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
The Fastest Version Control for Large Files
tl;dr ArtiVC is lightning fast. We recently released ArtiVC, our centralized file versioning solution specifically designed for large files. After sharing the release on Reddit and other places, one question that kept coming up was “how does ArtiVC perform in...
MLOPSLIVE WEBINAR SERIES
Session #7Product Madness (an Aristocrat co.) on Predicting 1st-Day Churn in Real Time Product Madness’ Head of Data Science discusses how technology and new work processes can help the gaming and mobile app industries predict and mitigate 1st-day (or D0) user churn...
ML Testing and Debugging – The Missing Piece in AI Development
Today, TruEra launched TruEra Diagnostics 2.0, the next major release of our flagship solution. This release is a game-changer for our customers and for ML leaders looking to accelerate the time required to get high quality models into production. That’s because...
Move Fast Without Breaking Things in ML
Many companies are learning that bringing a model that works in the research lab into production is much easier said than done. Written by Bob Nugman, ML Engineer at Doordash, and Aparna Dhinakaran, CPO of Arize AI. In this piece, Bob and Aparna discuss the importance...
How to Debug Transfer Learning Drift for Tabular Models
In a previous article, we analyzed a model for predicting Airbnb listing prices in San Francisco. The model was an XGBoost model trained on Airbnb data scraped by Inside Airbnb and hosted by OpenDataSoft. In this article, we’ll take a step further into the model’s...
6 examples of TerminusDB’s enterprise data solutions
TerminusDB is a powerful in-memory document graph database and provides several enterprise data solutions. It’s packed with features and sometimes the ability to fit into a wide array of applications causes confusion and ambiguity. This article aims to provide a...
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