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The role of secure data storage in fueling AI innovation

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).

Introducing Netplan v1.0 - stable, declarative network management

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.

OpenStack with Sunbeam as an on-prem extension of the OpenStack public cloud

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.=

AI on Public Cloud with Open Source

AI is at the heart of a revolution in the technology space. Organisations from all industries are looking for ways to put AI to work. Once they have finalised use case assessment, their next question is typically related to the environment they will use to develop and deploy their AI initiatives. They often prefer the public clouds as an initial environment, because of the computing power and ability to scale as projects mature. In addition to the infrastructure, enterprises need software where they can develop and deploy the machine learning models.

Inventory and remediate Red Hat Enterprise Linux with Security Technical Implementation Guides (STIGs)

Security Technical Implementation Guides (STIGs) are an excellent body of knowledge to leverage in securing your infrastructure. With the stig-rhel-7 module you can easily add inventory and remediation policy for RHEL 7 with CFEngine. Do note that as of March 2024 this module does not provide comprehensive coverage but rather an initial 10 findings are implemented.

AI and automotive: navigating the roads of tomorrow

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.