Name: Simplifying AI/ML adoption in telco with modern operations practices
Start: 2021-03-29T16:00:00Z
End: 2021-03-29T16:00:44.000Z
Location: BrightTALK
Rating: 4.7

Get the most in depth information about the Ubuntu technology and services from Canonical. 

Learn why Ubuntu is the preferred Linux platform and how Canonical can help you make the most out of your Ubuntu environment.

Linuxのことはおそらくご存じでしょうが、具体的にどんなものなのか、何ができるのか、そして信頼して次のプロジェクトに使えるものなのか、確信のない方も多いと思います。このウェビナーでは、CanonicalのIjlal LoutfiとHenry CoggillがLinuxとUbuntuのセキュリティについて語ります。最初にオペレーティングシステムの重要性に関する基本事項、次にそれが実行するあらゆるアプリの完全性を確保する仕組みを説明します。Linuxに親しみのない方のために、Linuxの歴史に触れ、オープンソースソフトウェアがどのように開発され、ディストリビューションにバンドルされるかも述べます。オープンソースエコシステムによるセキュリティ脆弱性対策、その発見と修正の方法、終わりのない闘いへのエンドユーザーの反応も検討します。次に、Ubuntuに組み込まれたセキュリティ技術とその未知の脅威に対する防御を解説します。最後は、Canonicalの企業グレードのサポートが、セキュアなオープンソース導入の包括的なプラットフォームとなる理由で締めくくります。

Linuxはセキュア？

Ubuntu 18.04 LTS, installed by millions of users and continuing to have a massive footprint on AWS, hit its End of Life (EOL) in May 2023. When using an unsupported version of Ubuntu LTS, your system and your end users are vulnerable to security risks. Not every company has the time or resources to undertake a migration project to a later and supported Ubuntu LTS distribution which is why many are adopting Ubuntu Pro. 

Join our upcoming webinar to learn how to extend your Ubuntu 18.04 support for an additional 5 years via Ubuntu Pro which provides continuous vulnerability management and patching for your complete fleet of devices. Additionally, gain insights into the simplicity of performing an in-place upgrade through AWS License Manager. 

With Ubuntu Pro, you can improve your DevSecOps practices by having all your open source software security covered from one single source with added automatic kernel livepatch, and automated/guided hardening. 

Don't miss out on this opportunity to streamline your security practices and protect your applications - register now for our webinar!

In this webinar, you’ll learn:
-Why more Ubuntu 18.04 LTS users are adopting Ubuntu Pro
-The features and benefits of Ubuntu Pro and how itprovides an additional 5 years of Extended Service Maintenance support 
-How to smoothly perform an in-place upgrade using AWS License Manager

Still running Ubuntu 18.04? What you need to know

Welcome to Part I of this two-part webinar series on the future of industrial transformation, jointly delivered by Canonical and Bosch Rexroth. 

In this webinar, we will explore the evolving landscape of industrial operations, where Information Technology (IT) meets Operational Technology (OT) to drive significant changes in how factories and manufacturing processes are managed.

Whether you are an IT leader or an engineer interested in the future of industrial operations, this webinar is for you. By the end of this webinar, you will:
- Gain a deep understanding of software-defined industrial transformation and its implications for your business.
- Get insights into the challenges and opportunities presented by this industrial evolution.

Sign up now to learn about the shift from proprietary systems to open standards and how it can benefit your manufacturing operations. In this joint webinar, experts from Canonical and Bosch Rexroth will explore the flexibility and automation possibilities enabled by software-defined approaches. We  will explain the power of IT-OT convergence and how it can improve operational efficiency and decision-making.

Driving the Future of Industrial Automation

Large language models (LLMs) are machine-learning models specialised in understanding natural language. They became famous once ChatGPT was widely adopted around the world, but they have applications beyond chatbots. This blog will explain large language models (LLMs), including their benefits, challenges, famous projects and what the future holds.

LLMs have multiple use cases -  from building  conversational assistants to performing sentiment analysis.  

Amongst the challenges that enterprises face are:

Large datasets Increased computing power 
Lack of talent 
Interpretability 

Join Andreea Munteanu, AI/ML Product Manager and Maciej Mazur, Principal AI/ML Field Engineer to talk more about large language models. During the webinar, they will cover:

What large language models are
How to overcome adoption barriers of LLMs within your enterprise
Use cases of LLMs
Guidance to build projects using LLMs
How to use open source to build LLMs

How to build LLMs with open source

In 22.04, Canonical announced a beta version of the Ubuntu kernel with the PREEMPT_RT patchset integrated. The new real-time kernel serves extreme latency-dependent use cases and provides deterministic response times to service events. By meeting stringent preemption specifications, real-time is suitable across a broad range of verticals, from telco applications to dedicated devices in industrial automation and robotics.

But does a real-time kernel necessarily result in optimized performance? And what would be the consequences of missing a deadline? If you are a Linux kernel enthusiast or just getting started with real-time systems and want to learn more about PREEMPT_RT, this webinar is for you.

This webinar will provide a broad overview of the target use cases and real-time applications. Starting with the building blocks, we will learn:

- What is a real-time system?
- What are the use cases of real-time across market segments?
- What is the role of the PREEMPT_RT patchset?
- How would one know if a low-latency kernel is acceptable over PREEMPT_RT?

And much more. Having set the stage and the necessary context in mind, we will then deep-dive into the Linux kernel build with the out-of-tree PREEMPT_RT patch applied.

An Introduction to Ubuntu Real-time Linux

Compare two of the most advanced database management systems

Oracle database is undoubtedly one of the biggest success stories in the last few decades of IT history. DB-Engines’ ranking still places it as the most popular database despite the growing competition. Oracle database pioneered a number of ideas in the database management landscape that inspired many commercial and open source competitors.

PostgreSQL is one of those open-source alternatives that gained momentum in the recent years due to its vibrant community and ever-increasing number of extensions around its ecosystem (PostGis, TimescaleDB, Citus …). PostgreSQL’ first place in the last StackOverflow survey is an attestation of its success.
PostgreSQL from an Oracle database user’s lens 

Whether you are considering a migration from your Oracle database to PostgreSQL or you are trying to add PostgreSQL to your internal catalogue of the data solutions,  it is critical to understand the differences of PostgreSQL compared to Oracle database. 

In this webinar, we will dive into the development, operational and ecosystem differences between both solutions. We will draw a parallel between some of Oracle database’s most popular features (e.g. Active Data Guard, GoldenGate, RMAN) and their closest counterparts in the PostgreSQL landscape.
How to migrate from Oracle database to PostgreSQL

Understanding and analysing the differences between database solutions is the first step in a successful migration from one database to the other. In this webinar, we will present a methodology to execute your migration while minimising downtime and lowering the risk of data loss and performance degradation.

PostgreSQL for Oracle database users

A lightweight, secure machine learning platform you can use on any infrastructure

Introduction to MLFlow, the open-source tool for machine learning

IT infrastructure is widely used to host mission-critical applications and services that must be available 24/7. However, downtime may occur and can have significant consequences in terms of costs, revenue and company reputation.

The cost and the consequences of downtime vary depending on the nature of the business, the type of infrastructure and the severity of the outage. For example, airlines, financial services and healthcare companies that rely on real-time systems for bookings, trading, and managing sensitive data, would likely experience much higher costs than a smaller company that uses its infrastructure for internal purposes.

It is exactly when incidents happen that organisations realise that implementing a fix in a timely manner can be quite expensive, and allocating skills and resources to incident response in advance can pay off significantly.

This is where enterprise support for IT infrastructure can be helpful, by bringing the right expertise that organisations need in the moment they need it. Support services act as an insurance policy by backing your team up 24/7 and expanding their knowledge with a valuable range of skills.

In this webinar, we will talk about how enterprise support services can help you minimise downtime for your IT infrastructure. The webinar will cover:

- Challenges maintaining and evolving IT infrastructure
- Challenges with incidents management
- How enterprise support for IT infrastructure works and how it can help you address those challenges
- How to choose the partner that is right for you
- How we support you at Canonical

How to ensure business continuity with IT infrastructure support

In this webinar Oliver Smith, Product Manager for Ubuntu, and Aaron Prisk, Community Engineer and former IT Director for a US K-12 educational institution, will share their thoughts and experiences on the role of Ubuntu in Education.

Back to school: Ubuntu Desktop in education

Intro to RTK - 3/10/23

Complying with the U.S. government security standards such as FISMA, FIPS, FedRAMP or DISA-STIG is crucial not only for government agencies but also for enterprises that provide solutions that need to comply with the strictest of the US government security requirements. 

At the same time, the operating system is the cornerstone of a compliance program. It provides the foundation for compliance for data protection with certified cryptography such as FIPS 140, hardening profiles for military applications such as DISA-STIG, and enables continuous vulnerability management. Canonical’s Ubuntu is well positioned not only to address the U.S. government's requirements for enterprise workloads, but also to provide the foundation for any successful solution.

In this webinar, we will:

- Provide an introduction to the U.S. government security standards and highlight common challenges
- Provide a breakdown of the standards in terms of software requirements and OS requirements
- Explain how 3rd party applications can follow the US government standards with Ubuntu
- Discuss how Ubuntu provides a secure platform for government agencies to build, operate and innovate with open source applications and technologies

How Ubuntu enables your compliance with FedRAMP, FISMA, FIPS, and DISA-STIG

AI is everywhere, especially in businesses.  From productivity to creativity to transformation, AI is rapidly becoming an indispensable tool for professionals.  Generative AI is a branch that took off this year, with a wide range of applications. While ChatGPT gathered more than 1 billion users in less than one week, the applications of generative AI go beyond chatbots.

What is generative AI?
Generative AI (GenAI) is a type of artificial intelligence that enables quick content generation. It uses various inputs, to deliver different outputs like text, sound, 3D animation or images. GenAI identifies patterns within existing data that are then used to generate new ones. Stable Diffusions or GPT-3 are just some examples of widely-adopted generative AI models. 

Generative AI models also need validation, like any other artificial intelligence project. Validation is important to ensure the quality of the output, which is especially important for applications that interact directly with users. Additionally, diversity in data sources is crucial to reduce bias and speed up output generation.

Generative AI vs LLMs
GenAI and large language models (LLMs) often create confusion. Whereas Generative AI focuses on content-creation functions, LLMs are used in relation to systems connected with languages. Generative AI is powered by very large machine learning models, often referred to as foundational models (FMs). Large language models (LLMs) are a subset of this category. LLMs are trained on trillions of words across many natural languages. This is the reason why LLMs can engage and build interactive conversations, powering many types of applications.

Join us live to learn more about generative AI

Demystifying generative AI: how to roll it out in your enterprise

Every innovation comes with its challenges, and AI is no exception. In the rapidly growing AI landscape, how can financial institutions navigate the complexities of at scale AI deployment effectively?

We invite you to our engaging webinar, where the speakers will:
- Present the business impact of AI
- Discuss opportunities for banks to boost competitiveness using AI solutions
- Explain barriers to AI adoption at scale
- Share a reference AI tech stack with a focus on open source technologies
- Delve into banking use cases of open source AI 
- Share best practices for navigating the challenges of at scale AI deployment

Open source AI in banking

Artificial Intilligence and Machine Learning are hot topics these days, with more enterprises announcing huge investments in powerful computing hardware and new LLM models all over the news. It translates into a clear need to also optimise and search for machine learning tooling, that enables the desired return on investment for all these projects.

Kubeflow vs MLFlow

Started by Google a couple of years ago, Kubeflow is by design an end-to-end MLOps platform for AI at scale. Canonical has its own distribution, Charmed Kubeflow addresses the entire machine-learning lifecycle. It is, in fact, a suite of tools, such as Notebooks, for training, Pipeline for automation, Katib for hyperparameter tuning or KServe for model serving and more. Charmed Kubeflow benefits from a wide range of integrations with other tools such as MLFlow, Spark, Grafana or Prometheus.

MLFLow on the other hand celebrated last year 10 million downloads, being a very popular solution when it comes to machine learning. Started initially with a core function, the tool has nowadays four conceptions that include model registry or experiment tracking.

So, the main question arises: which one should you choose for Machine Learning Operations?

Kubeflow vs MLFLow is a panel discussion with Maciej Mazur - AI/ML Principal Engineer at Canonical, Kimonas Sotirchos - Kubeflow Community Working Group Lead and Engineering Manager at Canonical about:

Production-grade MLOps
Open-source MLOps
Community-driven ML tooling
Kubeflow vs MLFlow; Pros and Cons

[APAC Webinar] Kubeflow vs MLFlow: which one to choose?

Give your generative AI models a broader and deeper pool of data with the right vector database

Future-proof AI applications with OpenSearch as a vector database

Give your generative AI models a broader and deeper pool of data with the right vector database.

Comparing the most popular open source databases:

PostgreSQL and MySQL are undoubtedly the most popular open source databases. You can check the latest developer surveys from StackOverflow and JetBrains, or DB-Engines’ popularity index if you are not convinced. Their popularity is fueled by their vibrant communities and their track record of successful deployments across  IT sectors.

In this webinar, we will dive into the differences between these two popular databases and what those differences mean from a performance, operability and community engagement perspective and how Canonical can support you in adopting, securing and scaling open-source databases.

PostgreSQL vs MySQL

How to choose between the most popular open-source databases for your enterprise

In this webinar you'll get a comprehensive overview of all AI/ML use cases in the telecom space. You'll also learn what infrastructure and software components are needed to enable them, and how open source software can help you achieve the best price-to-performance ratio for your business. We'll then go over the most prominent modern devops approaches that can help you increase adoption speed and time to market for ML based services. Finally, we'll cover the data scientists' perspective, and how you can experiment with telecom stack thanks to open source.

Simplifying AI/ML adoption in telco with modern operations practices

Artificial Intelligence

Machine Learning

Network Architecture

Network Function Virtualization

Open Source

Software Defined Networking

Telecommunications

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Simplifying AI/ML adoption in telco with modern operations practices

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