How to Reduce the Carbon Footprint of AI?

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Presented by

Marie-Pierre Garnier, VP Marketing & Communications, Cortical.io

About this talk

Training one single AI language model emits more carbon dioxide than 5 cars during their whole lifetime. While the AI community is becoming more and more aware of the sustainability issues of artificial intelligence and of the large training models, there is still no consensus about the best way to solve this problem. This webinar explores: - The reasons behind AI energy-efficiency issues - Three approaches that try to solve this problem > Quantum computing > Hardware acceleration > Reverse engineering the brain - Semantic Folding, an approach that leverages reverse engineering the brain, and is already implemented in enterprise environments.
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Cortical.io delivers highly efficient AI-based solutions that help enterprises unlock the value of unstructured text by leveraging a game-changing approach to Natural Language Understanding (NLU). Cortical.io SemanticPro is an intelligent document processing solution that accurately extracts, analyzes and classifies information based on meaning and builds the basis for document workflow automation. With more than 10 years expertise in implementing NLU solutions in the enterprise, Cortical.io has demonstrated its ability to solve the challenges of language ambiguity and variability across many use cases and verticals for Fortune 500 companies.