InfoQ Homepage Machine Learning Content on InfoQ
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Training Data Preprocessing for Text-to-Video Models
In this article, author Aleksandr Rezanov discusses the data preparation for generative text-to-image models to accelerate work on video generation services to be used in TV series and films. He explains how data is prepared and can serve as a starting point for creating custom datasets to develop proprietary models.
on Nov 06, 2025 -
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.
on Sep 24, 2025 -
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.
on Sep 02, 2025 -
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.
on Aug 29, 2025 -
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.
on Aug 22, 2025 -
Faster, Smoother, More Engaging: Personalized Content Pagination
Dynamic content loading powered by AI transforms user experiences by personalizing delivery based on user's behavior and network conditions. By analyzing scroll depth, speed, and dwell time, we optimize loading times, enhance engagement, and reduce infrastructure costs, especially on devices with poor internet connectivity.
on May 28, 2025 -
Beyond the Gang of Four: Practical Design Patterns for Modern AI Systems
In this article, author Rahul Suresh discusses emerging AI patterns in the areas of prompting, responsible AI, user experience, AI-Ops, and optimization, with code examples for each design pattern.
on May 15, 2025 -
Best Practices to Build Energy-Efficient AI/ML Systems
In this article, author Lakshmithejaswi Narasannagari discusses the sustainable innovations in AI/ML technologies, how to track carbon footprint in all stages of ML systems lifecycle and best practices for model development and deployment.
on May 09, 2025 -
Beyond Notebook: Building Observable Machine Learning Systems
In this article, the author discusses a machine learning pipeline with observability built-in for credit card fraud detection use case, with tools like MLflow, FastAPI, Streamlit, Apache Kafka, Prometheus, Grafana, and Evidently AI.
on Mar 14, 2025 -
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.
on Mar 03, 2025 -
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.
on Feb 10, 2025 -
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.
on Jan 21, 2025