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Bernard Widrow and Marcian Hoff built MADALINE at Stanford in 1962, taking neural networks beyond the perceptron's limitations.
In 1991, IBM researchers changed machine translation by introducing the first broad statistical approach.
In 1995, RNNs changed sequence processing by introducing neural networks with memory: connections.
Hochreiter and Schmidhuber introduced LSTMs in 1997 to address vanishing gradients. Covers gated memory, long context, and later sequence models.
In the 1980s, neural networks hit a wall: nobody knew how to train deep models. That changed when Rumelhart, Hinton.
In the mid-1990s, Princeton University released WordNet, a major lexical database.
In 1988, Yann LeCun introduced Convolutional Neural Networks at Bell Labs, forever changing how machines process visual information.
In 1987, Slava Katz solved one of statistical language modeling's biggest problems. When your model encounters word sequences it has never seen before.
In 1987, Alex Waibel introduced Time Delay Neural Networks, a major architecture that changed how neural networks process sequential data.
Covers OpenAI's ChatGPT release in 2022, including the conversational interface, RLHF training approach, safety measures.
Covers XLM (Cross-lingual Language Model) introduced by Facebook AI Research in 2019. Explains how cross-lingual pretraining.
Covers long context language models introduced in 2024. Explains how models achieved 1M+ token context windows through efficient attention mechanisms.
In 2004, ROUGE and METEOR addressed critical limitations in BLEU's evaluation approach.
The Penn Treebank established large tagged corpora for statistical NLP, enabling comparable research in part-of-speech tagging and syntactic parsing.
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