The Twitch streamer could pivot from influencer to candidate. But he tells WIRED's podcast he'd rather use his platform to tell Dems "you can't podcast your way out of this problem." Hasan Piker is many things to many people. They don't all feel the same way about Piker or his politics, but most presumably agree on one thing: He is a relentless human being. Most days a week, you can find the 34-year-old Twitch streamer talking to his audience, often for six to nine hours at a stretch. And during President Trump's second term, there's plenty of that to go around. He has nearly 3 million followers on Twitch and has hosted conversations with Senator Bernie Sanders and US representative Alexandria Ocasio-Cortez. He claims his election night stream in 2024 reached a staggering 7.5 million viewers. On this episode of, I talked to Piker about his looks, his love of Italian sandwiches, and any future political aspirations he might (or might not) want to tease. It's great to be here. I heard you were just at the gym. Yeah, I was at the park. Some days I take my dog and I play a little bit of basketball and get to hang out with some people.

To meet the demands of content moderation, online platforms have resorted to automated systems. Newer forms of real-time engagement($\textit{e.g.}$, users commenting on live streams) on platforms like Twitch exert additional pressures on the latency expected of such moderation systems. Despite their prevalence, relatively little is known about the effectiveness of these systems. In this paper, we conduct an audit of Twitch's automated moderation tool ($\texttt{AutoMod}$) to investigate its effectiveness in flagging hateful content. For our audit, we create streaming accounts to act as siloed test beds, and interface with the live chat using Twitch's APIs to send over $107,000$ comments collated from $4$ datasets. We measure $\texttt{AutoMod}$'s accuracy in flagging blatantly hateful content containing misogyny, racism, ableism and homophobia. Our experiments reveal that a large fraction of hateful messages, up to $94\%$ on some datasets, $\textit{bypass moderation}$. Contextual addition of slurs to these messages results in $100\%$ removal, revealing $\texttt{AutoMod}$'s reliance on slurs as a moderation signal. We also find that contrary to Twitch's community guidelines, $\texttt{AutoMod}$ blocks up to $89.5\%$ of benign examples that use sensitive words in pedagogical or empowering contexts. Overall, our audit points to large gaps in $\texttt{AutoMod}$'s capabilities and underscores the importance for such systems to understand context effectively.

Nvidia is mighty proud of G-Assist, its new "AI" companion that runs on top of an active game and helps you out with tips or hardware adjustments. Now, it looks like the company is preparing to expand its capabilities. A new plugin-making system and several examples are already letting the tool's tendrils expand to other services. While standard developers can already use the G-Assist API, Nvidia is hoping that more regular users will get in on the action, and has made a Plugin Builder to achieve this. Using ChatGPT's generative code capabilities, it allows even a complete novice to "vibe code" and connect it with anything that also has an open API or a similar setup.

If Claude Plays Pokémon is supposed to offer a glimpse of AI's future, it's not a very convincing showcase. For the past month and counting, Twitch has watched Anthropic's chatbot struggle to play Pokémon Red. Across multiple runs, Claude has failed to beat the nearly 30 year old game. And yet for David Hershey, the project's lead developer, the showcase has been a success. "I wanted some place where I could understand how Claude handles situations where it needs to work over a very long period of time," Hershey explains to me over a video call.

We present a novel digital humanities method for representing our Twitch chatters as user embeddings created by a large language model (LLM). We cluster these embeddings automatically using affinity propagation and further narrow this clustering down through manual analysis. We analyze the chat of one stream by each Twitch streamer: SmallAnt, DougDoug and PointCrow. Our findings suggest that each streamer has their own type of chatters, however two categories emerge for all of the streamers: supportive viewers and emoji and reaction senders. Repetitive message spammers is a shared chatter category for two of the streamers.

Vice-presidential candidate Tim Walz and Congresswoman Alexandria Ocasio-Cortez on Sunday streamed themselves playing an American football video game against each other on Sunday as the two Democrats continued their party's efforts to secure votes from young men just nine days before the White House election. During the stream of their showdown on the latest edition of the Madden game series, Ocasio-Cortez and Walz exalted the importance of regaining Democratic control of the US House, maintaining a majority in the Senate and ensuring Kamala Harris wins the 5 November presidential election against Donald Trump. "We don't all share the same politics, we don't all share the same views, but the need to defeat Trump this year has been my number one priority," Ocasio-Cortez said. She echoed others who have called Trump an aspiring authoritarian ruler and fascist supported by special interests who are exacerbating the ongoing climate crisis. She also discussed how the billionaire owners of the Los Angeles Times and Washington Post prevented their editorial teams endorsing Harris over Trump, referring to it as "a plutocracy mask-off moment".

'Baywatch' star Donna D'Errico cleared the air on common misunderstandings surrounding online content sharing. Twitch, one of the largest video game streaming platforms in the world, is rolling back a policy change that would have allowed "artistic depictions of nudity" on the site. "Morgpie," a Twitch streamer and internet personality, was at the center of a nudity controversy after she appeared live on stream, with some viewers believing her to be topless. The uproar over her subsequent banning on the site prompted Twitch to release new guidelines allowing the "artistic depictions of nudity." However, Twitch announced Friday that it was again changing its nudity policy.

OpenAI's board hired former Twitch chief Emmett Shear as chief executive officer, defying calls from investors to reinstate the ousted Sam Altman, according to people familiar with the matter. Shear stepped down as CEO of Amazon's game-streaming site Twitch earlier this year. He won over directors because he appeared to recognize the existential threats that AI presented, one of the people said. A computer scientist who spent more than a decade building Twitch into one of the world's most successful video platforms, Shear is regarded as having the heft to lead a large engineering group, the person added. Like some members of OpenAI's board, Shear has ties to the AI-skeptical effective altruism movement, which sees risks posed by advanced AI.

Stealing someone else's joke is one of the highest crimes in comedy. With new AI tools like ChatGPT, some comedians are now worried about getting ripped off. The AI-generated "Seinfeld" parody that rose to fame online appears to have broken, then returned with a focus on existential dread and a generally bleak tone. "The show has broken out of the loop and is now'working' again but it feels darker," 404 Media reporter Jason Koebler posted on X. "Characters are convulsing, water is flowing upwards out of the sink instead of down, they move in creepy ways, clipping through each other and furniture." The "Seinfeld" parody, "Nothing, Forever," started streaming non-stop online in December 2022 and has over 170,000 followers.

Live commenting on video, a popular feature of live streaming platforms, enables viewers to engage with the content and share their comments, reactions, opinions, or questions with the streamer or other viewers while watching the video or live stream. It presents a challenging testbed for AI agents, which involves the simultaneous understanding of audio-visual multimodal contexts from live streams and the ability to interact with human viewers through dialogue. As existing live streaming-based comments datasets contain limited categories and lack a diversity, we create a large-scale audio-visual multimodal dialogue dataset to facilitate the development of live commenting technologies. The data is collected from Twitch, with 11 different categories and 575 streamers for a total of 438 hours of video and 3.2 million comments. Moreover, we propose a novel multimodal generation model capable of generating live comments that align with the temporal and spatial events within the video, as well as with the ongoing multimodal dialogue context. Our initial results have demonstrated the effectiveness of the proposed model, providing a robust foundation for further research and practical applications in the field of live video interaction.