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Accelerate hyperparameter grid search for sentiment analysis with BERT models using Weights & Biases, Amazon EKS, and TorchElastic

AWS Machine Learning Blog

Transformer-based language models such as BERT ( Bidirectional Transformers for Language Understanding ) have the ability to capture words or sentences within a bigger context of data, and allow for the classification of the news sentiment given the current state of the world. Prior to AWS, he led AI Enterprise Solutions at Wells Fargo.

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Google Research, 2022 & beyond: Research community engagement

Google Research AI blog

We also support Responsible AI projects directly for other organizations — including our commitment of $3M to fund the new INSAIT research center based in Bulgaria. Dataset Description Auto-Arborist A multiview urban tree classification dataset that consists of ~2.6M

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Google’s Dr. Arsanjani on Enterprise Foundation Model Challenges

Snorkel AI

It came to its own with the creation of the transformer architecture: Google’s BERT, OpenAI, GPT2 and then 3, LaMDA for conversation, Mina and Sparrow from Google DeepMind. Others, toward language completion and further downstream tasks. So there’s obviously an evolution. Really quickly, LLMs can do many things.

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Google’s Arsanjani on Enterprise Foundation Model Challenges

Snorkel AI

It came to its own with the creation of the transformer architecture: Google’s BERT, OpenAI, GPT2 and then 3, LaMDA for conversation, Mina and Sparrow from Google DeepMind. Others, toward language completion and further downstream tasks. So there’s obviously an evolution. Really quickly, LLMs can do many things.

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Achieve high performance at scale for model serving using Amazon SageMaker multi-model endpoints with GPU

AWS Machine Learning Blog

In addition, load testing can help guide the auto scaling strategies using the right metrics rather than iterative trial and error methods. We tested two NLP models: bert-base-uncased (109M) and roberta-large (335M). NLP bert-base-uncased 109M PyTorch 26 62% 70 -39% 105 142% 140 29% TensorRT 42. Diff (%) CV CNN Resnet50 ml.g4dn.2xlarge

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