Data-Centric AI Means Centralizing Training Data

Name: Data-Centric AI Means Centralizing Training Data
Uploaded: 2021-11-10

Posted Nov 10, 2021 | Views 351

# Computer Vision

# Presentation

# Health Care

# v7labs.com

SPEAKER

Alberto Rizzoli

CEO @ V7

Alberto Rizzoli is co-Founder of V7, a platform for deep learning teams to create training data workflows that automate labeling. V7 is used by over 500 global AI companies and enterprises including GE, Siemens, Merck, and MIT.

Previously founded Aipoly, the first engine for running large convolutional neural networks on smartphones, leading to the creation of an app enabling the blind to identify 5,000 objects through their phone camera used on over 1 billion images.

Alberto's work on AI granted him an award and a personal audience by Italian President Sergio Mattarella, as well as Italy’s Premio Gentile for Science and Innovation. His work won the CES Best of Innovation in 2017 and 2018.

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SUMMARY

The competitive advantage of computer vision companies is no longer in model architectures but in their training data and the ML-Ops behind it. How do AI-first companies compete? We explored a number of emerging computer vision cases where models become fixed elements, re-trained on continuously evolving datasets as a company's deployments grow. This calls for the need for a CRM-like experience for training data, where ML-Ops tools can apply changes from multiple sources, and enable complex labeling or inference workflows to occur. We talked about how V7 has tackled this problem, what the needs for the MLOps community are, and how to standardize our work to enable further collaboration.

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