InfoQ Homepage Artificial Intelligence Content on InfoQ
-
/articles/validation-autonomous-systems/en/smallimage/logo-1624226498499.jpg)
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.
-
/articles/devops-not-enough-scaling-tech-driven-organizations/en/smallimage/logo-1617086584261.jpg)
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.
-
/articles/optimizing-mlops-enterprise-ai/en/smallimage/how-optimizing-MLOps-can-revolutionize-enterprise-AI-logo-small-1614873793830.jpg)
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.
-
/articles/sociotechnical-implications-using-machines-teammates/en/smallimage/logo-1614625343110.jpg)
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.
-
/articles/ai-cloud-security/en/smallimage/AI-no-silver-bullet-for-cloud-security-small-1611928293687.jpg)
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.
-
/articles/AI-applied-architecture-decision-optimization/en/smallimage/deploying-ai-in-the-enterprise-small-1611925224285.jpg)
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.
-
/articles/brain-not-computer/en/smallimage/the-biological-mind-s-1611697218890.jpg)
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.
-
/articles/book-review-cyber-securities/en/smallimage/cybersecurity-logo-small-1607015545941.jpg)
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.
-
/articles/book-review-accelerating-software-quality/en/smallimage/accelerating-cover-1604062444647.jpg)
Q&A on the Book Accelerating Software Quality
The book Accelerating Software Quality by Eran Kinsbruner explores how we can combine techniques from artificial intelligence and machine learning with a DevOps approach to increase testing effectiveness and deliver higher quality. It provides examples and recommendations for using AI/ML-based solutions in software development and operations.
-
/articles/AI-Closer-Common-Sense/en/smallimage/AI-Closer-Common-Sense-s-1602793883610.jpeg)
Is Artificial Intelligence Closer to Common Sense?
Intelligent agents lack the common-sense knowledge they need to reason about the world. Traditionally, there have been two unsuccessful approaches to getting computers to reason about the world—symbolic logic and deep learning. A new project, called COMET, tries to bring these two approaches together. Although it has not yet succeeded, it offers the possibility of progress.
-
/articles/human-pose-estimation-ai-powered-fitness-apps/en/smallimage/human-pose-estimation-ai-powered-fitness-apps-s-1602698421552.jpeg)
Challenges of Human Pose Estimation in AI-Powered Fitness Apps
In this article, the author discusses the human pose estimation solution powered by AI technologies and the challenges faced in online fitness apps which use the pose estimation to predict the position of the human body based on an image or a video containing a person.
-
/articles/book-review-techlash/en/smallimage/techlash-logo-1598373165736.jpg)
Q&A on the Book Techlash
The book Techlash by Ian Mitroff and Rune Storesund explains why companies need to become socially responsible by considering the potential negative outcomes of technology. It explains how proactive crisis management can help prevent a crisis by the early detection and correction of deviations from expected conditions.
SPONSORED BY
Live Webinar presented by Diffblue |
Q&A moderated by InfoQ
ChatGPT is fun, but the future is fully autonomous AI for code
ChatGPT and AI tools based on Large Language Model have recently grabbed headlines. But LLMs are not the only way to do AI for code: fully autonomous code-writing is possible by using reinforcement learning to write code that can compile, run and be correct. Learn more in this webinar.