Posts in: Blog

JUL 17, 2020

In defense of weight-sharing for neural architecture search: an optimization perspective

By Misha Khodak, Liam Li

A geometry-aware approach to optimization for neural architecture search.

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JUN 24, 2020

How to Build an Enterprise Deep Learning Platform, Part Three

By David Hershey

See an enterprise deep learning platform in action that comprises Pachyderm for data management, Determined for model development and training, and Seldon Core for deployment.

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JUN 12, 2020

How to Structure your Code to Build a Scalable Deep Learning Model

By David Hershey

How you structure your machine learning codebase has a big impact on how easy it is to scale, including adding support for distributed training, hyperparameter tuning, and experiment tracking.

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MAY 27, 2020

How to Build an Enterprise Deep Learning Platform, Part Two

By David Hershey

How to build a deep learning platform with open source components to handle tasks such as training data management and versioning, scalable model training, and deployment.

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MAY 12, 2020

How to Build an Enterprise Deep Learning Platform, Part One

By David Hershey

There is an incredibly common story playing out in countless enterprises in 2020.

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MAY 07, 2020

Scale Your Model Development on a Budget With GCP Preemptible Instances

By Dave Troiano

With Determined you can cloud burst your deep learning training workloads on GCP’s cost-effective preemptible GPUs, in a way that is friendly to infrastructure teams and model developers alike.

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APR 20, 2020

Determined / SageMaker Comparison

By Sean Rowan

Determined AI and AWS SageMaker are both platforms that accelerate these Machine Learning Engineering workflows, but with key differences that we compare, in detail.

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APR 15, 2020

What Andreessen Horowitz Got Wrong About AI

By Evan Sparks

A Response To Andreessen Horowitz’s “The New Business Of AI”

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MAR 16, 2020

Distributed Deep Learning That Actually Works

By Aaron Harlap, Dimitris Papailiopoulos

In this post, we explore the reasons behind it and suggest paths towards scalable training that have the potential to reliably work out of the box.

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FEB 14, 2020

AI in the 2020s Must Get Greener—and Here’s How

By Ameet Talwalkar

The environmental impact of artificial intelligence (AI) has been a hot topic as of late—and I believe it will be a defining issue for AI this decade.

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