Clouds, be they private or public, surprisingly remain one of the most DIY-favouring markets. Perhaps due to the nebulous and increasingly powerful technologies, a series of myths, or even unnecessary egos, the majority of non-tech-centric enterprises (meaning, companies whose primary business scope rests outside the realm of IT software and hardware) still try to build and nurture in-house cloud management teams, without considering outsourcing even part of their workload.

Artificial intelligence is the most exciting technology revolution of recent years. Nvidia, Intel, AMD and others continue to produce faster and faster GPU’s enabling larger models, and higher throughput in decision making processes. Outside of the immediate AI-hype, one area still remains somewhat overlooked: AI needs data (find out more here).

New subscription for IoT deployments brings security and long term compliance to the most advanced open source stack.

As the maintainer and lead developer of Netplan, I’m proud to announce the general availability of Netplan v1.0 after more than 7 years of development efforts. Over the years, we’ve had approximately 80 individual contributors from around the globe. This includes many contributions from our Netplan core-team at Canonical as well as organisations like Microsoft and Deutsche Telekom.

Canonical is proud to announce it is joining the ELISA (Enabling Linux in Safety Applications) project. By joining ELISA, Canonical will work side-by-side with other industry leaders to make Linux a trusted and dependable option for safety-critical environments.

One of the biggest challenges that cloud service providers (CSPs) face these days is to deliver an extension of the public cloud they host to a small-scale piece of infrastructure that runs on customers’ premises. While the world’s tech giants, such as Amazon or Azure, have developed their own solutions for this purpose, many smaller, regional CSPs rely on open source projects like OpenStack instead.=

I had the pleasure to be invited by Canonical’s AI/ML Product Manager, Andreea Munteanu, to one of the recent episodes of the Canonical AI/ML podcast. As an enthusiast of automotive and technology with a background in software, I was very eager to share my insights into the influence of artificial intelligence (AI) in the automotive industry.

This blog post explores the technical and strategic benefits of deploying open-source AI models on Ubuntu. We’ll highlight why it makes sense to use Ubuntu with open-source AI models, and outline the deployment process on Azure.

Telecommunications companies (telcos) are well on their way to transforming their infrastructure from the legacy, unadaptable, complex network of dedicated hardware from yesteryears to agile, modular and scalable software-defined systems running on common off-the-shelf (COTS) servers. Within this space, the current trend, driven by 5G deployments, is to complement tried and tested network function virtualisation (NFV) infrastructure with cloud-native network functions (CNFs).

In our previous post, we discussed how to generate Images using Stable Diffusion on AWS. In this post, we will guide you through running LLMs for text generation in your own environment with a GPU-based instance in simple steps, empowering you to create your own solutions. Text generation, a trending focus in generative AI, facilitates a broad spectrum of language tasks beyond simple question answering.