InfoQ Homepage Artificial Intelligence Content on InfoQ
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InfoQ AI, ML and Data Engineering Trends Report - 2025
This InfoQ Trends Report offers readers a comprehensive overview of emerging trends and technologies in the areas of AI, ML, and Data Engineering. This report summarizes the InfoQ editorial team’s and external guests' view on the current trends in AI and ML technologies and what to look out for in the next 12 months.
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Virtual Panel: How Software Engineers and Team Leaders Can Excel with Artificial Intelligence
Artificial intelligence is impacting the individual work of software developers, how professionals work together in teams, and how software teams are being managed. In this panel, we'll discuss how artificial intelligence is reshaping software development, and what mindset and skills are required for software developers and engineering leaders to become adaptable and resilient in the age of AI.
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Effective Practices for Architecting a RAG Pipeline
Hybrid search, smart chunking, and domain-aware indexing are key to building effective RAG pipelines. Context window limits and prompt quality critically affect LLM response accuracy. This article provides lessons learned from setting up a RAG pipeline.
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How Causal Reasoning Addresses the Limitations of LLMs in Observability
Large language models excel at converting observability telemetry into clear summaries but struggle with accurate root cause analysis in distributed systems. LLMs often hallucinate explanations and confuse symptoms with causes. This article suggests how causal reasoning models with Bayesian inference offer more reliable incident diagnosis.
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MCP: the Universal Connector for Building Smarter, Modular AI Agents
In this article, the authors discuss Model Context Protocol (MCP), an open standard designed to connect AI agents with tools and data they need. They also talk about how MCP empowers agent development, and its adoption in leading open-source frameworks.
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The Virtual Think Tank: Using LLMs to Gain a Multitude of Perspectives
The virtual think tank leverages LLMs to simulate diverse stakeholder and expert perspectives, enabling architects to explore trade-offs, challenge biases, and refine decisions. By prompting personas of real industry experts, the method fosters rich, contextual debates—offering a scalable, low-cost alternative to a traditional think tank.
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The Missing Layer in AI Infrastructure: Aggregating Agentic Traffic
In this article, author Eyal Solomon discusses AI Gateways, the outbound proxy servers that intercept and manage AI-agent-initiated traffic in real time to enforce policies and provide central management.
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Infusing AI into Your Java applications
Equip yourself with the basic AI knowledge and skills you need to start building intelligent and responsive Enterprise Java applications. With the help of our simple chatbot application for booking interplanetary space trips, see how Java frameworks like LangChain4j with Quarkus make it easy and efficient to interact with LLMs and create satisfying applications for end-users.
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Effective Practices for Coding with a Chat-Based AI
In this article, we explore how AI agents are reshaping software development and the impact they have on a developer’s workflow. We introduce a practical approach to staying in control while working with these tools by adopting key best practices from the discipline of software architecture, including defining an implementation plan, splitting tasks, and so on.
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The State Space Solution to Hallucinations: How State Space Models are Slicing the Competition
AI-powered search tools often hallucinate and make up facts, misquote sources, and recycle outdated information. The real cause of this is tied to the architecture of most AI models: Transformer. In this article, author Albert Lie explains why transformers struggle with hallucinations, how State Space Models (SSMs) offer a solution, and what this shift could mean for the future of AI search.
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Spotting Image Differences in Visual Software Testing with AI
Current AI, including multimodal models, fails at robust visual regression testing, missing structural changes that pixel-based tools flag as false positives. This article proposes a CNN-based solution to compare image segments, tolerating minor displacements. For larger distortions, a multi-scale algorithm realigns the images before comparison, isolating the true differences.
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Developer Joy: a Better Way to Boost Developer Productivity
In this article, Holly and Trisha explore why joy isn’t a distraction from productivity: it’s the secret ingredient. From debugging brain waves in the middle of a jog to cutting out test flakiness, they explain how to reclaim developer satisfaction and boost output by embracing curiosity, minimizing friction, and giving ourselves a break.