Ultralytics x Paperspace: Advancing Object Detection Capabilities Through Partnership

Object detection is crucial to many computer vision applications, from autonomous vehicles to security systems. Ultralytics YOLOv8 is an advanced object detection algorithm that achieves state-of-the-art accuracy while running at real-time speeds, making it a powerful tool for a wide range of use cases. We created YOLOv8 to help people and companies put AI to positive use.

At Ultralytics, we're excited to announce our newest partnership with Paperspace, a leading provider of machine learning infrastructure. Their environment, Gradient, has many features that make it easy to train your YOLOv5 and YOLOv8 models. Paperspace Gradient allows you to set up a managed GPU environment in a few seconds.

Getting Started With Ultralytics YOLOv8 and Paperspace#

Thanks to our partnership with Paperspace, Ultralytics YOLOv8 is now available on its robust cloud infrastructure. This means that you can quickly and easily train and deploy YOLOv8 models without the need for expensive hardware or time-consuming setup processes. Paperspace's scalable infrastructure ensures that you can handle even the largest datasets and training workloads, all with the ease and convenience of a cloud-based solution.

At Ultralytics, we're passionate about making computer vision accessible to everyone. Our partnership with Paperspace is a major step forward in achieving this goal. We're excited to continue working together to push the boundaries of what's possible with computer vision technology. Whether you're a developer, a researcher, or a business owner, we invite you to try YOLOv8 on Paperspace's cloud infrastructure for yourself.

What’s new in Ultralytics YOLOv8#

YOLOv8 comes as part of the broader Ultralytics Python framework offering. This new framework has been built from the ground up incorporating all of the feedback and learnings from our widely used YOLOv5.

• Global CLI
• The new global command line interface lets you easily access your YOLO models system-wide. You can execute any operation using the yolo command.

• Python API
• The new Ultralytics framework has a dedicated Python API that allows you to extend your Python applications with YOLO features.

• New Ultralytics YOLOv8 Models
• We’ve launched the framework with new Ultralytics YOLOv8 models that achieve SOTA performance on the COCO dataset.

More details about the usage, design, and model architecture are available in the Ultralytics docs.

Using Ultralytics YOLOv8 on Paperspace Gradient#

Paperspace integration is accessible from the Ultralytics README. It takes you to the Ultralytics YOLOv8 notebook on Paperspace Gradient. To get started with Ultralytics on Gradient, simply sign in and start executing the cells, or follow the Ultralytics Paperspace integration guide.

At Ultralytics, we commercially partner with other startups to help us fund the research and development of our open-source tools to keep them free for everybody. This article may contain affiliate links to those partners.