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Culture & Methods

Getting Rid of Wastes and Impediments in Software Development Using Data Science

This article presents how to use data science to detect wastes and impediments, and concepts and related information that help teams to figure out the root cause of impediments they struggle to get rid of. The knowledge discovered during research includes an expanded waste classification, and the use of trends to uncover undesired situations like hidden delayed backlog items and defects trends.

Everton Lucas
on Jan 07, 2022
AI, ML & Data Engineering

Developing Deep Learning Systems Using Institutional Incremental Learning

Institutional incremental learning promises to achieve collaborative learning. This form of learning can address data sharing and security issues, without bringing in the complexities of federated learning. This article talks about practical approaches which help in building an object detection system.

Ritesh Sinha
on Jan 05, 2022
DevOps

Is Artificial Intelligence Taking over DevOps?

AI tools are slowly replacing the role of the developer – just as DevOps did before – and will eventually supplant DevOps entirely. Assessing whether that prediction is true is tricky. In this article, we’ll look at what AI promises for the development process, assess whether it can really ever take over from human developers, and what DevOps is likely to look like in a decades’ time.

Sam Bocetta
on Oct 08, 2021
AI, ML & Data Engineering

AI, ML and Data Engineering InfoQ Trends Report - August 2021

How AI, ML and Data Engineering are evolving in 2021 as seen by the InfoQ editorial team. Topics discussed include deep learning, edge deployment of machine learning algorithms, commercial robot platforms, GPU and CUDA programming, natural language processing and GPT-3, MLOps, and AutoML.

Roland Meertens Kimberly McGuire Srini Penchikala Rags Srinivas Anthony Alford
on Aug 09, 2021
Culture & Methods

Validation of Autonomous Systems

This article introduces validation and certification as well as the general approval of autonomous systems and their components, such as those used in automation technology and robotics. It gives an overview of methods for verification and validation of autonomous systems, sketches current tools and show the evolution towards AI-based techniques for influence analysis of continuous changes.

Christof Ebert Michael Weyrich
on Jun 23, 2021
DevOps

DevOps is Not Enough for Scaling and Evolving Tech-Driven Organizations: a Q&A with Eduardo da Silva

Eduardo Silva from bol.com on the need for sociotechnical systems thinking. DevOps is a good starting point but a wider view of the organization as a sociotechnical system is key for sustained growth.

Eduardo da Silva Manuel Pais
on Mar 31, 2021
AI, ML & Data Engineering

How Optimizing MLOps Can Revolutionize Enterprise AI

In this article, author Monte Zweben discusses data science architecture, containerization, and how new solutions like Feature Store can help with the full lifecycle of machine learning processes.

Monte Zweben
on Mar 06, 2021
Culture & Methods

Sociotechnical Implications of Using Machines as Teammates

AI has become more than just a tool; it is now meriting consideration as an additional teammate. While this increases a project’s efficiency and technical rigor, AI teammates bring a fresh set of challenges around social integration, team dynamics, trust, and control. This article provides an overview of sociotechnical frameworks and strategies to address concerns with using machines as teammates.

Caitlyn Caggia
on Mar 03, 2021
Cloud

AI No Silver Bullet for Cloud Security, But Here’s How It Can Help

In this article, the author looks at the real role of artificial intelligence in cloud security – the hype, the reality, and how we can resolve the gap between them. He encourages the reader to focus on making cloud security platforms that allow humans to provide truly intelligent threat responses, rather than relying on the machines to do it for us.

Bernard Brode
on Feb 01, 2021
AI, ML & Data Engineering

AI Applied in Enterprises: Information Architecture, Decision Optimization, and Operationalization

The book Deploying AI in the Enterprise by Eberhard Hechler, Martin Oberhofer, and Thomas Schaeck gives insight into the current state of AI related to themes like change management, DevOps, risk management, blockchain, and information governance. It discusses the possibilities, limitations, and challenges of AI and provides cases that show how AI is being applied.

Ben Linders Eberhard Hechler Martin Oberhofer Thomas Schaeck
on Jan 31, 2021
Emerging Technologies

The Brain is Neither a Neural Network Nor a Computer: Book Review of The Biological Mind

Underlying much of artificial intelligence research is the idea that the essence of an individual resides in the brain. This is contrary to neuroscience which has discovered that a brain cannot work independently from the body and its environment. Understanding this enables us see what is reasonable to expect from artificial intelligence, as well as technology designed to improve human life.

Michael Stiefel
on Jan 29, 2021
Culture & Methods

Q&A on the Book Cybersecurity Threats, Malware Trends and Strategies

The book Cybersecurity Threats, Malware Trends and Strategies by Tim Rains provides an overview of the threat landscape over a twenty year period. It provides insights and solutions that can be used to develop an effective cybersecurity strategy and improve vulnerability management.

Ben Linders Tim Rains
on Dec 07, 2020