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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. By Steef-Jan Wiggers
Article: Architecture in a Flow of AI-Augmented Change
While AI adoption is surging, most organizations fail to scale past pilots. The solution lies in organizational structure, not just technology. This article details how architects can enable "fast flow" by defining clear domains and guardrails. Learn how to shift from controlling outcomes to curating context, allowing AI to drive continuous, valuable business change. By Jonathan McPhail, Juan Medina, Jake DeCrane, Isuru Wijesundara
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. By Andrew Hoblitzell
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
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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n8n
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
transformers
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
activepieces
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
DeepSpeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.