Computer Vision

Computers can be trained to accurately identify objects in images and videos faster than ever before, but they need massive amounts of data to do so.  Even for pre-trained models, re-training or tuning is essential to ensure high accuracy and effectiveness of a model.  What was once possible with on-premises workstations or servers, using initial models with limited pattern matching capabilities, has now shifted to deep learning and machine learning models that add AI capabilities, providing a deeper understanding of visual content. As the needs for acceleration of these models increases, companies often attempt to scale their operations for computer vision needs on cloud services such as AWS or GCP, only to realize that prolonged usage of these services can be prohibitively expensive.

With powerful models at their disposal, specific market segments- such as autonomous and robotic systems, healthcare, manufacturing, agriculture and security applications- can take data from sensors and other imaging devices and analyze it in a timely manner to meet the needs of specific workflows.

Cirrascale has been leveraging GPUs for computer vision use cases, enabling groundbreaking improvements across image and object classification, detection and tracking applications. Today, with a wider variety of acceleration options available for computer vision, Cirrascale’s AI Innovation Cloud platform is a superior choice for companies needing cloud-based, dedicated servers. You'll be charged one flat rate per month -no ingress or egress fees, no overage charges, no surprises. Plus, we provide a level of support that goes beyond other providers.