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Advance environmental sustainability in clinical trials using AWS

AWS Machine Learning Blog

AWS can play a key role in enabling fast implementation of these decentralized clinical trials. By exploring these AWS powered alternatives, we aim to demonstrate how organizations can drive progress towards more environmentally friendly clinical research practices.

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AWS re:Invent 2019 Livestream

Data Science 101

AWS re:Invent 2019 starts today. It is a large learning conference dedicated to Amazon Web Services and Cloud Computing. Based upon the announcements last week , there will probably be a lot of focus around machine learning and deep learning.

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Fast and cost-effective LLaMA 2 fine-tuning with AWS Trainium

AWS Machine Learning Blog

In this post, we walk through how to fine-tune Llama 2 on AWS Trainium , a purpose-built accelerator for LLM training, to reduce training times and costs. We review the fine-tuning scripts provided by the AWS Neuron SDK (using NeMo Megatron-LM), the various configurations we used, and the throughput results we saw.

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Frugality meets Accuracy: Cost-efficient training of GPT NeoX and Pythia models with AWS Trainium

AWS Machine Learning Blog

In this post, we’ll summarize training procedure of GPT NeoX on AWS Trainium , a purpose-built machine learning (ML) accelerator optimized for deep learning training. M tokens/$) trained such models with AWS Trainium without losing any model quality. We’ll outline how we cost-effectively (3.2 billion in Pythia.

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AWS Inferentia2 builds on AWS Inferentia1 by delivering 4x higher throughput and 10x lower latency

AWS Machine Learning Blog

The size of the machine learning (ML) models––large language models ( LLMs ) and foundation models ( FMs )–– is growing fast year-over-year , and these models need faster and more powerful accelerators, especially for generative AI. With AWS Inferentia1, customers saw up to 2.3x With AWS Inferentia1, customers saw up to 2.3x

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Say Goodbye to Costly BERT Inference: Turbocharge with AWS Inferentia2 and Hugging Face…

Mlearning.ai

These Cores accelerate matrix operations and are specifically designed to boost deep learning training and inference performance. These Cores accelerate matrix operations and are specifically designed to boost deep learning training and inference performance. Inf1 accelerators can deliver up to 2.3x

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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. Together, these elements lead to the start of a period of dramatic progress in ML, with NN being redubbed deep learning. Thirdly, the presence of GPUs enabled the labeled data to be processed.

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