YouTube's Custom Feeds Give You More Control Over the Algorithm In YouTube's latest update, viewers can tweak what the algorithm shows on their front page and curate it to a specific vibe. My YouTube algorithm is sacred, with years of data about my preferences and viewing history fermenting into whatever videos it picks for my home screen. YouTube's algorithm, while not perfect, sure knows what I want to see. The current top three videos on my front page are an Apple Watch analysis, a season 28 update, and something called "I Lost to the Muppets" from comedian Chris Fleming . As part of its Made on YouTube event Wednesday, Google released several new features, including a Custom Feeds button for adjusting what videos pop up on your front page. It's a rare chance for users to directly tweak their algorithmic feed on YouTube, in ways that go beyond just pressing thumbs up on a video or blocking a creator.

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In this summary article, organisers of a tutorial and a workshop at IJCAI-ECAI 2026 pick their key takeaways from their respective sessions. This tutorial was a practical, hands-on tutorial on the theory and methods for handling missing data in tabular and imaging settings, from statistical baselines to autoencoders and generative adversarial networks. The missingness mechanism is more important than the choice of imputation method. MCAR, MAR, and MNAR settings call for different treatment, and MNAR, the most challenging mechanism, is the one that most methods do not handle well. Deep generative imputation is not always better.

Should the Classroom Be More Like the Gym? As A.I. presses harder on the academic enterprise, we might look to a place where process is its own reward. When I'm in New York, I take spin classes on the Upper East Side. It is not especially pleasant. It is not supposed to be. We have chosen, quite deliberately, to subject ourselves to forty-five minutes of physical discomfort for benefits accrued down the road: better health, greater strength, a future version of ourselves that will justify the soreness tomorrow morning.

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Hosted by Ben Byford, The Machine Ethics Podcast brings together interviews with academics, authors, business leaders, designers and engineers on the subject of autonomous algorithms, artificial intelligence, machine learning, and technology's impact on society. This time we're chatting with E.M. about the promise of AI and making human connection easier, speech recognition and supporting linguistic diversity, making useful technologies that have a purpose, Mozilla Data Collective, under-represented cultures in datasets, accidental monocultures with technology, negative uses of datasets, AI literacy, the instability of LLMs and more E.M. Lewis-Jong is a Founder, Impact Entrepreneur and HCI researcher working at the intersection of community technology, open data, and inclusive AI. They are the Founder and CEO of the Mozilla Data Collective, a community-led platform for ethical creation, curation, and control of AI training datasets; built on the principle that people should be able to share their data on their own terms. They previously served as a VP at Mozilla Foundation, and the Director for Mozilla's Common Voice, an open-source platform enabling communities worldwide to preserve, revitalise, and contribute their languages to the future of speech tech. E.M. holds an MA in Modern History from the University of Oxford and is expecting a PhD in Informatics and Engineering at the University of Sussex, with research focused on controllability in conversational and voice AI for adolescents.

The studio released an official catch-up list ahead of December's release. We've got links to watch every one of the movies if you want to get up to speed. Marvel and Disney+ have issued a stacked watch list for fans ahead of the cinema release of on December 18. The Marvel Cinematic Universe can be complex terrain to navigate. Its 38 movies and 25 series to date span varying superhero plot lines, crossovers, and multiverse action, with the latest release likely to spare no less lore and real fan knowledge.

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This post contains a list of the AI-related seminars that are scheduled to take place in the next couple of months. All events detailed here are free and open for anyone to attend virtually. Jie Chao (Concord Consortium) Raspberry PI Sign up here to join. Pierre Marion (INRIA) EPFL The Zoom link is here . Stefan Klein and Anna Bon The Digital Humanism (DIGHUM) Initiative The talk will be livestreamed on YouTube here .