InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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IBM Research Introduces CUGA, an Open-Source Configurable Agent Framework on Hugging Face
IBM Research has released CUGA (Configurable Generalist Agent) on Hugging Face Spaces, making its enterprise-oriented agent framework easier to evaluate with open models and real workflows. The move positions CUGA as a practical alternative to brittle, tightly coupled agent frameworks that often struggle with tool misuse, long-horizon reasoning, and recovery from failure.
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QConAI NY 2025 - Designing AI Platforms for Reliability: Tools for Certainty, Agents for Discovery
Aaron Erickson at QCon AI NYC 2025 emphasized treating agentic AI as an engineering challenge, focusing on reliability through the blend of probabilistic and deterministic systems. He argued for clear operational structures to minimize risks and optimize performance, highlighting the importance of specialized agents and deterministic paths to enhance accuracy and control in AI workflows.
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Google Metrax Brings Predefined Model Evaluation Metrics to JAX
Recently open-sourced by Google, Metrax is a JAX library providing standardized, performant metrics implementations for classification, regression, NLP, vision, and audio models.
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Decathlon Switches to Polars to Optimize Data Pipelines and Infrastructure Costs
Decathlon, one of the world's leading sports retailers, recently shared why it adopted the open source library Polars to optimize its data pipelines. The Decathlon Digital team found that migrating from Apache Spark to Polars for small input datasets provides significant speed and cost savings.
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AWS Expands Well-Architected Framework with Responsible AI and Updated ML and Generative AI Lenses
At AWS re:Invent 2025, AWS expanded its Well-Architected Framework with a new Responsible AI Lens and updated Machine Learning and Generative AI Lenses. The updates provide guidance on governance, bias mitigation, scalable ML workflows, and trustworthy AI system design across the full AI lifecycle.
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QCon AI New York 2025: AI Platform Scaling at LinkedIn
At QCon AI NY 2025, LinkedIn's Prince Valluri and Karthik Ramgopal unveiled an internal platform for AI agents, prioritizing execution over intelligence. By using structured specifications within a robust orchestration layer, they enhance agent observability and interoperability while ensuring human accountability.
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Google Cloud Launches Managed MCP Support
Google Cloud's introduction of fully-managed Model Context Protocol (MCP) servers revolutionizes its API infrastructure, streamlining access for developers. This enterprise-ready solution enhances AI integration across services such as Google Maps and BigQuery while promoting wide-scale adoption. New tools ensure governance and security, and are currently in public preview.
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QCon AI New York 2025: Moving Mountains: Migrating Legacy Code in Weeks instead of Years
David Stein, principal AI engineer at ServiceTitan, presented “Moving Mountains: Migrating Legacy Code in Weeks instead of Years” at QCon AI New York 2025. Stein demonstrated how migrations don’t have to be synonymous to “moving mountains” and introduced the concepts of the Principle of Acceleration and the Assembly Line Pattern.
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OpenAI at QCon AI NYC: Fine Tuning the Enterprise
At QCon AI NYC 2025, Will Hang from OpenAI unveiled Agent RFT—a cutting-edge reinforcement fine-tuning approach for tool-using agents. By optimizing prompts and tasks before model adjustments, Hang showcased effective strategies to enhance decision-making and efficiency, emphasizing a balanced grading system. The session revealed a future where smarter agents reduce latency and improve outcomes.
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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.
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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.
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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.
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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.
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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.
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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.