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NVIDIA Labs has open-sourced NOOA (NVIDIA Object-Oriented Agents), a model-agnostic Python framework for building AI agents. Agent development today is split across prompt templates, tool schemas, callback code, and workflow graphs. NOOA collapses all of it into one Python class. Methods are the actions the model can take. Fields are agent state. Docstrings are prompts. […]
Learn how the SAS Viya MCP Server enables AI assistants like Claude Cowork to orchestrate governed, auditable banking analytics workflows while keeping model execution, governance and oversight within SAS Viya. The post Building a governed banking workflow with SAS® Viya® MCP Server and Claude Cowork appeared first on SAS Blogs.
Building a governed banking workflow with SAS® Viya® MCP Server and Claude Cowork Read More »
Meta AI has released Muse Code (in beta), a terminal coding agent in beta, powered by its new Muse Spark 1.2 model. Meta positions the pair as its next step toward the frontier, with larger models on the way. Muse Code targets complex software engineering across large repositories: it plans changes, writes code, and validates
The idea that AI agents need ‘eyes’ – real visual information from the real world, and not just paperwork and dashboards, have become a marker of advancement in construction technology. Yet mostly what has been referred to as an “agent” today is not actually acting based on what it sees. It narrates and alerts while
Introduction A reasoning LLM is a language model trained not just to predict the next word, but to work through a problem step by step and verify its own conclusions before answering the approach behind models like OpenAI’s o1 and DeepSeek’s R1. This guide condenses a practical path to building a compact 300–400M parameter GPT-style
Build a Reasoning LLM from Scratch: A Complete Guide to GRPO, RoPE & Pretraining. Read More »
NVIDIA has released Alpamayo 2 Super, a 34B-parameter vision-language-action (VLA) model for autonomous driving, under an open commercial license. The stated design target is the long-tail events: rare, multi-agent situations that conventional detection-and-prediction stacks handle poorly. The model pairs a 32B VLM backbone, built on NVIDIA Cosmos 3 Super Reasoner and post-trained with reinforcement learning,
CopilotKit has just released the Channels SDK. It is an open source library that puts an existing agent inside a messaging platform. The core assumption is focused and verifiable. You already have an agent. It already has a model, tools and business logic. Channels gives it a place to work with people, without a rewrite
Cursor Research has open-sourced Mixture-of-Kittens (MoK), the mixture-of-experts training megakernel behind its Composer models. MoK fuses every MoE communication and computation step into a single deterministic kernel. Cursor team reports up to 2.37x higher throughput than the strongest public baseline. It already powers Composer training across tens of thousands of GPUs. Is it deployable Yes,
Reflex AI has released XY, an Apache-2.0 Python charting library for interactive 2D visualization. Most Python charting stacks create one drawable object per row, so past a few hundred thousand points, render, hover, and zoom degrade. XY moves the work into a native Rust core, sends the browser typed binary buffers instead of JSON, and
A one-size-fits-all approach likely isn’t the best strategy when designing artificial intelligence systems that assist users in disease diagnosis.A new study by researchers at MIT and elsewhere found that, while AI assistance generally improved the accuracy of non-experts and clinicians in diagnosing skin diseases, AI explainability methods had different impacts depending on the users’ knowledge
The benefits of medical AI assistance vary based on user expertise Read More »
