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Development

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

You’ve Generated Your MVP Using AI. What Does That Mean for Your Software Architecture?

AI‑generated code creates implicit architectural decisions, forcing teams to rely on experimentation to validate quality attributes. To get useful results from AI, teams must clearly express trade‑offs and reasoning so the model can generate solutions aligned with desired QARs.

All in architecture-design

AI Infrastructure

Featured in AI, ML & Data Engineering

Building Embedding Models for Large-Scale Real-World Applications

Sahil Dua discusses the critical role of embedding models in powering search and RAG applications at scale. He explains the transformer-based architecture, contrastive learning techniques, and the process of distilling large language models into production-ready student models. He shares insights on optimizing query latency, handling document indexing, and evaluating retrieval quality.

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

DevOps

Featured in DevOps

From Alert Fatigue to Agent-Assisted Intelligent Observability

As systems grow, observability becomes harder to maintain and incidents harder to diagnose. Agentic observability layers AI on existing tools, starting in read-only mode to detect anomalies and summarize issues. Over time, agents add context, correlate signals, and automate low-risk tasks. This approach frees engineers to focus on analysis and judgment.

All in devops

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InfoQ Homepage Interviews Mike Keith on EJB 3

Mike Keith on EJB 3

19:35

Bio

Mike Keith is the co-specification lead of EJB 3.0 (JSR 220) and also a member of the Java EE 5 expert group (JSR 244). He has been involved in EJB since its initial release and other forms of persistence since long before EJB. He is currently an architect for OracleAS TopLink and the Oracle OC4J J2EE Container and is a popular speaker at numerous conferences and events.

About the conference

Feb 11, 2007

Interview with

Mike Keith

by

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