The purpose of symbolic artificial intelligence is to reproduce human reasoning by modeling it with a set of symbols.
Human reasoning is thus modeled and transmitted to the machine by coded rules, instructions.
The objective: To reproduce the logic and knowledge of an expert in a machine.
Symbolic artificial intelligence is an effective tool in the optimization of operational processes or the management of business operational flows.
The performance of symbolic artificial intelligence is limited in the processing of natural language or the recognition of objects for which we will favor machine learning.
What is Neuro-Symbolic AI?
Neuro-symbolic AI is the synergy of symbolic AI and deep learning.
Neuro-symbolic artificial intelligence combines machine learning based on knowledge modeling and the logical approach of expert systems based on explicit rules.
Neuro-symbolic models have demonstrated their ability to outperform deep learning models in areas such as image recognition and analysis.
They have been shown to achieve high accuracy with significantly less training data than traditional deep learning models.
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