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 …

There is great interest in how the growth of artificial intelligence and machine learning may
affect global GHG emissions. However, such emissions impacts remain uncertain, owing in …

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 …

The advent of generative artificial intelligence (AI) offers transformative potential in the field
of education. The study explores three main areas:(1) How did ChatGPT answer questions …

We study the design decision of publicly available instruction tuning methods, by
reproducing and breaking down the development of Flan 2022 (Chung et al., 2022) …

Abstract Trustworthy Artificial Intelligence (AI) is based on seven technical requirements
sustained over three main pillars that should be met throughout the system's entire life cycle …

Progress in machine learning (ML) comes with a cost to the environment, given that training
ML models requires computational resources, energy and materials. In the present article …

Driven by the goal of eradicating language barriers on a global scale, machine translation
has solidified itself as a key focus of artificial intelligence research today. However, such …

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 …

Generative AI systems across modalities, ranging from text, image, audio, and video, have
broad social impacts, but there exists no official standard for means of evaluating those …