arXiv:2602.18506v1 Announce Type: new Abstract: We initiate the study of control in hedonic games, where an external actor influences coalition formation by adding or deleting agents. We consider three basic control goals (1) enforcing that an agent is not alone (NA); (2) enforcing that a pair of agents is in the same coalition (PA); (3) enforcing that all agents are in the same grand coalition (GR), combined with two control actions: adding agents (AddAg) or deleting agents (DelAg). […]

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Piotr Niedźwiedź, CEO/CTO and founder of neptune.ai I’m excited to share that we’ve entered into a definitive agreement to be acquired by OpenAI, subject to closing conditions. We are thrilled to join the OpenAI team and help their AI researchers build better models faster. We started in 2017, when the pivotal transformer paper came out. And from then until today, we have focused on helping people who build ML models during the iterative, messy, and unpredictable phase of […]

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I find blockchain fascinating because it extends open source software development to open source + state. This seems to be a genuine/exciting innovation in computing paradigms; We don’t just get to share code, we get to share a running computer, and anyone anywhere can use it in an open and permissionless manner. The seeds of this revolution arguably began with Bitcoin, so I became curious to drill into it in some detail to get an intuitive understanding of […]

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arXiv:2603.03673v1 Announce Type: cross Abstract: Stein’s identity is a fundamental tool in machine learning with applications in generative models, stochastic optimization, and other problems involving gradients of expectations under Gaussian distributions. Less attention has been paid to problems with non-Gaussian expectations. Here, we consider the class of bounded-support $q$-Gaussians and derive a new Stein identity leading to gradient estimators which have nearly identical forms to the Gaussian ones, and which are similarly easy to implement. We do this […]

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Trust shouldn’t be trapped inside apps. When you switch Nostr clients, your context disappears and you rebuild the same trust layer from scratch. I built an extension and oracle that compute Web of Trust scores from your social graph once, making them portable across every client. Users control trust, not apps.

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https://arcprize.org/arc-agi/3 Interesting stuff, they find all well performing models probably have ARC-like data in their training set based on inspecting their reasoning traces. Also all frontier models on round 3 are below 1% score. Lots of room for improvement, specially considering prizes have not been claimed for round 1-2 yet (efficiency is still lacking). submitted by /u/LetsTacoooo [link] [comments]

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arXiv:2601.22160v1 Announce Type: new Abstract: Human animation aims to generate temporally coherent and visually consistent videos over long sequences, yet modeling long-range dependencies while preserving frame quality remains challenging. Inspired by the human ability to leverage past observations for interpreting ongoing actions, we propose FrameCache, a training-free three-stage framework consisting of Screen, Cache, and Match. In the Screen stage, a multi-dimensional, quality-aware mechanism with adaptive thresholds dynamically selects informative frames; the Cache stage maintains a reference pool using […]

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Predictive modeling over relational databases (RDBs) powers applications, yet remains challenging due to capturing both cross-table dependencies and complex feature interactions. Relational Deep Learning (RDL) methods automate feature engineering via message passing, while classical approaches like Deep Feature Synthesis (DFS) rely on predefined non-parametric aggregators. Despite performance gains, the comparative advantages of RDL over DFS and the design principles for selecting effective architectures remain poorly understood. We present a comprehensive study that unifies RDL and DFS in a […]

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William Irwin Thompson speculates on cultural transformation and explores themes of societal change at the edge of history.

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