How Uber Uses Transformers
12 engineering articles about Transformers from Uber's engineering team
Other Uber Technologies
Other Companies Using Transformers
Articles
Filter:
The article discusses the evolution and scaling of Uber's Delivery Search Platform, emphasizing the transition from traditional lexical search to a semantic search model that enhances user experien...
Divya Nagar, Zheng Liu, Jiasen Xu, Bo Ling, Haoyang Chen
11 min read
Has Summary
--
This article discusses the development and implementation of forecasting models aimed at improving driver availability at airports, which are critical to Uber's ridesharing ecosystem.
Bob Zheng, Dhruv Ghulati, Manoj Panikkar, Michael (Yichuan) Cai
15 min read
Has Summary
--
The article discusses how Uber optimizes the training of Large Language Models (LLMs) using both open-source and in-house models.
ApacheApache KafkaApache SparkCometDockerGoogle CloudGPTGPT-4Hugging FaceKubernetesMistralPyTorchSQLTransformers
Bo Ling, Jiapei Huang, Baojun Liu, Chongxiao Cao, Anant Vyas, Peng Zhang
11 min read
Has Summary
--
The article discusses DeepETA, Uber's advanced model for predicting arrival times using deep learning techniques.
ApacheApache SparkComputer VisionDeep LearningMachine LearningSelf-AttentionTensorFlowTransformerTransformersXGBoost
Xinyu Hu, Olcay Cirit, Tanmay Binaykiya, Ramit Hora
15 min read
Has Summary
--
The article discusses the integration of Elastic Distributed Training with XGBoost on Ray, highlighting how this approach addresses challenges in distributed machine learning at scale.
Michael Mui, Xu Ning, Kai Fricke, Amog Kamsetty, Richard Liaw
19 min read
Has Summary
--
Ludwig version 0. 3 introduces significant enhancements, including hyperparameter optimization, support for Transformers, and integration with TensorFlow 2.
Kerri Brown, Piero Molino, Yaroslav Dudin
10 min read
Has Summary
--
The article discusses the challenges and solutions involved in productionizing distributed XGBoost for training deep tree models on large datasets at Uber.
Joseph Wang, Anne Holler, Mingshi Wang, Michael Mui
14 min read
Has Summary
--
The article discusses the Plug and Play Language Model (PPLM), a novel approach to controlled text generation that allows users to steer large, pre-trained language models without the need for retr...
Rosanne Liu, Sumanth Dathathri, Andrea Madotto, Piero Molino, Jason Yosinski
19 min read
Has Summary
--
The article discusses the evolution of the Michelangelo model representation at Uber to enhance flexibility and scalability in machine learning model serving.
Anne Holler, Michael Mui
15 min read
Has Summary
--
The article discusses three innovative approaches to scaling machine learning at Uber, specifically from the Seattle Engineering team.
Lucy
3 min read
Has Summary
--
Ludwig v0. 2 introduces significant enhancements to its deep learning toolbox, including new features such as Comet.
Piero Molino, Yaroslav Dudin, Sai Sumanth Miryala
10 min read
Has Summary
--
The article discusses the scaling of Uber's Customer Support Ticket Assistant (COTA) system using deep learning techniques.
Huaixiu Zheng, Guoqin Zheng, Naveen Somasundaram, Basab Maulik, Hugh Williams, Jeremy Hermann
15 min read
Has Summary
--
You've reached the end! All 12 articles loaded.