Delivering generative AI for image tasks, multimodal models combining language and vision, plus object detection, image classification and more
Vision AI plays a pivotal role across an ever-increasing range of applications including medical diagnosis, insurance claims assessment, smart city management, manufacturing, retail, agriculture, advertising and more.
Graphcore hardware and software enables end-to-end computer vision workflows in the cloud - from model development to deployment - for researchers, developers and enterprise users.
Today, computer vision is finding applications across every sector of the economy. From agriculture to retail, from insurance to construction, entrepreneurs are applying computer vision to a wide range of industry-specific use cases with compelling economic upside.
CV analyzes insurance claims for damaged vehicles and homes to provide instant appraisal and claim resolution. It helps reduce cost and boosts business growth with higher customer satisfaction rates.
CV improves medical treatments and procedures, accelerates healthcare research and improves the overall patient experience, helping diagnose cancer and other disorders accurately and efficiently from X-rays and scans.
Generative AI is making a huge impact in the creative sector, opening up new avenues for creative exploration and experimentation by generating content for computer games, advertising, films, websites and much more.
CV helps boost crop yields by estimating seasonal yield before the harvesting period, it detects weeds and pests to to facilitate pesticide-free food production and remotely monitors crop and stock health.
Developing models on your own needs lots of training data, time, and expertise. Here’s the good news – you don’t have to be an expert to get started. Graphcore provides a number of pretrained models, already built and ready to use, to start developing your own CV solutions. Start with our Model Garden with links to pre-built CV models in our GitHub repo and ready-to-go Jupyter Notebooks, like Stable Diffusion, with zero set up required.
Check out our Developer Resources to learn about other computer vision resources, as well as other ML speech and natural language processing use cases, applications and pre-built models.
The popular latent diffusion model for generative AI with support for text-to-image on IPUs using Hugging Face Optimum.
YOLOv4 - You Only Look Once - a convolutional neural network model that performs object detection tasks on IPUs using PyTorch.
ViT (Vision Transformer) fine-tuning in PyTorch using Hugging Face transformers.
The popular latent diffusion model for generative AI with support for inpainting on IPUs using Hugging Face Optimum.
The popular latent diffusion model for generative AI with support for image-to-image on IPUs using Hugging Face Optimum.
Image classification training on IPUs using the CNN (Convolutional Neural Network) model ResNet-50 with TensorFlow 1.
CNN (Convolutional Neural Network) image classification inference on EfficientNet with PyTorch for IPU.
Build, train and deploy your models in the cloud, using the latest IPU hardware and the frameworks you love, with our cloud service partners
Browse providersHave questions about installation, deployment, cloud options or any other technical queries?
Get in touchInterested in getting a quote or finding out more information about the pricing of our data centre products?
Contact salesSign up below to get the latest news and updates: