It has been awarded jointly to John Hopfield & Geoffrey Hinton for constructing methods that helped lay foundation for machine learning (A type of AI) using ANNs.
What are ANNs?
- ANNs are a subset of Machine Learning algorithms designed to model workings of human brain.
- ANNs consist of interconnected nodes, or artificial neurons, that process information similarly to how neurons function in the human brain.
Discoveries
- John Hopfield: He invented a type of neural network (Hopfield Network) which is designed to store and recall patterns, similar to how memory works.
- Hopfield network utilizes physics that describes a material’s characteristics due to its atomic spin.
- Atomic spin is magnetic moment of an atom that is caused by spins of particles that make up atoms.
- Hopfield network utilizes physics that describes a material’s characteristics due to its atomic spin.
- Geoffrey Hinton: He invented a method (Boltzman Machine) that can autonomously find properties in data e.g. identifying specific elements in pictures.
- Boltzmann machine learns by using examples that it may see while it works. It can sort images or create new patterns similar to what it learned.
- This network uses methods from statistical physics.
- Boltzmann machine learns by using examples that it may see while it works. It can sort images or create new patterns similar to what it learned.
Role of ANNs in AI
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