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Blog posts tagged
"AI"

robgibbon
20 May 2021

Data Lab, Data Lake, Data Hub: what’s the difference?

AI Article

In this post we’ll explore the concepts of data lake, data hub and data lab. There are many opinions and interpretations of these concepts, and they are broadly comparable. In fact, many might say they’re synonymous and we’re just splitting hairs. Let’s look again. ...

Leia Ruffini
13 May 2021

Ubuntu in the wild – 13th of May 2021

Ubuntu Article

The Ubuntu in the wild blog post ropes in the latest highlights about Ubuntu and Canonical around the world on a bi-weekly basis. ...

Maciej Mazur
5 April 2021

Ubuntu for machine learning with NVIDIA RAPIDS in 10 min

AI Article

10 minutes tutorial on how to set up Ubuntu for machine learning, data science and data analytics using NVIDIA RAPIDS, NGC Containers and Anaconda. ...

Leia Ruffini
30 March 2021

Ubuntu in the wild – 30th of March 2021

Cloud and server Article

The Ubuntu in the wild blog post ropes in the latest highlights about Ubuntu and Canonical around the world on a bi-weekly basis. ...

Andreea Munteanu
11 February 2021

Can AI help redefine the future of finserv?

AI Article

The last few years has been a time of major disruption in the Finserv sector. Artificial Intelligence (AI) technology has emerged as an important tool for providers of financial products and services to deliver more personalised and more sophisticated services to customers faster. The financial services sector is at the beginning of an ex ...

Rui Vasconcelos
4 November 2020

Deploying Kubeflow everywhere: desktop, edge, and IoT devices

AI Article

Kubeflow, the ML toolkit on K8s, now fits on your desktop and edge devices! 🚀 Data science workflows on Kubernetes Kubeflow provides the cloud-native interface between Kubernetes and data science tools: libraries, frameworks, pipelines, and notebooks. > Read more about what is Kubeflow Cloud-native MLOps toolkit gets heavy To make Kubeflo ...

Rui Vasconcelos
28 October 2020

Kubeflow operators: lifecycle management for data science

AI Article

Canonical, the publisher of Ubuntu, releases Charmed Kubeflow, a set of charm operators to deliver the 20+ applications that make up the latest version of Kubeflow, for easy consumption anywhere, from workstations to on-prem, public cloud, and edge. > Visit Charmed-kubeflow.io to learn more. Kubeflow, the ML toolkit on K8s Kubeflow provid ...

Canonical
5 October 2020

Canonical expands collaboration with NVIDIA to bring AI to the edge

Ubuntu Article

Canonical has been working closely with NVIDIA for many years to fuel innovation and support open source software with the power of accelerated processing. That already allowed us to jointly deliver GPU acceleration into Linux, OpenStack and container workloads on traditional datacenter servers. We continued working together, with Ubuntu ...

Canonical
2 September 2020

HP Z series on Ubuntu – AI development on enterprise workstations, now in your remote office

Desktop Article

Today, HP announced the launch of its Z series of laptops and workstations certified with Ubuntu 20.04 LTS, the latest additions to their popular professional workstation line. Made to drive AI and machine learning and with hardware that is also suited to 3D and virtual reality development, the Z series is an ideal enterprise workstation ...

Rui Vasconcelos
2 July 2020

Building Kubeflow pipelines: Data science workflows on Kubernetes – Part 2

AI Article

This blog series is part of the joint collaboration between Canonical and Manceps. Visit our AI consulting and delivery services page to know more. Introduction Kubeflow Pipelines are a great way to build portable, scalable machine learning workflows. It is a part of the Kubeflow project that aims to reduce the complexity and time involv ...

Rui Vasconcelos
24 June 2020

Demystifying Kubeflow pipelines: Data science workflows on Kubernetes – Part 1

AI Article

Kubeflow Pipelines are a great way to build portable, scalable machine learning workflows. It is one part of a larger Kubeflow ecosystem that aims to reduce the complexity and time involved with training and deploying machine learning models at scale. In this blog series, we demystify Kubeflow pipelines and showcase this method to produce ...

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