 month ago

Announcing Roboflow Rapid: the first prompt-based model creation engine. Data labeling is dead. Go from idea to deployed model in minutes without labeling data. Upload a video, type a text prompt, and get an API. No data labeling teams. No manual annotation. No infra / dependency hell. If you are spending 95% of your time labeling data and only 5% building your app, you are doing it wrong.

Announcing Roboflow Rapid: the first prompt-based model creation engine. Data labeling is dead. Go from idea to deployed model in minutes without labeling data. Upload a video, type a text prompt, and get an API. No data labeling teams. No manual annotation. No infra / dependency hell. If you are spending 95% of your time labeling data and only 5% building your app, you are doing it wrong.

23,039 views • 11 months ago

On the tenth day of #Shipmas, Roboflow gave to me... MJPEG camera streams. Now even old-school IP cameras can plug straight into Roboflow Inference and Workflows, unlocking millions of streams for use with AI. Point to the URL, hit run, get predictions + annotated video.

On the tenth day of #Shipmas, Roboflow gave to me... MJPEG camera streams. Now even old-school IP cameras can plug straight into Roboflow Inference and Workflows, unlocking millions of streams for use with AI. Point to the URL, hit run, get predictions + annotated video.

13,213 views • 10 months ago

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