Blog posts tagged "AI/ML"

Run an MLOps toolkit within a few clicks on a major public cloud Canonical is proud to announce that Charmed Kubeflow is now available as a software appliance on the Amazon Web Services (AWS) marketplace. With the appliance, users can now launch and manage their machine learning workloads hassle-free using Charmed Kubeflow on AWS. This

Canonical, the company behind Ubuntu, has enjoyed a partnership with Dell Technologies for over a decade. Together, they have collaborated to develop a series of cutting-edge reference architectures applicable to various industries, providing customers with unparalleled experiences and value. This year at KubeCon + CloudNativeCon Europe (

Date: 17-21 April 2023 Location: Amsterdam  Booth: P15 In just a few weeks, Kubecon will be held at RAI Convention Center, in Amsterdam, the Netherlands. After a bunch of news from the industry around AI projects, such as GPT4 or MidJourney4, Canonical is also ready to bring open source into the landscape. Among the attendees,

Run serverless ML workloads. Optimise models for deep learning. Expand your data science tooling.  Canonical, the publisher of Ubuntu, announced today the general availability of Charmed Kubeflow 1.7. Charmed Kubeflow is an open-source, end-to-end MLOps platform that can run on any cloud, including hybrid cloud or multi-cloud scenarios. T

Charmed Kubeflow is now certified in the NVIDIA DGX-Ready Software Program for MLOps! Canonical is proud to announce that Charmed Kubeflow is now certified as part of the  NVIDIA DGX-Ready Software program. This collaboration accelerates at-scale deployments of AI and data science projects on the highest-performing AI infrastructure, prov

Canonical is happy to announce that Charmed Kubeflow 1.7 is now available in Beta. Kubeflow is a foundational part of the MLOps ecosystem that has been evolving over the years. With Charmed Kubeflow 1.7, users benefit from the ability to run serverless workloads and perform model inference regardless of the machine learning framework they

After ChatGPT took off, the AI/ML market suddenly became attractive to everyone. But is it that easy to kickstart a project? More importantly, what do you need to scale an AI initiative? MLOps or machine learning operations is the answer when it comes to automating machine learning workflows. Adopting MLOps is like adopting DevOps, you

The adoption of AI/ML in financial services is increasing as companies seek to drive more robust, data-driven decision processes as part of their digital transformation journey. For global banking, McKinsey estimates that AI technologies could potentially deliver up to $1 trillion of additional value each year. But productionising machine

MLOps (short for machine learning operations) is slowly evolving into an independent approach to the machine learning lifecycle that includes all steps – from data gathering to governance and monitoring. It will become a standard as artificial intelligence is moving towards becoming part of everyday business, rather than an innovative act

Join Canonical and Ubuntu at Mobile World Congress Barcelona 2023 to discuss open source innovation in telecommunications.

While AI seems to be the topic of the moment, especially in the tech industry, the need to make it happen in a reliable way is becoming more obvious. MLOps, as a practice, finds itself in a place where it needs to keep growing and remain relevant in view of the latest trends. Solutions like

Join us as we look back at some of the transformative changes to WSL over the last year as well as a roundup of our personal highlights and Ubuntu insights.

MLOps is the short term for machine learning operations and it represents a set of practices that aim to simplify workflow processes and automate machine learning and deep learning deployments. It accomplishes the deployment and maintenance of models reliably and efficiently for production, at a large scale. MLOps is slowly evolving into

From brick-and-mortar stores to online marketplaces, retail companies are all increasing their investments in artificial intelligence, in order to gain a competitive advantage!

The integration allows users to leverage deep learning for AI/ML projects within the MLOps platform On 8 November 2022, at Open Source Experience Paris, Canonical announced that Charmed Kubeflow, Canonical’s enterprise-ready Kubeflow distribution, now integrates with MindSpore, a deep learning framework open-sourced by Huawei.  Charmed Ku

Looking at the report that Gartner did in 2022 regarding top technology trends, AI engineering represents an important pillar in the near future. It is composed of three core technologies: DataOps, MLOps and DevOps.The discipline’s main purpose is to develop AI models that can quickly and continuously provide business value. For instance,