Satya Mallick's banner

Satya Mallick

@LearnOpenCV • 14,594 subscribers

CEO, https://t.co/CzUdJlxzJM. Course Director, https://t.co/O2Tz9vUOQ8 Entrepreneur. Ph.D. ( Computer Vision & Machine Learning ). Author: https://t.co/olraDEG5Ue

Shorts

I used GPT-6 Astra Ultra to track a tennis ball. The results are impressive until I tell you the following. Ball annotation, using 3 parallel agents took 8m 35s and 17,611 tokens. Complete workflow: 11m 49s and 30,481 tokens. The complete workflow also processed 313,914 uncached input tokens and 7,528,320 cached input tokens. That's a total of 7.87 million total, mostly context reused across frame-inspection calls.

I used GPT-6 Astra Ultra to track a tennis ball. The results are impressive until I tell you the following. Ball annotation, using 3 parallel agents took 8m 35s and 17,611 tokens. Complete workflow: 11m 49s and 30,481 tokens. The complete workflow also processed 313,914 uncached input tokens and 7,528,320 cached input tokens. That's a total of 7.87 million total, mostly context reused across frame-inspection calls.

1,043,851 просмотров

Videos

Anya Rossi

sweetdream.ai

SweetDream.ai•Sponsored•Livecam

Watch Anya Live

Anya is streaming live right now! Join her private show and enjoy exclusive content.

Exclusive private shows

1.2k viewers online

Private Show

Join now for exclusive access

Free preview available • Premium content

1/20 I trained two segmentation models using GPT-6 Astra Ultra as the orchestrator with no human labels supplied. My prompt was very lazy too as I had to catch a flight. RF-DETR-Seg-M predictions: Left: SAM3 training masks Right: Astra training masks Both videos held out.

1/20 I trained two segmentation models using GPT-6 Astra Ultra as the orchestrator with no human labels supplied. My prompt was very lazy too as I had to catch a flight. RF-DETR-Seg-M predictions: Left: SAM3 training masks Right: Astra training masks Both videos held out.

28,485 просмотров • 1 день назад

⚡️Did you know YOLOv8 is an anchor-free object detection model, and YOLOv5 is an anchor-based object detection model? We conduct an in-depth comparison between them and carry out inference for detection and segmentation. #yolo #yolov8 #yolov5 #ai

⚡️Did you know YOLOv8 is an anchor-free object detection model, and YOLOv5 is an anchor-based object detection model? We conduct an in-depth comparison between them and carry out inference for detection and segmentation. #yolo #yolov8 #yolov5 #ai

84,454 просмотров • 3 лет назад

Больше нет контента для загрузки