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Guide to Enterprise AI Platform Selection

This is an article from DZone's 2022 Enterprise AI Trend Report.

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The use of artificial intelligence (AI) in companies is becoming more and more widespread, possibly even trending toward industrialization. Whether this is done on the basis of an existing data science platform or not, using all-in-one tools or not, or hosting data in the cloud or on-premise, there is a large number of software solutions available and, therefore, choices. This profusion of choices should not make us forget the raison d'être of any IT solution! Between those who promise you the moon and those who want the ultimate (and unfeasible) solution, you must stick to your needs more strongly than ever. 

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How To Use Kubernetes in AI Projects

Introduction

The Cloud Native Survey, which polls Technology/Software organizations, reports that the use of containers in production has increased by 84% from the previous year, up to 92%. The use of Kubernetes is up 78% from the previous year, reaching 83%.

Kubernetes’ distributed architecture and scalability pair well with Machine Learning and Artificial Intelligence. As these technologies continue to mature, 2021 is the year to watch for growth in this space.

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What is AIOps or Artificial Intelligence for IT Operations? Top 10 AIOps Use Cases

What is AIOps

Artificial Intelligence for IT Operations (AIOps) involves using Artificial Intelligence and Machine Learning technologies along with big data, data integration, and automation technologies to help make IT operations smarter and more predictive. AIOps complement manual operations with machine-driven decisions.

Types of AIOps Solutions

At a high level, AIOps solutions are categorized into two areas: domain-centric and domain-agnostic, as defined by Gartner. Domain-centric solutions apply AIOps for a certain domain like network monitoring, log monitoring, application monitoring, or log collection. You will often see monitoring vendors claim AIOps but primarily they are domain-agnostic, bringing the power of AI to the domain they manage. Domain-agnostic solutions operate more broadly and work across domains, monitoring, logging, cloud, infrastructure, etc., and they take data from all domains/tools and learn from this data to more accurately establishing patterns and inferences.

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AI From an Analyst’s Point of View

It’s always interesting to listen to analysts' points of view on tech topics, at least because they are deeply listened to and followed by many key decision-makers. In this article, I’ll use source Gartner, IDC, and the World Economic Forum as my main sources.

What to Do Over the Two Next Years

Analysts seem to be converging on the fact that 2020 will be the year in which AI will start to take off with the first large-scale deployments. The years 2019 and 2020 will therefore be pivotal for the implementation of AI within companies, which must begin to prepare and reflect on the cases of uses that AI could carry.

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How Can AI Be Used in Schools?

It's perhaps fair to suggest that much of the discussion to date around artificial intelligence and education has revolved around the impact AI will have on jobs, and the changes in skills required to work effectively with and alongside the new technology. It's been much less common to explore how AI might impact the act of education itself, so a recently published report from the innovation group, NESTA, makes timely reading.

The report first looks at the way AI is being used in workplaces today, before then exploring possible changes in the future. NESTA identified three main uses of AI in education today: