How Uber Uses PyTorch

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...

This article discusses how Uber has integrated explainability into its machine learning platform, Michelangelo, using Integrated Gradients (IG) to provide interpretable attributions for deep learni...

The article discusses how Uber optimizes the training of Large Language Models (LLMs) using both open-source and in-house models.

The article discusses Uber's evolution in machine learning (ML) through its centralized platform, Michelangelo, highlighting its transition from predictive to generative AI.

The article discusses the integration of Elastic Horovod with Ray, focusing on how this combination enhances distributed deep learning training by enabling autoscaling and fault tolerance.

Horovod v0. 21 introduces significant enhancements aimed at optimizing network utilization for distributed deep learning training.

The article introduces Neuropod, an open-source deep learning inference engine developed by Uber's Advanced Technologies Group (ATG).

The article discusses Uber ATG's machine learning infrastructure and versioning control platform, VerCD, designed to manage the complexities of developing self-driving vehicles.

The article discusses Uber's open source initiatives in 2019, highlighting the company's contributions to the open source community, the establishment of the Open Source Program Office (OSPO), and ...

The article introduces DMM-Net, a differentiable mask-matching network designed for video instance segmentation.

The article introduces Hypothesis GU Func, an open-source Python package designed to facilitate unit testing for machine learning models, particularly those using NumPy and PyTorch.

EvoGrad is a lightweight Python library designed to facilitate gradient-based evolution in machine learning.

The article introduces the Plato Research Dialogue System, a flexible conversational AI platform developed by Uber AI.

The article features an interview with Fritz Obermeyer and Noah Goodman from Uber AI, discussing the significance of Pyro, an open-source deep probabilistic programming language.

The article discusses the latest updates to Horovod, a distributed deep learning framework, which now includes support for PySpark and Apache MXNet, along with features aimed at enhancing training ...

The article discusses the modeling of censored time-to-event data using Pyro, an open-source probabilistic programming language.

The First Uber Science Symposium brought together experts from various fields to discuss advancements in reinforcement learning (RL), natural language processing (NLP), conversational AI, and deep ...

The article introduces Ludwig, an open-source deep learning toolbox developed by Uber that allows users to train and test deep learning models without writing code.

The article reviews Uber's open source initiatives in 2018, highlighting the diversity of projects and their impact on the technical community.

The article introduces Alex Sergeev, the lead of the Horovod project at Uber, detailing the motivations behind open sourcing Horovod, a distributed deep learning framework.

Horovod, Uber's open-source distributed training framework, has joined the LF Deep Learning Foundation, enhancing its support for open-source innovation in AI and deep learning.

The article discusses an innovative approach to enhance the performance of Convolutional Neural Networks (CNNs) by utilizing JPEG's internal representations.

The article introduces the Metropolis-Hastings GAN (MH-GAN), a novel approach to enhance Generative Adversarial Networks (GANs) by leveraging the discriminator for improved sample selection.

The article discusses how NVIDIA leverages Uber's Horovod to enhance the training of deep learning models for autonomous vehicles.

The article discusses Peloton, Uber's unified resource scheduler designed to manage diverse cluster workloads efficiently.

The article highlights seven open source projects showcased at the Uber Open Summit, emphasizing Uber's contributions to the open source community.

The article introduces Michelangelo PyML, Uber's platform designed for rapid Python machine learning model development.

The article announces the Uber Open Summit 2018, emphasizing the importance of open source collaboration in Uber's growth.

The article introduces Petastorm, an open-source data access library developed by Uber's Advanced Technologies Group (ATG) for facilitating deep learning model training and evaluation directly from...

The article highlights Uber's contributions to the open source community in 2017, showcasing several key projects that enhance software development and engineering practices.