As the free online encyclopedia turns 25, it's facing political opposition, AI scraping, dwindling volunteers, and a public that may no longer believe in its ideals. In 2010, the FBI sent Wikipedia a letter that would be intimidating for any organization to receive. The missive demanded that the free online encyclopedia remove the FBI's logo from an entry about the agency, claiming that reproducing the emblem was illegal and punishable with fines, imprisonment, "or both." Rather than back down, a lawyer for the Wikimedia Foundation, which hosts Wikipedia, shot back a sharp refusal outlining how the FBI's interpretation of the relevant statute was incorrect and saying that Wikipedia was "prepared to argue our view in court." It worked--the FBI dropped the matter.

A lot of people wanted to know who's dead. Wikipedia currently contains over 7.1 million entries in English alone. Breakthroughs, discoveries, and DIY tips sent six days a week. It's hard to imagine the internet without Wikipedia . But in the immediate years following its debut in 2001, many critics scoffed at the idea that a free, volunteer-run online encyclopedia could ever be considered a reputable source of information.

US shutdown ends: What happens next? New Epstein emails: What do they say about Trump? Last month, tech billionaire Elon Musk launched Grokipedia, an AI-powered platform, to rival online encyclopedia Wikipedia. "Grokipedia will exceed Wikipedia by several orders of magnitude in breadth, depth and accuracy," Musk posted on X the day after his site went live on October 27. Grokipedia will exceed Wikipedia by several orders of magnitude in breadth, depth and accuracy https://t.co/Nt4M6vqEZu

Booth is a reporter at TIME. Booth is a reporter at TIME. Jimmy Wales describes himself as a "pathological optimist." And yet, when the co-founder of Wikipedia spoke with TIME in October, he still seemed somewhat surprised that his online encyclopedia actually worked. "Wikipedia is very trusting, in a way that always seemed a bit crazy," Wales says.

Mark Zuckerberg announced in April that the company would make huge capital expenditures in the coming year to keep up in the race to develop cutting-edge artificial intelligence. He made good on that promise last week with a 15bn "AI superintelligence" team that would feature reported nine-figure salaries and a 49% investment in Scale AI. Before Meta's investment, Scale counted most of the major players in AI among its clients, and some of them were less than thrilled with the development. Bloomberg puts it succinctly: Scale AI's Wang Brings to Meta Knowledge of What Everyone Else is Doing. Google, Scale's largest customer, got scared.

Wikipedia has been struggling with the impact that AI crawlers -- bots that are scraping text and multimedia from the encyclopedia to train generative artificial intelligence models -- have been having on its servers, leading to increased costs and slower load times for human users in some cases. Perhaps in an effort to stop the bots from pummeling the public Wikipedia website and soaking up too much bandwidth, the Wikimedia Foundation (which manages Wikipedia's data) is offering AI developers a dataset they can freely use. The organization has teamed up with Kaggle, a data science platform, to offer up a beta release of a structured dataset in both English and French. According to Google -- which owns Kaggle -- the dataset is formatted for machine learning to make it more useful for training, development and data science. Wikimedia Enterprise notes that the dataset includes "abstracts, short descriptions, infobox-style key-value data, image links and clearly segmented article sections."

What do Taylor Swift, Andrew Tate and Robert Oppenheimer all have in common? They were the most searched articles on Wikipedia this year. The platform shared a fascinating report revealing the topics most interested people in English-speaking countries. Collectively, we racked up more than 84 billion views on Wikipedia this year. The site's page for ChatGPT was the top article, with more than 49 million views, following its breakout year that sparked curiosity and concern worldwide. Curiosity and concern also played a part in the second most viewed Wikipedia article of the year: 'Deaths in 2023' ' which HAD over 42 million views.

Welcome to Source Notes, a Future Tense column about the internet's information ecosystem. Wikipedia is, to date, the largest and most-read reference work in human history. But the editors who update and maintain Wikipedia are certainly not complacent about its place as the preeminent information resource, and are worried about how it might be displaced by generative A.I. At last week's Wikimania, the site's annual user conference, one of the sessions was "ChatGPT vs. WikiGPT," and a panelist at the event mentioned that rather than visiting Wikipedia, people seem to being going to ChatGPT for their information needs. Veteran Wikipedians have couched ChatGPT as an existential threat, predicting that A.I. chatbots will supplant Wikipedia in the same way that Wikipedia infamously dethroned Encyclopedia Britannica back in 2005.

Wikipedia is one of the most successful collaborative projects in history. It is the largest encyclopedia ever created, with millions of users worldwide relying on it as the first source of information as well as for fact-checking and in-depth research. As Wikipedia relies solely on the efforts of its volunteer-editors, its success might be particularly affected by toxic speech. In this paper, we analyze all 57 million comments made on user talk pages of 8.5 million editors across the six most active language editions of Wikipedia to study the potential impact of toxicity on editors' behaviour. We find that toxic comments consistently reduce the activity of editors, leading to an estimated loss of 0.5-2 active days per user in the short term. This amounts to multiple human-years of lost productivity when considering the number of active contributors to Wikipedia. The effects of toxic comments are even greater in the long term, as they significantly increase the risk of editors leaving the project altogether. Using an agent-based model, we demonstrate that toxicity attacks on Wikipedia have the potential to impede the progress of the entire project. Our results underscore the importance of mitigating toxic speech on collaborative platforms such as Wikipedia to ensure their continued success.

Overall, we explore the possibility of emergent behaviors in a multi-agent setting with a simple goal of predicting the next state of the game. By giving each cell agency with a convolutional neural network, we were able to explore more complex multi-agent behavior, giving each agent a short term memory in the form of convolutional parameters, and the ability to explore vs exploit their environment through their output movements. The goal was to explore the types of emerging behavior from groups of CNN agents with a selective pressure toward better predictions of the next state. Question In an environment where pixel agents are given mechanisms to self-replicate, compete, communicate, and predict, are these channels enough for the emergence of centralized control from distinct agents? Related Work This work was heavily inspired by the paper "Growing Neural Cellular Automata" 1, as well as by the original Game of Life by John Conway 2. The ResNet architecture was also borrowed and modified from this tutorial 3. Finally, the idea of a fitness value for the cells comes from the field of genetic algorithms. The guiding question and following philosophical implications are deeply connected to the works of Deleuze and Simondon among other philosophers and physicists. Assumptions Macroscopic wholes can emerge from discretized atomic agents Intelligent, accurate predictions of the world emerge from resource scarcity, thus a system requiring accurate predictions to grow imposes resource constraints correlated to those which life imposes on cell division and growth. We can model primordial selves with self replicating simplified agents given arbitrary, nonstationary bounds on themselves in the form of a pixel.