Welcome to our latest roundup of what's going on in the indie game space. There are tons of interesting games out this week. But first, there's been some discourse around the Nintendo Switch version of, which arrived this week as well. On other platforms, there's an option to censor genitalia and other explicit content, but that's not present in the Switch version. Instead, such content is censored by default, with black rectangles covering up characters' bits and someone flipping the bird.

A quarter century ago, Wikipedia's decentralized, crowdsourced, and consensus-driven model replaced the centralized, expert-driven, and authority-based standard for encyclopedic knowledge curation. The emergence of generative AI encyclopedias, such as Grokipedia, possibly presents another potential shift in epistemic evolution. This study investigates whether AI- and human-curated encyclopedias rely on the same foundations of authority. We conducted a multi-scale comparative analysis of the citation networks from 72 matched article pairs, which cite a total of almost 60,000 sources. Using an 8-category epistemic classification, we mapped the "epistemic profiles" of the articles on each platform. Our findings reveal several quantitative and qualitative differences in how knowledge is sourced and encyclopedia claims are epistemologically justified. Grokipedia replaces Wikipedia's heavy reliance on peer-reviewed "Academic & Scholarly" work with a notable increase in "User-generated" and "Civic organization" sources. Comparative network analyses further show that Grokipedia employs very different epistemological profiles when sourcing leisure topics (such as Sports and Entertainment) and more societal sensitive civic topics (such as Politics & Conflicts, Geographical Entities, and General Knowledge & Society). Finally, we find a "scaling-law for AI-generated knowledge sourcing" that shows a linear relationship between article length and citation density, which is distinct from collective human reference sourcing. We conclude that this first implementation of an LLM-based encyclopedia does not merely automate knowledge production but restructures it. Given the notable changes and the important role of encyclopedias, we suggest the continuation and deepening of algorithm audits, such as the one presented here, in order to understand the ongoing epistemological shifts.

W hen the first ever stage adaptation of the global book and film franchise The Hunger Games opens its doors in London next week, fans paying up to £200 have been promised an "electrifying" and "immersive" experience. The show at the purpose-built 1,200 seat Troubadour in Canary Wharf, which features Hollywood A-lister John Malkovich appearing via screen as the evil President Snow who oversees the televised spectacle of teenagers fighting to the death, is the latest in an explosion of launches looking to cash in on a boom in consumer demand for experiential entertainment, often linked to bankable franchises. The boom in the market for experimental, unusual nights out and shows is well established, from escape rooms, axe throwing and slumber parties to Secret Cinema's Olympic Park takeover to recreate the setting for Back to the Future and the hugely successful Abba Voyage. Recent pop-ups include experiences linked to Minecraft, Jurassic World and Squid Game. As big money has rolled into the sector, so too has a desire from companies to rely on solid gold intellectual property to bring in the crowds - with mixed results.

OpenAI's latest app encourages users to generate a personal digital avatar and scroll AI-generated videos of themselves and their friends. On Tuesday, OpenAI released an AI video app called Sora . The platform is powered by OpenAI's latest video generation model, Sora 2, and revolves around a TikTok-like For You page of user-generated clips. This is the first product release from OpenAI that adds AI-generated sounds to videos. For now, it's available only on iOS and requires an invite code to join.

Video Games The Buzziest Video Game of the Year Is Here. Sometimes, in our modern world where every Goliath wants to be seen as a David, where the middle class is evaporating and the working class is crushed and the wealthy play victim, the little guy still manages to win. Sometimes the little guy even wins big. And then sometimes the little guy wins, in a manner that destabilizes a flailing industry, upends media coverage, and incites multiple minor culture wars. That's how it went for Ari Gibson and William Pellen, a pair of Australian game developers known collectively as Team Cherry, who last week released the only video game that every gamer is talking about right now: .

After school, Karandeep Anand often finds his 6-year-old daughter deep in conversation with an AI chatbot as she eats snacks at their kitchen counter. She's too young to type--let alone have her own account on Character.AI--but that hasn't stopped her from nabbing his phone to have voice conversations with a Sherlock Holmes bot, which she uses to build her own mystery stories. Character.AI is an AI companion startup (though Anand likes to say it's an AI role-play startup, which we'll get into later). He took over as the CEO in June in the midst of a potentially devastating lawsuit for its parent company and looming questions about child safety. When I ask if he's concerned about his daughter connecting with an AI chatbot rather than a real human, he's quick to say no.

In the human-bot symbiotic information ecosystem, social bots play key roles in spreading and correcting disinformation. Understanding their influence is essential for risk control and better governance. However, current studies often rely on simplistic user and network modeling, overlook the dynamic behavior of bots, and lack quantitative evaluation of correction strategies. To fill these gaps, we propose MADD, a Multi Agent based framework for Disinformation Dissemination. MADD constructs a more realistic propagation network by integrating the Barabasi Albert Model for scale free topology and the Stochastic Block Model for community structures, while designing node attributes based on real world user data. Furthermore, MADD incorporates both malicious and legitimate bots, with their controlled dynamic participation allows for quantitative analysis of correction strategies. We evaluate MADD using individual and group level metrics. We experimentally verify the real world consistency of MADD user attributes and network structure, and we simulate the dissemination of six disinformation topics, demonstrating the differential effects of fact based and narrative based correction strategies.

Corey Feldman discusses his movie "The Birthday," which wrapped in 2004. "The Goonies" star Corey Feldman is concerned that the rise of artificial intelligence could ruin the "magic" of Hollywood filmmaking. In a new interview with Fox News Digital, the entertainer talked about his decades of being part of the film industry and what he thinks of it today compared to how it was when he was starring in beloved 80s classics like "Goonies," "The Lost Boys" and "The Burbs." When asked if he believes modern Hollywood can still conjure up the same "magic" that led to the creation of these iconic films, he said he wasn't so sure. "Well, I share the opinion that there is a lot of the magic that's been lost because of A.I., because of CGI, because of, you know, these things kind of taking over from the good stories, the great characters that we draw, the great writing," Feldman said.

The video game industry loves to tout figures: record-breaking sales numbers, astonishing revenue growth, dazzling quantities of concurrent players. It makes sense that the people who make and play games love numbers: They're proof that someone is winning. We have a new incredible number from the world of video games: In spite of an alarming price tag, it took only four days for the Nintendo Switch 2 to become the fastest-selling home video game console of all time, with 3.5 million units sold over the weekend following its June 5 release. This is tremendous business, enough for investors to take note and consider Nintendo a safe haven in a moment of extreme economic volatility. This kind of success is typically a point of pride to proponents of the video game industry, hard data proving the medium's significance to any doubters.

The performance of large language models (LLMs) is significantly affected by the quality and composition of their pre-training data, which is inherently diverse, spanning various domains, sources, and topics. Effectively integrating these heterogeneous data sources is crucial for optimizing LLM performance. Previous research has predominantly concentrated on domain-based data mixing, often neglecting the nuanced topic-level characteristics of the data. To address this gap, we propose a simple yet effective topic-based data mixing strategy that utilizes fine-grained topics generated through our topic modeling method, DataWeave. DataWeave employs a multi-stage clustering process to group semantically similar documents and utilizes LLMs to generate detailed topics, thereby facilitating a more nuanced understanding of dataset composition. Our strategy employs heuristic methods to upsample or downsample specific topics, which significantly enhances LLM performance on downstream tasks, achieving superior results compared to previous, more complex data mixing approaches. Furthermore, we confirm that the topics Science and Relationships are particularly effective, yielding the most substantial performance improvements. We will make our code and datasets publicly available.