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Topics

Featured in Development

Expanding Swift from Apps to Services
Cory Benfield discusses the evolution of Swift from an app language to a critical tool for secure, high-scale services. He explains how Swift’s lack of a garbage collector eliminates tail latency and shares how its "zero-cost abstractions" rival C performance. He shares Apple’s roadmap for incremental adoption and demonstrates groundbreaking new interoperability for C++ and Java ecosystems.

All in development

Architecture & Design

Featured in Architecture & Design

Spec-Driven Development – Adoption at Enterprise Scale
Spec‑Driven Development shifts AI‑augmented software delivery from tactical prompting to collaborative intent articulation. Enterprises face gaps in tooling, workflow integration, multi‑repo coordination, and cross‑functional collaboration. Sustainable adoption requires treating specs as living, shared interfaces, and evolving organizational practices.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

DevOps Modernization: AI Agents, Intelligent Observability and Automation
The panelists share how AI is redefining DevOps and SRE practices by moving teams beyond reactive monitoring toward predictive, automated delivery and operations. They discuss integrating AI agents into CI/CD pipelines and feature management to enable intelligent rollouts and machine-speed remediation.

All in ai-ml-data-eng

Culture & Methods

Featured in Culture & Methods

Beyond Code: How Engineers Need to Evolve in the AI Era
In this podcast, Shane Hastie, Lead Editor for Culture & Methods, spoke to Ben Greene about embracing AI in software engineering, expanding beyond pure technical skills to understand business context, and prioritizing human empathy in increasingly automated systems.

All in culture-methods

Featured in DevOps

Proactive Autoscaling for Edge Applications in Kubernetes
Kubernetes often reacts too late when traffic suddenly increases at the edge. A proactive scaling approach that considers response time, spare CPU capacity, and container startup delays can add or remove instances more smoothly, prevent sudden spikes, and keep performance stable on systems with limited resources.

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QCon London 2026

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InfoQ HomepageMachine Learning Content on InfoQ

Machine Learning

Articles about Machine Learning

Presentations about Machine Learning

AI, ML & Data Engineering
Building Embedding Models for Large-Scale Real-World Applications
Sahil Dua
on Feb 13, 2026
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44:06
AI, ML & Data Engineering
How to Unlock Insights and Enable Discovery within Petabytes of Autonomous Driving Data
Kyra Mozley
on Jan 21, 2026
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49:45
Culture & Methods
Humans in the Loop: Engineering Leadership in a Chaotic Industry
Michelle Brush
on Nov 24, 2025
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48:25
AI, ML & Data Engineering
Growing and Cultivating Strong Machine Learning Engineers
Vivek Gupta
on Nov 10, 2025
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38:15
AI, ML & Data Engineering
Achieving Precision in AI: Retrieving the Right Data Using AI Agents
Adi Polak
on Nov 07, 2025
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50:00
AI, ML & Data Engineering
AI for Food Image Generation in Production: How & Why
Iaroslav Amerkhanov
on Aug 27, 2025
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44:46
AI, ML & Data Engineering
10 Reasons Your Multi-Agent Workflows Fail and What You Can Do about It
Victor Dibia
on Aug 14, 2025
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48:24

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Live Webinar presented by Astronomer |
Q&A moderated by InfoQ

Save your Seat!

Orchestrating Production-Ready AI Workflows with Apache Airflow

WHEN: Thursday, March 5th, 202611:00 AM - 12:00 PM EST

Production AI pipelines are hard to run reliably—from RAG and context engineering to inference and human review. Learn how teams use Apache Airflow to orchestrate scalable, event-driven AI workflows with stronger reliability, visibility, and traceability.

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