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A "good regulator theorem" for embodied agents
Nathaniel Virgo, Martin Biehl, Manuel Baltieri, Matteo Capucci
https://arxiv.org/abs/2508.06326 https://

A "good regulator theorem" for embodied agents
In a classic paper, Conant and Ashby claimed that "every good regulator of a system must be a model of that system." Artificial Life has produced many examples of systems that perform tasks with apparently no model in sight; these suggest Conant and Ashby's theorem doesn't easily generalise beyond its restricted setup. Nevertheless, here we show that a similar intuition can be fleshed out in a different way: whenever an agent is able to perform a regulation task, it is possible for an observer …

Acceptability of AI Assistants for Privacy: Perceptions of Experts and Users on Personalized Privacy Assistants
Meihe Xu, Aurelia Tam\`o-Larrieux, Arianna Rossi
https://arxiv.org/abs/2509.08554

Acceptability of AI Assistants for Privacy: Perceptions of Experts and Users on Personalized Privacy Assistants
Individuals increasingly face an overwhelming number of tasks and decisions. To cope with the new reality, there is growing research interest in developing intelligent agents that can effectively assist people across various aspects of daily life in a tailored manner, with privacy emerging as a particular area of application. Artificial intelligence (AI) assistants for privacy, such as personalized privacy assistants (PPAs), have the potential to automatically execute privacy decisions based on…

Internal email: Cognition offers buyouts to the ~200 newly acquired Windsurf staff, with Cognition CEO Scott Wu writing "we don't believe in work-life balance" (The Information)
https://www.theinformation.com/articles/cognition-off…

Cognition Offers Buyouts to Newly Acquired Windsurf Staff
Cognition, a two-year-old artificial intelligence coding startup last valued at $4 billion, has offered buyouts to the roughly 200 employees it acquired in a takeover of rival Windsurf three weeks ago, saying they will receive nine months of salary in return, according to an e-mail seen by The ...

Computational Concept of the Psyche
Anton Kolonin, Vladimir Kryukov
https://arxiv.org/abs/2509.07009 https://arxiv.org/pdf/2509.07009

Computational Concept of the Psyche
The article provides an overview of approaches to modeling the human psyche in the perspective of building an artificial one. Based on the review, a concept of cognitive architecture is proposed, where the psyche is considered as an operating system of a living or artificial subject, including a space of needs that determines its life meanings in connection with stimuli from the external world, and intelligence as a decision-making system for actions in relation to this world in order to satisf…

Composable Life: Speculation for Decentralized AI Life
Botao Amber Hu, Fangting
https://arxiv.org/abs/2508.20668 https://arxiv.org/pdf/2508.20668

Composable Life: Speculation for Decentralized AI Life
"Composable Life" is a hybrid project blending design fiction, experiential virtual reality, and scientific research. Through a multi-perspective, cross-media approach to speculative design, it reshapes our understanding of the digital future from AI's perspective. The project explores the hypothetical first suicide of an on-chain artificial life, examining the complex symbiotic relationship between humans, AI, and blockchain technology.

"As AI becomes part of everyday life, it brings a hidden climate cost"
#AI #ArtificialIntelligence #Climate

As AI becomes part of everyday life, it brings a hidden climate cost
Marissa Loewen first started using artificial intelligence in 2014 as a project management tool. She has autism and ADHD and said it helped immensely with organizing her thoughts.

Brain Tumor Detection Through Diverse CNN Architectures in IoT Healthcare Industries: Fast R-CNN, U-Net, Transfer Learning-Based CNN, and Fully Connected CNN
Mohsen Asghari Ilani, Yaser M. Banad
https://arxiv.org/abs/2509.05821

Brain Tumor Detection Through Diverse CNN Architectures in IoT Healthcare Industries: Fast R-CNN, U-Net, Transfer Learning-Based CNN, and Fully Connected CNN
Artificial intelligence (AI)-powered deep learning has advanced brain tumor diagnosis in Internet of Things (IoT)-healthcare systems, achieving high accuracy with large datasets. Brain health is critical to human life, and accurate diagnosis is essential for effective treatment. Magnetic Resonance Imaging (MRI) provides key data for brain tumor detection, serving as a major source of big data for AI-driven image classification. In this study, we classified glioma, meningioma, and pituitary tumo…

"And quite an adventure the life of Margittai Neumann Janos Lajos was. A child prodigy, he published his first paper in mathematics before age 20. He was the indisputable champion of applied mathematics in the 20th century. His work yielded groundbreaking advances in theoretical mathematics, quantum mechanics, game theory, economics, fluid dynamics, artificial intelligence, electrodynamics, meteorology, and computing."

William Aspray
There was a moment in which Kurt Gödel, Albert Einstein, and John von Neumann were all roaming the halls of the Institute for Advanced Studies in Princeton at the same time. Let that information sink in. Humanity experiences such gatherings of brilliant minds in a remote location of the space-time continuum only every so often; maybe the ancient Greeks and the men of the Renaissance witnessed such periods in time, as did the IAS staff at the end of World War II. How much will we have to wait f…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[1/6]:
- Temporal and Heterogeneous Graph Neural Network for Remaining Useful Life Prediction
Zhihao Wen, Yuan Fang, Pengcheng Wei, Fayao Liu, Zhenghua Chen, Min Wu

AI/ML Life Cycle Management for Interoperable AI Native RAN
Chu-Hsiang Huang, Chao-Kai Wen, Geoffrey Ye Li
https://arxiv.org/abs/2507.18538 https://arxiv.o…

AI/ML Life Cycle Management for Interoperable AI Native RAN
Artificial intelligence (AI) and machine learning (ML) models are rapidly permeating the 5G Radio Access Network (RAN), powering beam management, channel state information (CSI) feedback, positioning, and mobility prediction. However, without a standardized life-cycle management (LCM) framework, challenges, such as model drift, vendor lock-in, and limited transparency, hinder large-scale adoption. 3GPP Releases 16-20 progressively evolve AI/ML from experimental features to managed, interoperabl…

Understanding support for AI regulation: A Bayesian network perspective
Andrea Cremaschi, Dae-Jin Lee, Manuele Leonelli
https://arxiv.org/abs/2507.05866 ht…

Understanding support for AI regulation: A Bayesian network perspective
As artificial intelligence (AI) becomes increasingly embedded in public and private life, understanding how citizens perceive its risks, benefits, and regulatory needs is essential. To inform ongoing regulatory efforts such as the European Union's proposed AI Act, this study models public attitudes using Bayesian networks learned from the nationally representative 2023 German survey Current Questions on AI. The survey includes variables on AI interest, exposure, perceived threats and opportunit…

Recent grads and PhDs are being recruited by AI companies like Handshake to provide specialized training data in fields like music and law for $30-$160 per hour (Emma Haidar/Bloomberg)
https://www.bloomberg.com/news/articles/2025-07-24/col…

College Grads Are Finding Jobs Training AI Models
Ever since he picked up a trombone in middle school, Jackson Spellman has wanted to pursue a career in music.“It's 100% going to be a part of my life for the rest of my life,” said the 22-year-old from Wellington, Florida, who graduated in June from Northwestern University with a double major in music and cognitive science.Along with his degree, Spellman finished school with a new gig to add to his resume: artificial intelligence trainer. In the weeks leading up to graduation, Spellman said…

A Defect Classification Framework for AI-Based Software Systems (AI-ODC)
Mohammed O. Alannsary
https://arxiv.org/abs/2508.17900 https://arxiv.org/pdf/2508.…

A Defect Classification Framework for AI-Based Software Systems (AI-ODC)
Artificial Intelligence has gained a lot of attention recently, it has been utilized in several fields ranging from daily life activities, such as responding to emails and scheduling appointments, to manufacturing and automating work activities. Artificial Intelligence systems are mainly implemented as software solutions, and it is essential to discover and remove software defects to assure its quality using defect analysis which is one of the major activities that contribute to software qualit…

🦖 Study analyzes 400 million years of enzyme evolution
#biology

Study analyzes 400 million years of enzyme evolution
Enzymes catalyze chemical reactions in organisms—without which life would not be possible. Leveraging AlphaFold2 artificial intelligence, researchers at Charité—Universitätsmedizin Berlin have now succeeded in analyzing the laws of their evolution on a large scale.

Extending a Phylogeny-based Method for Detecting Signatures of Multi-level Selection for Applications in Artificial Life
Matthew Andres Moreno, Sanaz Hasanzadeh Fard, Luis Zaman, Emily Dolson
https://arxiv.org/abs/2508.14232

Extending a Phylogeny-based Method for Detecting Signatures of Multi-level Selection for Applications in Artificial Life
Multilevel selection occurs when short-term individual-level reproductive interests conflict with longer-term group-level fitness effects. Detecting and quantifying this phenomenon is key to understanding evolution of traits ranging from multicellularity to pathogen virulence. Multilevel selection is particularly important in artificial life research due to its connection to major evolutionary transitions, a hallmark of open-ended evolution. Bonetti Franceschi & Volz (2024) proposed to detect m…

An ELIXIR scoping review on domain-specific evaluation metrics for synthetic data in life sciences
Styliani-Christina Fragkouli, Somya Iqbal, Lisa Crossman, Barbara Gravel, Nagat Masued, Mark Onders, Devesh Haseja, Alex Stikkelman, Alfonso Valencia, Tom Lenaerts, Fotis Psomopoulos, Pilib \'O Broin, N\'uria Queralt-Rosinach, Davide Cirillo
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An ELIXIR scoping review on domain-specific evaluation metrics for synthetic data in life sciences
Synthetic data has emerged as a powerful resource in life sciences, offering solutions for data scarcity, privacy protection and accessibility constraints. By creating artificial datasets that mirror the characteristics of real data, allows researchers to develop and validate computational methods in controlled environments. Despite its promise, the adoption of synthetic data in Life Sciences hinges on rigorous evaluation metrics designed to assess their fidelity and reliability. To explore the…

Agentic Enterprise: AI-Centric User to User-Centric AI
Arpit Narechania, Alex Endert, Atanu R Sinha
https://arxiv.org/abs/2506.22893 https://

Agentic Enterprise: AI-Centric User to User-Centric AI
After a very long winter, the Artificial Intelligence (AI) spring is here. Or, so it seems over the last three years. AI has the potential to impact many areas of human life - personal, social, health, education, professional. In this paper, we take a closer look at the potential of AI for Enterprises, where decision-making plays a crucial and repeated role across functions, tasks, and operations. We consider Agents imbued with AI as means to increase decision-productivity of enterprises. We hi…

Romance, Relief, and Regret: Teen Narratives of Chatbot Overreliance
Mohammad 'Matt' Namvarpour, Brandon Brofsky, Jessica Medina, Mamtaj Akter, Afsaneh Razi
https://arxiv.org/abs/2507.15783

Romance, Relief, and Regret: Teen Narratives of Chatbot Overreliance
As Generative Artificial Intelligence (GenAI) driven chatbots like Character.AI become embedded in adolescent life, they raise concerns about emotional dependence and digital overreliance. While studies have investigated the overreliance of adults on these chatbots, they have not investigated teens' interactions with chatbots with customizable personas. We analyzed 318 Reddit posts made by users self-reported as 13-17 years old on the Character.AI subreddit to understand patterns of overrelianc…

A Concept-based approach to Voice Disorder Detection
Davide Ghia, Gabriele Ciravegna, Alkis Koudounas, Marco Fantini, Erika Crosetti, Giovanni Succo, Tania Cerquitelli
https://arxiv.org/abs/2507.17799 …

A Concept-based approach to Voice Disorder Detection
Voice disorders affect a significant portion of the population, and the ability to diagnose them using automated, non-invasive techniques would represent a substantial advancement in healthcare, improving the quality of life of patients. Recent studies have demonstrated that artificial intelligence models, particularly Deep Neural Networks (DNNs), can effectively address this task. However, due to their complexity, the decision-making process of such models often remain opaque, limiting their t…

EyeAI: AI-Assisted Ocular Disease Detection for Equitable Healthcare Access
Shiv Garg, Ginny Berkemeier
https://arxiv.org/abs/2507.20346 https://arxiv.org/…

EyeAI: AI-Assisted Ocular Disease Detection for Equitable Healthcare Access
Ocular disease affects billions of individuals unevenly worldwide. It continues to increase in prevalence with trends of growing populations of diabetic people, increasing life expectancies, decreasing ophthalmologist availability, and rising costs of care. We present EyeAI, a system designed to provide artificial intelligence-assisted detection of ocular diseases, thereby enhancing global health. EyeAI utilizes a convolutional neural network model trained on 1,920 retinal fundus images to auto…

On using AI for EEG-based BCI applications: problems, current challenges and future trends
Thomas Barbera, Jacopo Burger, Alessandro D'Amelio, Simone Zini, Simone Bianco, Raffaella Lanzarotti, Paolo Napoletano, Giuseppe Boccignone, Jose Luis Contreras-Vidal
https://arxiv.org/abs/2506.16168

On using AI for EEG-based BCI applications: problems, current challenges and future trends
Imagine unlocking the power of the mind to communicate, create, and even interact with the world around us. Recent breakthroughs in Artificial Intelligence (AI), especially in how machines "see" and "understand" language, are now fueling exciting progress in decoding brain signals from scalp electroencephalography (EEG). Prima facie, this opens the door to revolutionary brain-computer interfaces (BCIs) designed for real life, moving beyond traditional uses to envision Brain-to-Speech, Brain-to-…

Small Data Explainer -- The impact of small data methods in everyday life
Maren Hackenberg, Sophia G. Connor, Fabian Kabus, June Brawner, Ella Markham, Mahi Hardalupas, Areeq Chowdhury, Rolf Backofen, Anna K\"ottgen, Angelika Rohde, Nadine Binder, Harald Binder, the Collaborative Research Center 1597 Small Data
https://arxi…

Small Data Explainer -- The impact of small data methods in everyday life
The emergence of breakthrough artificial intelligence (AI) techniques has led to a renewed focus on how small data settings, i.e., settings with limited information, can benefit from such developments. This includes societal issues such as how best to include under-represented groups in data-driven policy and decision making, or the health benefits of assistive technologies such as wearables. We provide a conceptual overview, in particular contrasting small data with big data, and identify comm…

Learning to Use AI for Learning: How Can We Effectively Teach and Measure Prompting Literacy for K-12 Students?
Ruiwei Xiao, Xinying Hou, Ying-Jui Tseng, Hsuan Nieu, Guanze Liao, John Stamper, Kenneth R. Koedinger
https://arxiv.org/abs/2508.13962

Learning to Use AI for Learning: How Can We Effectively Teach and Measure Prompting Literacy for K-12 Students?
As Artificial Intelligence (AI) becomes increasingly integrated into daily life, there is a growing need to equip the next generation with the ability to apply, interact with, evaluate, and collaborate with AI systems responsibly. Prior research highlights the urgent demand from K-12 educators to teach students the ethical and effective use of AI for learning. To address this need, we designed an Large-Language Model (LLM)-based module to teach prompting literacy. This includes scenario-based d…

Feeling Machines: Ethics, Culture, and the Rise of Emotional AI
Vivek Chavan, Arsen Cenaj, Shuyuan Shen, Ariane Bar, Srishti Binwani, Tommaso Del Becaro, Marius Funk, Lynn Greschner, Roberto Hung, Stina Klein, Romina Kleiner, Stefanie Krause, Sylwia Olbrych, Vishvapalsinhji Parmar, Jaleh Sarafraz, Daria Soroko, Daksitha Withanage Don, Chang Zhou, Hoang Thuy Duong Vu, Parastoo Semnani, Daniel Weinhardt, Elisabeth Andre, J\"org Kr\"uger, Xavier Fresquet

Feeling Machines: Ethics, Culture, and the Rise of Emotional AI
This paper explores the growing presence of emotionally responsive artificial intelligence through a critical and interdisciplinary lens. Bringing together the voices of early-career researchers from multiple fields, it explores how AI systems that simulate or interpret human emotions are reshaping our interactions in areas such as education, healthcare, mental health, caregiving, and digital life. The analysis is structured around four central themes: the ethical implications of emotional AI, …