Chatting about ChatGPT: how may AI and GPT impact academia and libraries?
Purpose This paper aims to provide an overview of key definitions related to ChatGPT, a
public tool developed by OpenAI, and its underlying technology, Generative Pretrained …
public tool developed by OpenAI, and its underlying technology, Generative Pretrained …
ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing
This article discusses OpenAI's ChatGPT, a generative pre‐trained transformer, which uses
natural language processing to fulfill text‐based user requests (ie, a “chatbot”). The history …
natural language processing to fulfill text‐based user requests (ie, a “chatbot”). The history …
A survey on model compression for large language models
Abstract Large Language Models (LLMs) have transformed natural language processing
tasks successfully. Yet, their large size and high computational needs pose challenges for …
tasks successfully. Yet, their large size and high computational needs pose challenges for …
On the opportunities and risks of foundation models
AI is undergoing a paradigm shift with the rise of models (eg, BERT, DALL-E, GPT-3) that are
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
trained on broad data at scale and are adaptable to a wide range of downstream tasks. We …
Towards the systematic reporting of the energy and carbon footprints of machine learning
Accurate reporting of energy and carbon usage is essential for understanding the potential
climate impacts of machine learning research. We introduce a framework that makes this …
climate impacts of machine learning research. We introduce a framework that makes this …
Rethinking embedding coupling in pre-trained language models
We re-evaluate the standard practice of sharing weights between input and output
embeddings in state-of-the-art pre-trained language models. We show that decoupled …
embeddings in state-of-the-art pre-trained language models. We show that decoupled …
Counting carbon: A survey of factors influencing the emissions of machine learning
AS Luccioni, A Hernandez-Garcia - arXiv preprint arXiv:2302.08476, 2023 - arxiv.org
Machine learning (ML) requires using energy to carry out computations during the model
training process. The generation of this energy comes with an environmental cost in terms of …
training process. The generation of this energy comes with an environmental cost in terms of …
An exploratory literature study on sharing and energy use of language models for source code
Context: Large language models trained on source code can support a variety of software
development tasks, such as code recommendation and program repair. Large amounts of …
development tasks, such as code recommendation and program repair. Large amounts of …
Carburacy: summarization models tuning and comparison in eco-sustainable regimes with a novel carbon-aware accuracy
Generative transformer-based models have reached cutting-edge performance in long
document summarization. Nevertheless, this task is witnessing a paradigm shift in …
document summarization. Nevertheless, this task is witnessing a paradigm shift in …
Iot in the era of generative ai: Vision and challenges
Equipped with sensing, networking, and computing capabilities, Internet of Things (IoT) such
as smartphones, wearables, smart speakers, and household robots have been seamlessly …
as smartphones, wearables, smart speakers, and household robots have been seamlessly …