AI & Machine Learning on Power

The purpose of this blog is to show you how to change the batch size to improve the inferencing throughput of an LSTM AI model. We know that using a larger batch size, such as 640, provides higher inferencing throughput than using smaller batch sizes. ...

In a previous blog post, we introduced Kubeflow on Power . In this article, you will learn how you can use Kubeflow to automate your end-to-end machine learning process – from data loading and cleaning to model training, deployment, and monitoring. The ...

Are you annoyed by writing a custom code for every database you need to connect to, to get all the data you need for your machine learning (ML) models? Here comes a handy solution: use Trino - now fully integrated in our Kubeflow on Power distribution ...

The purpose of this blog is to show you how to enable AI infused SQL queries in IBM Db2 using Python UDFs (User-Defined Functions). The blog also explains how to build AI models on an IBM Power10 system running Linux as well as how to create the dataset ...

The purpose of this blog is to show you how to build an AI model that exploits the benefits of Matrix Math Acceleration (MMA) on an IBM Power10 system. An AI model is a tool or algorithm, which is based on a certain data set through which it can arrive ...