A productionalized intelligence platform for digital and research infrastructure and outputs
AI Agent Lands PRs in Major OSS Projects, Targets Maintainer...
An AI agent is merging PRs into major OSS projects and cold-emailing maintainers to drum up more work.
The PR you would have opened yourself
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Atlas Research - AI-Powered Research Platform
Transform your research workflow with Atlas - an AI-powered platform for data analysis, PDF processing, and interactive notebooks.
ecosyste.ms | Tools and datasets to support, sustain, and secure critical digital infrastructure.
Tools and datasets to support, sustain, and secure critical digital infrastructure.
A Collectivist, Economic Perspective on AI
Information technology is in the midst of a revolution in which omnipresent data collection and machine learning are impacting the human world as never before. The word ``intelligence'' is being...
Databricks: Leading Data and AI Platform for Enterprises
Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform.
Public Intelligence
Imagine 50 years from now a Public Intelligence that was a distributed, open-source, non-commercial artificial intelligence, operated like the internet, and available to the whole world. This public AI would be a federated system, not owned by any one entity, … Continue reading →
AI native industrial data platform for manufacturing | UMH
Standardize industrial data across sites and systems to reduce costs, improve efficiency and accelerate execution. Open-source, deployed at production sites across Europe, live in weeks.
Perspective Chapter: Fit for Purpose? Creative Commons Licensing for Research Data in the Age of Artificial Intelligence
Licensing is an important component of the re-usability of research data, itself part of the FAIR principles: without clear, machine-readable licensing, datasets risk becoming technically...
Getting Started with ML and AI in Research Software | Software Sustainability Institute
Getting started with ML in research software means embracing a shift in how results are produced and reproduced. Instead of a fixed execution path, research software teams work with systems whose behaviour emerges from data, configuration, and training dynamics. Reproducibility becomes a matter of capturing the process rather than relying solely on the code. The tools and techniques outlined here can be adopted incrementally into existing projects, and together they provide a practical foundation for reproducible ML research.
We need to talk about the lack of investment in digital research infrastructure
Research software infrastructure is critical for accelerating science, and yet, these digital public goods are often unsustainably funded. Solving this problem requires an appreciation of the intrinsic value of research software outputs, and greater investment of time and effort into effectively funding maintenance of software at scale.
From OSS to Open Source AI: an Exploratory Study of Collaborative...
AI development is embracing open-source paradigm, but the fundamental distinction between AI models and traditional software artifacts may lead to a divergent open-source development paradigm with...
microsoft/bitnet-b1.58-2B-4T · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
