The emergence of Chat GPT has once again sparked a wave of information revolution in
generative artificial intelligence. This article provides a detailed overview of the development …

Introduction The emergence and application of generative artificial intelligence/large
language models (hereafter GenAI LLMs) have the potential for significant impact on the …

Seismic advances in generative AI algorithms for imagery, text, and other data types has led
to the temptation to use synthetic data to train next-generation models. Repeating this …

Colloquially speaking, image generation models based upon diffusion processes are
frequently said to exhibit''hallucinations''samples that could never occur in the training data …

The era of proliferation of large language and image generation models begs the question
of what happens if models are trained on the synthesized outputs of other models. The …

As AI model size grows, neural scaling laws have become a crucial tool to predict the
improvements of large models when increasing capacity and the size of original (human or …

The proliferation of generative models, combined with pretraining on web-scale data, raises
a timely question: what happens when these models are trained on their own generated …

AI progress is creating a growing range of risks and opportunities, but it is often unclear how
they should be navigated. In many cases, the barriers and uncertainties faced are at least …

Within the scaling laws paradigm, which underpins the training of large neural networks like
ChatGPT and Llama, we consider a supervised regression setting and establish the …

Generative artificial intelligence (AI) technologies and large models are producing realistic
outputs across various domains, such as images, text, speech, and music. Creating these …