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TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter

Neural Information Processing Systems

Recent progress in generative artificial intelligence (gen-AI) has enabled the generation of photo-realistic and artistically-inspiring photos at a single click, catering to millions of users online. To explore how people use gen-AI models such as DALLE and StableDiffusion, it is critical to understand the themes, contents, and variations present in the AI-generated photos.


Grok and the A.I. Porn Problem

The New Yorker

Elon Musk's X is living up to its name. Shortly after Elon Musk purchased Twitter, in 2022, he claimed that "removing child exploitation is priority #1." It was certainly a noble goal--social-media sites had become havens for distributing abusive materials, including child pornography and revenge porn, and there was perhaps no major platform as openly hospitable to such content as Twitter. Unlike Facebook, Instagram, and TikTok, which restricted nudity and pornographic videos, Twitter allowed users to post violent and "consensually produced adult content" to their feeds without consequence. Long before Musk's takeover, Twitter had positioned itself as anti-censorship, the "free-speech wing of the free-speech party," as Tony Wang, the general manager of Twitter in the U.K., once put it--less concerned with policing content than with providing a public square for users to express themselves freely.


2025 proved humanoid robots are here to stay. And fall down.

Popular Science

Their creators say it's the getting back up part that matters. A humanoid robot is carried by technicians after being knocked out in a kickboxing match at the World Humanoid Robot Games on August 15, 2025 in Beijing, China. Breakthroughs, discoveries, and DIY tips sent every weekday. Tech companies are collectively spending billions to turn the age old sci-fi trope of humanoid, general-purpose robots into reality. So far, that momentous effort has mostly produced staged performances, underwhelming demos, and of falling.


TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter

Neural Information Processing Systems

Recent progress in generative artificial intelligence (gen-AI) has enabled the generation of photo-realistic and artistically-inspiring photos at a single click, catering to millions of users online. To explore how people use gen-AI models such as DALLE and StableDiffusion, it is critical to understand the themes, contents, and variations present in the AI-generated photos. In this work, we introduce TWIGMA (TWItter Generative-ai images with MetadatA), a comprehensive dataset encompassing over 800,000 gen-AI images collected from Jan 2021 to March 2023 on Twitter, with associated metadata (e.g., tweet text, creation date, number of likes). Through a comparative analysis of TWIGMA with natural images and human artwork, we find that gen-AI images possess distinctive characteristics and exhibit, on average, lower variability when compared to their non-gen-AI counterparts. Additionally, we find that the similarity between a gen-AI image and natural images is inversely correlated with the number of likes. Finally, we observe a longitudinal shift in the themes of AI-generated images on Twitter, with users increasingly sharing artistically sophisticated content such as intricate human portraits, whereas their interest in simple subjects such as natural scenes and animals has decreased. Our analyses and findings underscore the significance of TWIGMA as a unique data resource for studying AI-generated images.


Five Things That Changed the Media in 2025

The New Yorker

A.I., of course--but there were also other, less obvious stories and trends that are going to shape how we understand the news. Media is a famously myopic and sclerotic industry. The big changes that take place within it often go unnoticed, at first, by the people who are paid to set its future course. Sometimes, the stuff that we in the industry miss out on is obvious to the rest of the world. We were not the first to notice, for example, that features and news stories were being cannibalized by social media, slowly at first, and then thoroughly.


Ruby Is Not a Serious Programming Language

WIRED

Ruby survives on affection, not utility. My little theory is that the concept of "imprinting" in psychology can just as easily be applied to programming: Much as a baby goose decides that the first moving life-form it encounters is its parent, embryonic programmers form ineradicable attachments to the patterns and quiddities of their first formative language. Because if/when the machines take over, we should at least speak their language. For many people, that language is Ruby. It's often credited with making programming "click"; imprintees speak of it with a certain indebtedness and affection.


The Shifting Landscape of Vaccine Discourse: Insights From a Decade of Pre- to Post-COVID-19 Vaccine Posts on Social Media

Gyawali, Nikesh, Caragea, Doina, Caragea, Cornelia, Mohammad, Saif M.

arXiv.org Artificial Intelligence

In this work, we study English-language vaccine discourse in social media posts, specifically posts on X (formerly Twitter), in seven years before the COVID-19 outbreak (2013 to 2019) and three years after the outbreak was first reported (2020 to 2022). Drawing on theories from social cognition and the stereotype content model in Social Psychology, we analyze how English speakers talk about vaccines on social media to understand the evolving narrative around vaccines in social media posts. To do that, we first introduce a novel dataset comprising 18.7 million curated posts on vaccine discourse from 2013 to 2022. This extensive collection-filtered down from an initial 129 million posts through rigorous preprocessing-captures both pre-COVID and COVID-19 periods, offering valuable insights into the evolution of English-speaking X users' perceptions related to vaccines. Our analysis shows that the COVID-19 pandemic led to complex shifts in X users' sentiment and discourse around vaccines. We observe that negative emotion word usage decreased during the pandemic, with notable rises in usage of surprise, and trust related emotion words. Furthermore, vaccine-related language tended to use more warmth-focused words associated with trustworthiness, along with positive, competence-focused words during the early days of the pandemic, with a marked rise in negative word usage towards the end of the pandemic, possibly reflecting a growing vaccine hesitancy and skepticism.



ColdGANs: Taming Language GANs with Cautious Sampling Strategies Supplementary Material

Neural Information Processing Systems

We used a single RTX 2080 Ti GPU. While T5-small underperforms its larger version, T5-11B, the latter has 11 billion parameters. Gabon and South Africa, are ranked 119th and 121st, respectively . ANSWER: 119th HUMAN: What is Gabon ' s ranking? ColdGAN: What is Gabon ' s rank on the HDI?