Remove 2020 Remove Deep Learning Remove System Architecture
article thumbnail

Google Research, 2022 & beyond: Robotics

Google Research AI blog

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.

Algorithm 139
article thumbnail

Introducing Our New Punctuation Restoration and Truecasing Models

AssemblyAI

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.,

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Ask HN: Who wants to be hired? (July 2025)

Hacker News

Or if you have a team of greybeards doing HPC/systems programming and you're looking for some young blood, I am a very quick learner, and very eager to learn. Strong in system architecture, developer tooling, and cross-functional collaboration. Some: React, IoT, bit o elm, ML, LLM ops and auotmation.

Python 55
article thumbnail

Mitigating risk: AWS backbone network traffic prediction using GraphStorm

Flipboard

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.

AWS 135