Powering AI/ML Operational Innovation with Generative Synthetic Data

Presented by

Muckai Girish, Co-founder and Vyas Sekar, Co-founder, DataFuel

About this talk

Data has become the fuel that powers the Artificial Intelligence ecosystem. Global enterprises continue to face hurdles in training, development and testing of AI/ML models by Dev & Test teams, Data Scientists and MLOps teams: (a) access to data and sharing data is impeded by restrictions and regulations, (b) retention and storage of raw data is expensive and, (c) sparseness and bias in data. Gartner predicts that by 2024, 60% of data used for the development of AI and analytics projects will be synthetically generated. In this webinar, we will discuss how synthetic data can help maximize the usefulness of data by safely sharing it with whom, when and what. We will describe how recent advances in AI Generative Adversarial Networks (GANs) models can be used with structured, time series, incident log and session journey data effectively to create high-fidelity synthetic data that addresses privacy challenges.
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