Neural Network Timeline - Temporal Simulation

1943

Warren McCulloch and Walter Pitts create a computational model for neural networks.

1958

Frank Rosenblatt designs the Perceptron, the first artificial neural network.

1969

Marvin Minsky and Seymour Papert publish "Perceptrons," highlighting limitations of single-layer neural networks.

1974

Paul Werbos develops backpropagation learning algorithm for multi-layer networks.

1980

Kunihiko Fukushima introduces Neocognitron, a hierarchical multi-layered neural network.

1982

John Hopfield popularizes Hopfield networks for associative memory and optimization problems.

1986

David Rumelhart, Geoffrey Hinton, and Ronald Williams publish influential work on backpropagation.

1989

Yann LeCun applies convolutional neural networks to handwritten digit recognition.

1997

Sepp Hochreiter and Jürgen Schmidhuber introduce Long Short-Term Memory (LSTM) networks.

2006

Geoffrey Hinton introduces deep belief networks, sparking renewed interest in deep learning.

2012

AlexNet wins ImageNet competition, demonstrating the power of deep convolutional networks.

2014

Ian Goodfellow introduces Generative Adversarial Networks (GANs).

2017

Google's AlphaGo Zero achieves superhuman performance in Go using reinforcement learning.

2020

OpenAI releases GPT-3, a large language model with 175 billion parameters.

2023

Development of the first quantum-entangled neural network.

Timeline Divergence Point

2028

Introduction of the Holographic Neural Interface (HNI) for direct brain-computer interaction.

2035

First successful implementation of a city-wide neural network for optimizing urban infrastructure.

2042

Launch of the Global Neural Network (GNN) for climate prediction and mitigation.

2050

Development of self-evolving neural networks capable of independent goal-setting and ethical decision-making.