how-to-control-access-in-llm-data-plus-distributed-authorization 
The MLOps Blog
MARCH 23, 2023
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.
AWS Machine Learning Blog
OCTOBER 19, 2023
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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AWS Machine Learning Blog
JANUARY 29, 2024
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.
AWS Machine Learning Blog
NOVEMBER 30, 2023
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.
APRIL 13, 2023
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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