With the ever‐growing adoption of artificial intelligence (AI)‐based systems, the carbon
footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to …

Artificial intelligence and machine learning (AI/ML) models have been adopted in a wide
range of healthcare applications, from medical image computing and analysis to continuous …

In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large
language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine …

This article presents a comprehensive and practical guide for practitioners and end-users
working with Large Language Models (LLMs) in their downstream Natural Language …

Recent years have seen a surge in the popularity of commercial AI products based on
generative, multi-purpose AI systems promising a unified approach to building machine …

Language models (LMs) have become ubiquitous in both NLP research and in commercial
product offerings. As their commercial importance has surged, the most powerful models …

Much of the evaluation and tuning of a search system relies on relevance labels---
annotations that say whether a document is useful for a given search and searcher. Ideally …

We introduce MOMENT, a family of open-source foundation models for general-purpose
time series analysis. Pre-training large models on time series data is challenging due to (1) …

Generative AI, exemplified in ChatGPT, Dall-E 2, and Stable Diffusion, are exciting new
applications consuming growing quantities of computing. We study the compute, energy …

The carbon footprint associated with large language models (LLMs) is a significant concern,
encompassing emissions from their training, inference, experimentation, and storage …