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Article Series: AI-Assisted Development: Real World Patterns, Pitfalls, and Production Readiness
In this series, we examine what happens after the proof of concept and how AI becomes part of the software delivery pipeline. As AI transitions from proof of concept to production, teams are discovering that the challenge extends beyond model performance to include architecture, process, and accountability. This transition is redefining what constitutes good software engineering.
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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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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.