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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 ...
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 ...
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 ...
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 ...
Public clouds enabled digital transformation at unprecedented speed. But their operational costs over time can be exacting as compute needs increase. Hybrid clouds emerged as an alternative to gain the benefits of both worlds: private infrastructure that allows for lower operational expenditures and tighter control, and public clouds that ...
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 ...
