Google Research AI blog

FEBRUARY 14, 2023

Behind both language models and many of our robotics learning approaches, like RT-1 , are Transformers , which allow models to make sense of Internet-scale data. In 2020, we introduced Performers as an approach to make Transformers more computationally efficient, which has implications for many applications beyond robotics.

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AssemblyAI

NOVEMBER 8, 2023

This aligns with the scaling laws observed in other areas of deep learning, such as Automatic Speech Recognition and Large Language Models research. New Models The development of our latest models for Punctuation Restoration and Truecasing marks a significant evolution from the previous system. Susanto et al., Mayhew et al.,

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Flipboard

JANUARY 15, 2025

System architecture for GNN-based network traffic prediction In this section, we propose a system architecture for enhancing operational safety within a complex network, such as the ones we discussed earlier. Specifically, we employ GraphStorm within an AWS environment to build, train, and deploy graph models.

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