video

datacentricaisummit2022

aiatscale2023

day2summit

monitor

observe

explain

3March2022

7April2022

AI at Scale 2023

Data-Centric AI Summit 2022

Daniel Jeffries – AIIA – The Age of Industrialized AI and What It Means for the Future

Greg Throne – FeatureBase – Maintaining Up-to-the-Millisecond Freshness Across 20B Devices

Luca Antiga – Lightning AI – Scaling Up Foundation Models with Lightning

Amber Roberts – Arize – Fairness Metrics and Bias Tracing in Production

Miriam Santos – DCAI Community – Auditing Data Quality with Pandas Profiling

Eric Landau – Encord – Active Learning & the ML Team of the Future

Gilad Shaham – Iguazio – Production-First Approach: How to Scale up your ML Operations

Monitoring on Structured Data and Beyond

Iguazio shows you the challenges of managing experiment tracking at scale.

Iguazio - Experiment Tracking - March 2022

Seldon - Model Serving Event - April 2022

HPE – Refining ML models with ML

Jennifer Prendki – Alectio – What the *%& is DataPrepOps?

Fabiana Clemente – YData – Scaling DataPrepOps

Alejandro (Alex) Muller – Savvy AI – Mind the GAP

Daniel Langkilde – Kognic – Optimal Representations for Human Feedback

Niccolò Zanichelli – OpenBioML – AI at scale in computational biology

Seth Clark – Modzy – Deploy once, run anywhere: A new approach for scaling production ML

The AI Infrastructure Alliance brings together the tools, data scientists and data engineers need to build a robust, scalable, end-to-end, enterprise artificial intelligence and machine learning (AI/ML) platform.

AI Infrastructure Alliance

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