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QCon AI NY 2025 - Becoming AI-Native Without Losing Our Minds To Architectural Amnesia
Tracy Bannon's QCon AI NY 2025 talk revealed how the rise of AI agents risks amplifying common architectural failures. She emphasized the distinctions between bots, assistants, and agents, highlighting the need for governance, clear identity controls, and disciplined decision-making to address “agentic debt.” Bannon called for architects to apply foundational principles amid rapid AI adoption. By Andrew Hoblitzell
How Artificial Intelligence Can Help Us Connect with Customers
In software development, success means going beyond meeting requirements. We must create products that surprise and delight users and are innovative, create impactful solutions, Ken Hughes said in the keynote “Connection is Everything”. AI can help us connect with customers and create better user experiences. By Ben Linders
Cactus v1: Cross-Platform LLM Inference on Mobile with Zero Latency and Full Privacy
Cactus, a Y Combinator-backed startup, enables local AI inference to mobile phones, wearables, and other low-power devices through cross-platform, energy-efficient kernels and a native runtime. It delivers sub-50ms time-to-first-token for on-device inference, eliminates network latency, and defaults to complete privacy. By Sergio De Simone
Presentation: Ecologies and Economics of Language AI in Practice
Jade Abbott discusses the shift from massive, resource-heavy models to "Little LMs" that prioritize efficiency and cultural sustainability. She explains how techniques like LoRA, quantization, and GRPO allow for high performance with less compute. By sharing the "Ubuntu Punk" philosophy, she shares how to move beyond extractive data practices toward human-centric, sustainable AI systems. By Jade Abbott
OpenAI and Anthropic Donate AGENTS.md and Model Context Protocol to New Agentic AI Foundation
OpenAI and Anthropic have donated their AGENTS.md and Model Context Protocol projects to the Agentic AI Foundation (AAIF), a new directed fund under the Linux Foundation. Block contributed their agent framework, goose, as another founding project, and several other tech companies have joined as Platinum members. By Anthony Alford
Pinecone Introduces Dedicated Read Nodes in Public Preview for Predictable Vector Workloads
Pinecone recently announced the public preview of Dedicated Read Nodes (DRN), a new capacity mode for its vector database designed to deliver predictable performance and cost at scale for high-throughput applications such as billion-vector semantic search, recommendation systems, and mission-critical AI services. By Craig Risi
Toad: A Unified CLI Tool for All Your LLMs That Promises Improved UX From Existing Ones
During his sabbatical, Will McGugan, maker of Rich and Textual( frameworks for making Textual User Interfaces (TUI)), put his UI skills to work to build Toad. The newly publicly released tool aims to provide a unified, “beautiful” GUI for multiple coding agents in your terminal, accessible via the same tool via the Agent Communication Protocol (ACP). By Olimpiu Pop
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. By Robert Krzaczyński
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. By Andrew Hoblitzell
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qlib
Qlib is an AI-oriented Quant investment platform that aims to use AI tech to empower Quant Research, from exploring ideas to implementing productions. Qlib supports diverse ML modeling paradigms, including supervised learning, market dynamics modeling, and RL, and is now equipped with https://github.com/microsoft/RD-Agent to automate R&D process.
stable-baselines3
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
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.
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.