A platform for open source AI applications
PyTorch is one of the most popular tools for AI model development and tuning. With KubeRay and Ray on AKS, you can quickly work with models at scale, using code running on your laptop to train and tune your model in the cloud. You can also train and tune off-the-shelf, open source models from sites like Hugging Face and customize them for your specific use cases. This means you don’t have to invest in expensive GPUs or large data centers. Instead, you can treat Azure and Ray as a batch-processing environment that only runs when you need it, keeping costs down and letting you quickly deploy custom models in your own network.
There’s a lot more to modern AI than chatbots, and by supporting Ray, AKS becomes a place to train and tune computer vision and other models, using image data stored in Azure blobs or time-series operational data in Fabric, Azure’s big-data service. Once trained, those models can then be downloaded and used in your own applications. For example, you can use NPUs designed for computer vision to run custom-trained models that find flaws in products or that spot safety violations and then trigger warnings. Similar models working with log file data could spot fraud or request preemptive equipment maintenance.
By training and tuning on your own data and your own infrastructure, you get the model you need for a specific task that otherwise might be too expensive to implement. AKS and Ray provide an on-demand, cloud-native training environment, so you’re not only able to get that model in production quickly but also to keep it updated as you identify new source data that can make it more accurate or tuning parameters that will make it more responsive.
