Abstract: While early AutoML frameworks focused on optimizing traditional ML pipelines and their hyperparameters, a recent trend in AutoML is to focus on neural architecture search. In this paper, we ...

Google has reportedly initiated the TorchTPU project to enhance support for the PyTorch machine learning framework on its tensor processing units (TPUs), aiming to challenge the software dominance of ...

Google's TorchTPU aims to enhance TPU compatibility with PyTorch Google seeks to help AI developers reduce reliance on Nvidia's CUDA ecosystem TorchTPU initiative is part of Google's plan to attract ...

You: Have an Apple Silicon Mac (M1, M2, M1 Pro, M1 Max, M1 Ultra) and would like to set it up for data science and machine learning. This repo: Helps you install ...

Forbes contributors publish independent expert analyses and insights. Originally developed by Anyscale, Ray is an open source distributed computing framework for AI workloads, including data ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

The choice between PyTorch and TensorFlow remains one of the most debated decisions in AI development. Both frameworks have evolved dramatically since their inception, converging in some areas while ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

Abstract: Machine Learning models based on Deep Neural Networks behave unpredictably when presented with inputs that do not stem from the training distribution and sometimes make egregiously wrong ...

I'm working with your PyTorch version of this (zcemycl/PyTorch-DeepFloorplan), and is thinking if I should implement it with a ResNet50 backbone. I'm a bit new to CNNs, and is wondering if using ...