AI INFRASTRUCTURE ALLIANCE
Building the Canonical Stack for Machine Learning
Our Work
At the AI Infrastructure Alliance, we’re dedicated to bringing together the essential building blocks for the Artificial Intelligence applications of today and tomorrow.
Right now, we’re seeing the evolution of a Canonical Stack (CS) for machine learning. It’s coming together through the efforts of many different people, projects and organizations. No one group can do it alone. That’s why we’ve created the Alliance to act as a focal point that brings together many different groups in one place.
The Alliance and its members bring striking clarity to this quickly developing field by highlighting the strongest platforms and showing how different components of a complete enterprise machine learning stack can and should interoperate. We deliver essential reports and research, virtual events packed with fantastic speakers and visual graphics that make sense of an ever-changing landscape.
Download the Enterprise Generative AI Adoption Report
Oct 2023
Our biggest report of the year covers the wide world of agents, large language models and smart apps. This massive guide dives deep into the next-gen emerging stack of AI, prompt engineering, open source and closed source generative models, common app design patterns, legal challenges, LLM logic and reasoning and more.
Get it now. FREE.
AI Landscape
Check out our constantly updated AI Landscape Graphic that shows the full range of capabilities for major MLOps tools instead of just pigeonholing them into a single box that highlights only one aspect of their primary characteristics.
Today’s MLOps tooling offers a broad sweep of possibilities for data engineering and data science teams. You can’t easily see those capabilities in typical graphics that show a bunch of logos so we’ve engineered a better info-graphic to let you quickly figure out if a tool does what you need now.
Events – Past and Future
Check here for our upcoming events and to watch videos from past events. We put on 3 to 4 major events every year and they’re packed with fantastic speakers from across the AI/ML ecosystem.
MEMBERS
ARTICLES
TerminusDB 10.1 – The Mule Release
The latest release of TerminusDB is here and there’s a lot to tell you about. The Mule Release, a homage to Asimov’s Foundation series, is faster, more robust, and includes new features to make developing knowledge graphs and data-intensive applications easier and...
Understanding ML Monitoring Debt
We’re all familiar with technical debt in software engineering, and at this point, hidden technical debt in ML systems is practically dogma. But what is ML monitoring debt? ML monitoring debt is when model monitoring is overwhelmed by the scale of the ML systems that...
5 Minimum Requirements of an Operational Feature Store
I’ve spent the last few months thinking heavily about feature stores. It’s the hottest new buzz word in the ML space, and everyone has a distinct implementation laser-focused on their personal use cases. A recent article¹ that I read talked about this exact topic and...
Lead with DevSecOps to Lower Risk and Raise Value
Developing and deploying AI-powered systems and applications is a complex business, especially in our extended remote reality. You’re likely facing an uphill climb and let’s face it, huge risks. The way to clear the obstacles, lower the risks, and raise the value you...
What are AI attacks?
What are AI attacks? Introduction AI is the gamechanger of this decade. It is rapidly transforming our world and everyday life. The underlying technology, called Machine Learning (ML), is all around us. It’s ML that decides whether you get a loan sanctioned, how much...
A Modern Approach to Versioning Large Files for Machine learning and moree
Original article (Mandarin) written by ArtiV developer Chen-en Lu (Popcorny) for the MLOps Taiwan Facebook community. Translated and adapted to English by Dave Flynn tl;dr ArtiV is smart version control system for large files, especially suited for use on machine...
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