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

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

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

HPE – Refining ML models with ML

Seldon - Model Serving Event - April 2022

Fabiana Clemente – YData – Scaling DataPrepOps

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

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

Davit Buniatyan – Activeloop – Training Large Visual Models with Deep Lake

Amit Phadke – Bosch AIShield – Securing AI systems at Scale

Bernease Herman –WhyLabs–Truly scalable monitoring and observability for massive NLP and CV datasets

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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