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26 Jan 2022 / 17:30 - 19:00

Knowledge Intensive AI: beyond the data-driven approach

The abundance of data and the recent advances in deep neural networks (e.g. Transformer models) allowed for the creation of data-driven AI systems/models with new emergent capabilities that produced impressive results across many different domains and tasks in the last years.

But, data-driven only approaches are prone to critical limitations that can impose critical risks when deployed in real-case scenarios. In this master class, we will discuss the main characteristics and differences of data-driven and knowledge-intensive AI approaches, when knowledge-intensive AI approaches should be chosen, how to incorporate knowledge in modern AI approaches and why knowledge helps improve the capabilities of data-driven approaches.

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Estevam Rafael Hruschka,

Megagon Labs

Estevam Hruschka is the Head of Research at Megagon Labs

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