Let’s meet at AI4 and talk about open source and AI tooling

Date: 12 – 14 August 2024

Booth: 426

Autumn is a season full of events for the AI/ML industry. We are starting early this year, before the summer ends, and will be in Las Vegas to attend AI4 2024. This is North America’s largest industry event, and it attracts some of the biggest names in the AI/ML space to share deep discussions about initial exploration for AI, machine learning operations (MLOps) and AI at the edge. Join Canonical at our very first AI4, where you’ll be able to get in-person recommendations for innovating at speed with open source AI.

Sponsored

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Canonical is the publisher of Ubuntu, the leading Linux distribution that has been around for 20 years. Our mission to provide secure open source software extends well into the machine learning space. We have been providing solutions since the earliest days of AI/ML, for example our official distribution of Kubeflow, an end-to-end MLOps platform that helps organisations productise their ML workloads. Nowadays, Canonical’s MLOps portfolio includes a suite of tools that help you run the entire machine learning lifecycle at all scales, from AI workstations to the cloud to edge devices. Let’s meet to talk more about it!

Engaging with industry leaders, open source users, and organisations looking to scale their ML projects is a priority for us. We’re excited to connect with attendees at AI4 to meet, share a cup of coffee, and give you our insights and lessons in this vibrant ecosystem.

Innovate at speed with open source AI

At Canonical, ever since we launched our cloud-native apps portfolio, our aim has been to enable organisations to run their Data & AI projects with one integrated stack, on any CNCF-comformant Kubernetes distribution and on any environment, weather it is on-prem or on any major public cloud.  As you might know already, we enable you to run your projects at all scales:

• Data science stack for beginners: Many people are trying to upskill in data science and machine learning these days. However, beginners spend more time setting up their environment than developing their capabilities in this field. Data science stack (DSS) is an easy-to-deploy solution that can run on any workstation. It gives access to an environment to quickly get started with data science or machine learning. You can read more about our Data Science Stack here.
• Charmed Kubeflow for ML at scale: Kubeflow is an end-to-end MLOps platform used to develop and deploy models at scale. It is a cloud-native application that runs on any CNCF-conformant Kubernetes, including MicroK8s, AKS, EKS or GKE. It integrates with leading open source toolings such as MLflow, Spark or OpenSearch. Try it out now!
• Ubuntu Core and Kserve for Edge AI: Devices are often a vulnerable point and running a secure OS is crucial in order to protect all the artefacts, regardless of the architecture. Open source tools such as KServe enable AI practitioners to deploy their models on any edge device,

During AI4, we have prepared for a series of demos to show you how open source tooling can help you with your data & AI projects. You should join our booth if you:

• Have questions about AI, MLOps, Data and the role of open source
• Need help with defining your MLOps architecture
• Are looking for secure open source software for your Data & AI initiatives
• Would like to learn more about Canonical and our solutions

Get your infrastructure ready for GenAI

In 2023, the Linux Foundation published a report which found that almost half of surveyed organisations prefer open source tooling for their GenAI projects. Despite this rapid adoption, enterprises are still facing challenges that are related to security, transparency and accessibility and costs. While initial experimentation seems handy due to the large number of solutions available on the market, taking GenAI projects to production obliges organisations to upgrade their AI infrastructure and ensure the data and model protection.

Join my talk, “GenAI beyond the hype: from experimentation to production“ at AI4 on Wednesday, August 14, 2024  from 11:35 AM. During the presentation, I will guide you through  how to move GenAI projects beyond experimentation using open source tooling such as Kubeflow or OpenSearch. We will explore the key considerations and common pitfalls as well as challenges that organisations face when starting a new initiative. Finally, we will analyse the ready-made ML models and scenarios to determine when they are more suitable than building your own solution. 

At the end of it, you will be better equipped to run your GenAI projects in production, using secure open source tooling. 

Join us at Booth 426

If you are attending AI4 2024 in Las Vegas, US between 12- 14 August, make sure to visit booth 426. Our team of open source experts will be available throughout the day to answer all your questions about AI/ML and beyond.

You can already book a meeting with our team member [SDR name] using the link below.