Can Neurosymbolic AI Save LLM Bubble from Exploding?
Neurosymbolic AI systems
Neurosymbolic AI systems are attractive due to their potential to enable easy-to-interpret reasoning and knowledge-based decision-making, which are crucial for ensuring responsible and reliable AI systems.
Extensions to Kahnemans System 1 and System 2 framework
This article introduces substantial extensions to Kahnemans System 1 and System 2 framework and proposes a new taxonomy of cognitive styles that can help us better understand the strengths and weaknesses of different AI systems.
LLM-based conversational agents
This trend has sparked significant discourse centered around the ever-increasing need for LLM-based conversational agents to be interpretable and controllable, raising concerns about their potential biases and harmful effects.
Integration of neural networks and symbolic AI
Neurosymbolic AI refers to AI systems that seek to integrate neural networks and symbolic AI, with the aim of combining the strengths of both approaches to achieve more powerful and interpretable AI systems.
Rapidly emerging paradigm
This article introduces the rapidly emerging paradigm of Neurosymbolic AI, which combines neural networks and symbolic AI to create a new generation of AI systems that are more powerful and interpretable than traditional AI systems.
20 years of research in neurosymbolic AI
In this paper, we seek to place 20 years of research in the area of neurosymbolic AI known as neural-symbolic integration within the broader context of AI research.
History of Neuro-symbolic AI
Neuro-symbolic AI has a long history. However, it remained a rather niche topic until recently when advances in deep learning and the availability of large datasets have led to a renewed interest in this area.
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