Left: Comparison of architectures where encoder-decoder creates a fixed input representation with KV cache only for output, while decoder-only requires growing KV caches for both input and output. Top ...

While pretrained encoders have achieved success in various natural language understanding (NLU) tasks, there is a gap between these pretrained encoders and natural language generation (NLG). NLG tasks ...

The typical encoder-decoder architecture used by USM can include a CTC, RNN-T, or LAS decoder as the decoder. USM employs the Conformer, a convolution-augmented transformer, as the encoder. The ...

TensorRT-LLM has long been a critical tool for optimizing inference in models such as decoder-only architectures like Llama 3.1, mixture-of-experts models like Mixtral, and selective state-space ...

In November 2022, Google announced its 1,000 Languages Initiative, which aims to develop an artificial intelligence model that can support the 1,000 most widely spoken languages.As part of this ...