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Latest articles from InfoQ• Updated 17 minutes ago
Netflix Migrates to Amazon Aurora: 75% Performance Boost and 28% Cost Reduction
Netflix consolidated its relational databases onto Amazon Aurora, cutting costs by 28% and boosting performance by up to 75%. The move from self-managed PostgreSQL reduced operational toil, improving latency for critical apps. This mirrors migrations by Samsung and Panasonic, though benchmarks suggest alternatives like Timescale may suit specific workloads better. By Mark Silvester
TornadoVM 2.0 Brings Automatic GPU Acceleration and LLM support to Java
The TornadoVM project recently reached version 2.0, a major milestone for the open-source project that aims to provide a heterogeneous hardware runtime for Java. The project automatically accelerates Java programs on multi-core CPUs, GPUs, and FPGAs. This release is likely to be of particular interest to teams developing LLM solutions on the JVM. By Ben Evans
Transformers v5 Introduces a More Modular and Interoperable Core
Hugging Face has released the first candidate for Transformers v5, marking a significant evolution from v4 five years ago. The library has grown from a specialized model toolkit to a critical resource in AI development, achieving over three million installations daily and more than 1.2 billion total installs. By Robert Krzaczyński
Meta's Optimization Platform Ax 1.0 Streamlines LLM and System Optimization
Now stable, Ax is an open-source platform from Meta designed to help researchers and engineers apply machine learning to complex, resource-intensive experimentation. Over the past several years, Meta has used Ax to improve AI models, accelerate machine learning research, tune production infrastructure, and more. By Sergio De Simone
Lyft Rearchitects ML Platform with Hybrid AWS SageMaker-Kubernetes Approach
Lyft has rearchitected its machine learning platform LyftLearn into a hybrid system, moving offline workloads to AWS SageMaker while retaining Kubernetes for online model serving. Its decision to choose managed services where operational complexity was highest, while maintaining custom infrastructure where control mattered most, offers a pragmatic alternative to unified platform strategies. By Eran Stiller
AWS Transform Custom Tackles Technical Debt
AWS Transform Custom revolutionizes code modernization with AI-driven, out-of-the-box transformations for Java, Node.js, and Python. This enterprise-focused tool accelerates application upgrades by up to 5x while learning from organizational nuances to deliver high-quality, repeatable transformations. By Steef-Jan Wiggers
Article: Trustworthy Productivity: Securing AI Accelerated Development
Autonomous AI agents amplify productivity but can cause severe damage without safeguards. Defend the ReAct loop—context, reasoning, and tools—through provenance gates, planner-critic separation, scoped credentials, sandboxed code, and STRIDE/MAESTRO threat modeling. With robust logging, bounded autonomy, and red-teaming, agents can deliver trustworthy productivity while minimizing risk. By Sriram Madapusi Vasudevan
Presentation: Powering Enterprise AI Applications with Data and Open Source Software
Francisco Javier Arceo explored Feast, the open-source feature store designed to address common data challenges in the AI/ML lifecycle, such as feature redundancy, and low-latency serving at scale. By Francisco Javier Arceo
AlphaEvolve Enters Google Cloud as an Agentic System for Algorithm Optimization
Google Cloud announced the private preview of AlphaEvolve, a Gemini-powered coding agent designed to discover and optimize algorithms for complex engineering and scientific problems. The system is now available through an early access program on Google Cloud, targeting use cases where traditional brute-force or manual optimization methods struggle due to vast search spaces. By Robert Krzaczyński
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