Tootfinder

Paramount DTC Chair Cindy Holland says Paramount is now open to buying third party content, reminiscent of Holland's strategy when she was at Netflix (Nellie Andreeva/Deadline)
https://deadline.com/2025/08/paramount-plus-outside-studios-releas…

Paramount+ Opening Up To Outside Studios, May Experiment With Release Patterns, Won’t Try To Replicate CBS-Style Programming
Paramount+ is opening up to outside studios, may experiment with release patterns & won't try to replicate CBS-style programming, Cindy Holland says.

How does the #brain transfer #MotorSkills between hands?
This study reveals that transfer relies on re-expressing the neural patterns established during initial learning in distributed higher-order brain areas,
offering new insights into learning

Transfer of motor learning is associated with patterns of activity in the default mode network
How does the brain transfer motor skills between hands? This study reveals that transfer relies on re-expressing the neural patterns established during initial learning in distributed higher-order brain areas, offering new insights into learning generalization.

🇺🇦 Auf radioeins läuft...
Peter and Kerry:
🎵 All I've Got Are My Dreams
#NowPlaying #PeterandKerry
https://peterandkerry.bandcamp.com/track/all-ive-got-are-my-dreams
https://open.spotify.com/track/3GvMPgHM6pEK20uD0WjOQC

An Anthropic report details how Claude usage varies by country and US states, finding 36% use it for coding, 77% of enterprise use is for automation, and more (Anthropic)
https://www.anthropic.com/research/anthropic-economic-index-september-2025-report

Anthropic Economic Index report: Uneven geographic and enterprise AI adoption
To study such patterns of early AI adoption, we extend the Anthropic Economic Index along two important dimensions, introducing a geographic analysis of Claude.ai conversations and a first-of-its-kind examination of enterprise API use. We show how Claude usage has evolved over time, how adoption patterns differ across regions, and—for the first time—how firms are deploying frontier AI to solve business problems.

Efficient Mining of Low-Utility Sequential Patterns
Jian Zhu, Zhidong Lin, Wensheng Gan, Ruichu Cai, Zhifeng Hao, Philip S. Yu
https://arxiv.org/abs/2510.10243 https://

Efficient Mining of Low-Utility Sequential Patterns
Discovering valuable insights from rich data is a crucial task for exploratory data analysis. Sequential pattern mining (SPM) has found widespread applications across various domains. In recent years, low-utility sequential pattern mining (LUSPM) has shown strong potential in applications such as intrusion detection and genomic sequence analysis. However, existing research in utility-based SPM focuses on high-utility sequential patterns, and the definitions and strategies used in high-utility S…

SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agents
Longjie Guo, Chenjie Yuan, Mingyuan Zhong, Robert Wolfe, Ruican Zhong, Yue Xu, Bingbing Wen, Hua Shen, Lucy Lu Wang, Alexis Hiniker
https://arxiv.org/abs/2510.11035

SusBench: An Online Benchmark for Evaluating Dark Pattern Susceptibility of Computer-Use Agents
As LLM-based computer-use agents (CUAs) begin to autonomously interact with real-world interfaces, understanding their vulnerability to manipulative interface designs becomes increasingly critical. We introduce SusBench, an online benchmark for evaluating the susceptibility of CUAs to UI dark patterns, designs that aim to manipulate or deceive users into taking unintentional actions. Drawing nine common dark pattern types from existing taxonomies, we developed a method for constructing believab…

Topological Signatures of ReLU Neural Network Activation Patterns
Vicente Bosca, Tatum Rask, Sunia Tanweer, Andrew R. Tawfeek, Branden Stone
https://arxiv.org/abs/2510.12700 htt…

Topological Signatures of ReLU Neural Network Activation Patterns
This paper explores the topological signatures of ReLU neural network activation patterns. We consider feedforward neural networks with ReLU activation functions and analyze the polytope decomposition of the feature space induced by the network. Mainly, we investigate how the Fiedler partition of the dual graph and show that it appears to correlate with the decision boundary -- in the case of binary classification. Additionally, we compute the homology of the cellular decomposition -- in a regr…

A Non-Intrusive Framework for Deferred Integration of Cloud Patterns in Energy-Efficient Data-Sharing Pipelines
Sepideh Masoudi, Mark Edward Michael Daly, Jannis Kiesel, Stefan Tai
https://arxiv.org/abs/2510.12354

A Non-Intrusive Framework for Deferred Integration of Cloud Patterns in Energy-Efficient Data-Sharing Pipelines
As data mesh architectures gain traction in federated environments, organizations are increasingly building consumer-specific data-sharing pipelines using modular, cloud-native transformation services. Prior work has shown that structuring these pipelines with reusable transformation stages enhances both scalability and energy efficiency. However, integrating traditional cloud design patterns into such pipelines poses a challenge: predefining and embedding patterns can compromise modularity, re…

Approach to zigzag and checkerboard patterns in spatially extended systems
Manoj C. Warambhe, Prashant M. Gade
https://arxiv.org/abs/2510.10723 https://arx…

Approach to zigzag and checkerboard patterns in spatially extended systems
Zigzag patterns in one dimension or checkerboard patterns in two dimensions occur in a variety of pattern-forming systems. We introduce an order parameter `phase defect' to identify this transition and help to recognize the associated universality class on a discrete lattice. In one dimension, if $x_{i}(t)$ is a variable value at site $i$ at time $t$. We assign spin $s_i(t)=1$ for $x_{i}(t)>x_{i-1}(t)$, $s_i(t)=-1$ if $x_{i}(t)

🇺🇦 Auf radioeins läuft...
Peter and Kerry:
🎵 All I've Got Are My Dreams
#NowPlaying #PeterandKerry
https://peterandkerry.bandcamp.com/track/all-ive-got-are-my-dreams
https://open.spotify.com/track/3GvMPgHM6pEK20uD0WjOQC