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Deploying Large NLP Models: Infrastructure Cost Optimization

The MLOps Blog

Models like for example ChatGPT, Gopher **(280B), GPT-3 (175B), Jurassic-1 (178B), and Megatron-Turing NLG (530B) are predominantly very large and often addressed as large language models or LLMs. Even if you are fine-tuning an average-sized model for a large-scale application, you need to muster a huge amount of data. Sure there is.

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Automatically redact PII for machine learning using Amazon SageMaker Data Wrangler

AWS Machine Learning Blog

Customers increasingly want to use deep learning approaches such as large language models (LLMs) to automate the extraction of data and insights. For many industries, data that is useful for machine learning (ML) may contain personally identifiable information (PII).

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Benchmark and optimize endpoint deployment in Amazon SageMaker JumpStart 

AWS Machine Learning Blog

When deploying a large language model (LLM), machine learning (ML) practitioners typically care about two measurements for model serving performance: latency, defined by the time it takes to generate a single token, and throughput, defined by the number of tokens generated per second.

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Welcome to a New Era of Building in the Cloud with Generative AI on AWS

AWS Machine Learning Blog

The bottom layer is the infrastructure to train Large Language Models (LLMs) and other Foundation Models (FMs) and produce inferences or predictions. We believe generative AI has the potential over time to transform virtually every customer experience we know. Innovative startups like Perplexity AI are going all in on AWS for generative AI.

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Announcing New Tools for Building with Generative AI on AWS

Flipboard

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses.

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Pinterest's Closeup Recommendations Engine

Bugra Akyildiz

Articles Airbnb's data management platform has evolved over the past 6 years. The platform started with Dataportal, which aimed to "democratize data" at Airbnb by enabling data users to find trusted data. Metis has been serving critical roles across data compliance, data reliability, and data quality initiatives.