Relations (1)
related 2.00 — strongly supporting 3 facts
Machine learning and artificial neural networks are intrinsically linked as core components of connectionist AI [1] and are foundational technologies recognized together in the work of Geoffrey Hinton [2]. Furthermore, both are utilized in tandem to optimize complex systems like thermal energy storage [3].
Facts (3)
Sources
RAG Using Knowledge Graph: Mastering Advanced Techniques procogia.com 1 fact
claimGeoffrey Hinton is widely regarded as the 'godfather of AI' and shared the Nobel Prize with John J. Hopfield for foundational discoveries and inventions that enable machine learning with artificial neural networks.
The Synergy of Symbolic and Connectionist AI in LLM ... arxiv.org 1 fact
claimConnectionist AI is a paradigm that focuses on neural networks and machine learning algorithms, drawing influence from cognitive science and computational neuroscience to identify patterns and glean insights from datasets.
Global perspectives on energy technology assessment and ... link.springer.com 1 fact
claimArtificial intelligence optimizes thermal energy storage (TES) by improving capacity, efficiency, and cost-effectiveness through the use of machine learning, evolutionary algorithms, and neural networks.