Language understanding
AI milestones in language understanding, part of ai research.
4 milestones
Microsoft Research released Turing Natural Language Generation (T-NLG), a 17-billion-parameter language model
In February 2020, Microsoft Research announced Turing Natural Language Generation (T-NLG), a 17-billion-parameter autoregressive language model trained using the Megatron-LM framework. At the time of release it was the largest publicly disclosed language model and achieved state-of-the-art results on question-answering and summarisation benchmarks.
Andrew M. Dai and Quoc V. Le Introduced Semi-Supervised Sequence Learning
In November 2015, Andrew M. Dai and Quoc V. Le at Google Brain published 'Semi-Supervised Sequence Learning', showing that pre-training recurrent neural networks with unsupervised objectives, language modelling or sequence autoencoding, before supervised fine-tuning improved text classification accuracy and training stability, anticipating the pre-train-then-fine-tune paradigm later adopted widely in NLP.
Jabberwacky Chatbot Developed by Rollo Carpenter
In 1988, British programmer Rollo Carpenter began developing Jabberwacky, a chatbot that simulated conversation by storing and retrieving lines from prior user exchanges rather than using fixed scripted responses, with the aim of exploring machine-based natural language interaction.
HAM-ANS Natural Language Dialog System (University of Hamburg, 1983)
In 1983, Wolfgang Hoeppner, Katharina Morik, and Heinz Marburger at the University of Hamburg presented HAM-ANS, a natural language dialog system enabling users to query databases in ordinary German, demonstrated at the GWAI-83 workshop and published in Springer's Lecture Notes in Computer Science series.