--- title: 'Digest #2019.09.02 – The why of Kubeflow' description: 'AI Tales: Building Machine learning pipeline using Kubeflow and Minio – Understand the Kubeflow value proposition in an entertaining format. The story starts with Joe, the neighbourhood Machine learning enthusiast. Joe reads a few things, becomes an expert, and then the real fun begins. He quickly runs into problems with portability, DevO […]' url: https://canonical.com/blog/digest-2019-09-02?format=md --- 1. [Blog](https://canonical.com/blog) 2. Article --- [Carmine Rimi](https://canonical.com/blog/author/carmine-rimi "More about Carmine Rimi") 2 September 2019 # Digest #2019.09.02 – The why of Kubeflow [Kubeflow News](https://canonical.com/blog/tag/kubeflow-news) --- Share the article * [AI Tales: Building Machine learning pipeline using Kubeflow and Minio](https://medium.com/kredaro-engineering/ai-tales-building-machine-learning-pipeline-using-kubeflow-and-minio-4b88da30437b) – Understand the Kubeflow value proposition in an entertaining format. The story starts with Joe, the neighbourhood Machine learning enthusiast. Joe reads a few things, becomes an expert, and then the real fun begins. He quickly runs into problems with portability, DevOps, scaling, performance, and cost. Enter Kubeman (or Kubeperson?), who personifies Kubeflow, and saves the day! * [Basics of Data Science Product Management: The ML Workflow](https://towardsdatascience.com/basics-of-ai-product-management-orchestrating-the-ml-workflow-3601e0ff6baa) – Another look at the complicated space that Kubeflow helps solve. “Something I quickly learned was that managing ML products is difficult because of the complexities and uncertainties involved with the different steps in the machine learning workflow” – (1) Review of related literature; (2) Data gathering & processing; (3) Model training, experimentation, & evaluation; (4) Deployment * Hardware Science: [Researchers demonstrate all-optical neural network for deep learning](https://phys.org/news/2019-08-all-optical-neural-network-deep.html) – In a key step toward making large-scale optical neural networks practical, researchers have demonstrated a first-of-its-kind multilayer all-optical artificial neural network. The next generation of artificial intelligence hardware will be much faster and exhibit lower power consumption compared to today’s computer-based artificial intelligence. * Hardware Science: [Quantum computing should supercharge this machine-learning technique](https://www.technologyreview.com/s/613119/quantum-computing-should-supercharge-this-machine-learning-technique/) – Researchers from IBM and MIT show how an IBM quantum computer can accelerate a specific type of machine-learning task called feature matching. Feature matching is a technique that converts data into a mathematical representation that lends itself to machine-learning analysis. Using a quantum computer, it should be possible to perform this on a scale that was hitherto impossible. [Get in touch Interested in running Ubuntu in your organization?](https://ubuntu.com/about/contact-us/form) ## Sign up for our newsletter Get the latest Canonical news and updates in your inbox. Work email: \*I agree to receive information about Canonical's products and services. By submitting this form, I confirm that I have read and agree to [Canonical's Privacy Policy](https://canonical.com/legal/dataprivacy). Sign up ## Share on --- ## Related posts [### Kubeflow operations guide](https://canonical.com/blog/kubeflow-operations-guide) Operating MLOps stacks alike Kubeflow in an increasingly multi-cloud world will be a key topic as this market and Kubernetes adoption grow. Kubeflow operations webinar To... [Andreea Munteanu](https://canonical.com/blog/author/munteanuandreea) 17 March 2021 [### Latest community videos](https://canonical.com/blog/latest-kubeflow-videos) MLOps community jewels The MLOps community continues to grow and gift us with great content and discussions around the topic! Here are a couple of interesting discussions – a... [Rui Vasconcelos](https://canonical.com/blog/author/ruivasconcelos) 8 March 2021 [### Still figuring out what is Kubeflow?](https://canonical.com/blog/kubeflow-learn-understand) Kubeflow has become quite popular in the MLOps community as the tool that enables data science teams to automate their workflows from data preprocessing to model deployment on... [Andreea Munteanu](https://canonical.com/blog/author/munteanuandreea) 22 February 2021 [### SageMaker and Kubeflow: end-to-end ML workflows](https://canonical.com/blog/sagemaker-and-kubeflow) In June 2020, AWS introduced SageMaker components for Kubeflow. 6 months later, Antje Barth, Sr. developer advocate @AWS, presents how to build end-to-end ML workflows with... [Rui Vasconcelos](https://canonical.com/blog/author/ruivasconcelos) 11 February 2021