InfoQ Homepage Artificial Intelligence Content on InfoQ
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InfoQ Software Architecture and Design Trends Report - 2025
The InfoQ Trends Reports offer InfoQ readers a comprehensive overview of key topics worthy of attention. The reports also guide the InfoQ editorial team towards cutting-edge technologies in our reporting. In conjunction with the report and trends graph, our accompanying podcast features insightful discussions among the editors digging deeper into some of the trends.
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Distributed Cloud Computing: Enhancing Privacy with AI-Driven Solutions
Distributed cloud, PETs, and AI enable secure, private data processing. This integration enhances collaboration, security, and compliance across marketing, finance, and healthcare, addressing the growing need for data protection.
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Bridging Modalities: Multimodal RAG for Advanced Information Retrieval
In this article, the authors discuss how multi-model retrieval augmented generation (RAG) techniques can enhance AI by integrating multiple modalities like text, images, and audio for deeper contextual understanding, with help of a practical example of a healthcare application.
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Beyond Chatbots: Architecting Domain-Specific Generative AI for Operational Decision-Making
This article explores the use of domain-specific Generative AI, models that understand operational constraints, real-world dynamics, and business rules to generate executable strategies, not just text descriptions. These models require significantly smaller datasets and fewer parameters, making them cost-effective while enabling AI-driven core business decision intelligence at scale.
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AI Trends Disrupting Software Teams
In this article, author Bilgin Ibryam discusses various AI trends disrupting the overall software development process and tools, and how these trends are influencing different IT teams like developers, operations, technical writers, and SaaS service providers.
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Secure AI-Powered Early Detection System for Medical Data Analysis & Diagnosis
In this article, the author discusses the techniques for securing AI applications in healthcare with an use case of early detection system for medical data analysis & diagnosis. The proposed layered architecture includes application components to support secure computation, ai modeling, governance and compliance, and monitoring and auditing.
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Prompt Engineering: Challenges, Strengths, and Its Place in Software Development's Future
Prompt engineering is evolving as a crucial skill that bridges AI communication and programming, blending creativity and precision to shape the future of software development. The future of software development might involve a synergistic blend of both approaches. Prompt engineering can accelerate prototyping and enhance interactivity, while traditional programming ensures robustness.
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Building Trust in AI: Security and Risks in Highly Regulated Industries
Explore the transformative power of responsible AI across industries, emphasizing security, MLOps, and compliance. As AI drives innovation—from predicting hurricanes to enhancing legal workflows—organizations must prioritize ethical practices, transparency, and robust governance to safeguard sensitive data while navigating an evolving regulatory landscape.
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Launching GenAI Productivity Tools: Insights and Lessons
In this article, based on a talk at QCon San Francisco 2024, author Mandy Gu shares some of the ways her company uses GenAI to enhance productivity and the lessons they learned along the way, including failed bets and features that were rolled back because of low user adoption. Most important, they learned to focus on building tools that were aligned with business goals.
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Prompt Injection for Large Language Models
This article will cover two common attack vectors against large language models and tools based on them, prompt injection and prompt stealing. We will additionally introduce three approaches to make your LLM-based systems and tools less vulnerable to this kind of attacks and review their benefits and limitations, including fine-tuning, adversarial detectors, and system prompt hardening.
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Elevate Developer Experience with Generative AI Capabilities on AWS
This is a summary of a talk I gave at InfoQ Dev Summit Munich 2024. I discussed the transformative potential of generative AI in enhancing developer experiences, particularly through AWS. I’ll introduce key tools like Amazon Bedrock, Code Review Assistant, Agentic Code Generation, and Code Summarization in this article.
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A Framework for Building Micro Metrics for LLM System Evaluation
LLM accuracy is a challenging topic to address and is much more multi-dimensional than a simple accuracy score. Denys Linkov introduces a framework for creating micro metrics to evaluate LLM systems, focusing on goal-aligned metrics that improve performance and reliability. By adopting an iterative "crawl, walk, run" methodology, teams can incrementally develop observability.