Seq2seq is a family of machine learning approaches used for natural language processing. Applications include language translation, image captioning,...

he established with others from Google. He co-invented the doc2vec and seq2seq models in natural language processing. Le also initiated and lead the AutoML...

language models. At the time, the focus of the research was on improving Seq2seq techniques for machine translation, but even in their paper the authors...

approach instead of older, statistical approaches. In 2014, a 380M-parameter seq2seq model for machine translation using two Long short-term Memory (LSTMs)...

"Attention Is All You Need". This paper's goal was to improve upon 2014 Seq2seq technology, and was based mainly on the attention mechanism developed by...

to 1022 FLOPs) of compute which was 1.5 orders of magnitude larger than Seq2seq model of 2014 (but about 2x smaller than GPT-J-6B in 2021). Google Translate's...

Machine Translation Architectures". arXiv:1703.03906 [cs.CV]. "Pytorch.org seq2seq tutorial". Retrieved December 2, 2021. Bahdanau, Dzmitry; Cho, Kyunghyun;...

of Electrical Engineering and Computer Science. Vinyals co-invented the seq2seq model for machine translation along with Ilya Sutskever and Quoc Viet Le...

inability to capture sequential data, which later led to developments of Seq2seq approaches, which include recurrent neural networks which made use of long...

synthesis, spectrogram (or spectrogram in mel scale) is first predicted by a seq2seq model, then the spectrogram is fed to a neural vocoder to derive the synthesized...