Tootfinder

Ukraine’s Main Intelligence Directorate (HUR) claims it paralyzed the operations of Orion Telecom, one of the largest internet providers in Russia’s Siberian region, on Russia Day.
https://tvpworld.com/87242100/ukrainian-hackers-cripple-siberia…

Ukrainian cyberattack cripples major internet provider in Siberia on Russia Day
The attack disabled hundreds of servers while also wiping out backup systems.

Apple says Visual Intelligence will now be able to search on-screen content in addition to analyzing real world objects, expanding on camera search (Tim Hardwick/MacRumors)
https://www.macrumors.com/2025/06/09/ios-26-visual-intellige…

iOS 26: Visual Intelligence Now Searches On-Screen Content
Apple has announced a major Visual Intelligence update at WWDC 2025, enabling users to search and take action on anything displayed across their...

AutoGEEval : A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine
Shuyang Hou, Zhangxiao Shen, Huayi Wu, Haoyue Jiao, Ziqi Liu, Lutong Xie, Chang Liu, Jianyuan Liang, Yaxian Qing, Xiaopu Zhang, Dehua Peng, Zhipeng Gui, Xuefeng Guan
https://

AutoGEEval++: A Multi-Level and Multi-Geospatial-Modality Automated Evaluation Framework for Large Language Models in Geospatial Code Generation on Google Earth Engine
Geospatial code generation is becoming a key frontier in integrating artificial intelligence with geo-scientific analysis, yet standardised automated evaluation tools for this task remain absent. This study presents AutoGEEval++, an enhanced framework building on AutoGEEval, and the first automated assessment system for large language models (LLMs) generating geospatial code on Google Earth Engine (GEE). It supports diverse data modalities and varying task complexities. Built on the GEE Python …

EmbodiedGen: Towards a Generative 3D World Engine for Embodied Intelligence
Wang Xinjie, Liu Liu, Cao Yu, Wu Ruiqi, Qin Wenkang, Wang Dehui, Sui Wei, Su Zhizhong
https://arxiv.org/abs/2506.10600

EmbodiedGen: Towards a Generative 3D World Engine for Embodied Intelligence
Constructing a physically realistic and accurately scaled simulated 3D world is crucial for the training and evaluation of embodied intelligence tasks. The diversity, realism, low cost accessibility and affordability of 3D data assets are critical for achieving generalization and scalability in embodied AI. However, most current embodied intelligence tasks still rely heavily on traditional 3D computer graphics assets manually created and annotated, which suffer from high production costs and li…

AURA: A Multi-Agent Intelligence Framework for Knowledge-Enhanced Cyber Threat Attribution
Nanda Rani, Sandeep Kumar Shukla
https://arxiv.org/abs/2506.10175

AURA: A Multi-Agent Intelligence Framework for Knowledge-Enhanced Cyber Threat Attribution
Effective attribution of Advanced Persistent Threats (APTs) increasingly hinges on the ability to correlate behavioral patterns and reason over complex, varied threat intelligence artifacts. We present AURA (Attribution Using Retrieval-Augmented Agents), a multi-agent, knowledge-enhanced framework for automated and interpretable APT attribution. AURA ingests diverse threat data including Tactics, Techniques, and Procedures (TTPs), Indicators of Compromise (IoCs), malware details, adversarial to…

Azure cost reduction/optimization for hosted applications using Artificial Intelligence. And it's REPEATABLE. Interested? Read on...
✅ Daniel Meppiel's Project Post
https://www.linkedin.com/posts/danielmeppiel_enterpriseai-ai-…

💥 What if AI could shrink your cloud bill by 80% in the time it takes to drink your coffee? | Daniel Meppiel
💥 What if AI could shrink your cloud bill by 80% in the time it takes to drink your coffee? 💥 I recently got it to happen—firsthand. What started as a quick experiment turned into something game-changing. Using VSCode's reusable prompts and the Azure MCP server, GitHub Copilot identified key optimizations for my app's infra in a predictable manner. Then, the Coding Agent implemented them. 📉 The result? An 80% smaller cloud bill. Just like that. In this 2-minute demo (linked below …

'The US has, however, not found that Iran is on the verge of acquiring nuclear weapons or attempting to do so. In March, US Director of National Intelligence Tulsi Gabbard said the US “continues to assess that Iran is not building nuclear weapons and Supreme Leader Ayatollah Ali Khamenei has not authorised the nuclear weapons programme he suspended in 2003”.'
What is behind Israel’s decision to attack Iran? | Conflict News | Al Jazeera

What is behind Israel’s decision to attack Iran?
Israel believes Iran is a threat to its security despite Iran’s insistence that it doesn’t want nuclear weapons.

IDEA: Augmenting Design Intelligence through Design Space Exploration
Chuer Chen, Xiaoke Yan, Xiaoyu Qi, Nan Cao
https://arxiv.org/abs/2506.10587 https://

IDEA: Augmenting Design Intelligence through Design Space Exploration
Design spaces serve as a conceptual framework that enables designers to explore feasible solutions through the selection and combination of design elements. However, effective decision-making remains heavily dependent on the designer's experience, and the absence of mathematical formalization prevents computational support for automated design processes. To bridge this gap, we introduce a structured representation that models design spaces with orthogonal dimensions and discrete selectable elem…

I’ve been having a conversation in my head with my friend Jac Mullen. One of his provocative ideas is that we’re better off dropping the term “artificial intelligence,” and instead calling these new technologies “artificial attention.”
#ai
#attention

Artificial Attention?
A letter to my friend Jac Mullen on AI and attention, looking at the 12th century history of reading with Ivan Illich's book In the Vineyard of the Text.

This is of historical interest on so many levels.
When the notion of AI first appeared, chess was considered the epitome of intelligence (before that it was calculating)—which, of course, it isn’t. Now AI is all about pattern recognition, which certainly covers more of what we associate with human intelligence, but go figure, it’s not *just* pattern recognition either. ⇢

Director of National Intelligence Tulsi Gabbard posted a bizarre video about nuclear bombs on X this morning.
She says we are “closer to the brink of nuclear annihilation than ever before…”
(Breaking the video into a 2 part 🧵 bc of video post limits, but watch to the end..it gets weird.)
Part 1:
https://…

Interview with Craig Federighi and Greg Joswiak on Apple's struggles to ship AI features, demoed in 2024, with the "V1 Siri architecture" and work on a V2 model (Lance Ulanoff/TechRadar)
https://www.techra…

This is what really happened with Siri and Apple Intelligence, according to Apple
Is it a delay, a strategy... or something else?

The Effects of GitHub Copilot on Computing Students' Programming Effectiveness, Efficiency, and Processes in Brownfield Programming Tasks
Md Istiak Hossain Shihab, Christopher Hundhausen, Ahsun Tariq, Summit Haque, Yunhan Qiao, Brian Mulanda
https://arxiv.org/abs/2506.10051

The Effects of GitHub Copilot on Computing Students' Programming Effectiveness, Efficiency, and Processes in Brownfield Programming Tasks
When graduates of computing degree programs enter the software industry, they will most likely join teams working on legacy code bases developed by people other than themselves. In these so-called brownfield software development settings, generative artificial intelligence (GenAI) coding assistants like GitHub Copilot are rapidly transforming software development practices, yet the impact of GenAI on student programmers performing brownfield development tasks remains underexplored. This paper i…

Agentic Semantic Control for Autonomous Wireless Space Networks: Extending Space-O-RAN with MCP-Driven Distributed Intelligence
Eduardo Baena, Paolo Testolina, Michele Polese, Sergi Aliaga, Andrew Benincasa, Dimitrios Koutsonikolas, Josep Jornet, Tommaso Melodia
https://arxiv.org/abs/2506.10925

Agentic Semantic Control for Autonomous Wireless Space Networks: Extending Space-O-RAN with MCP-Driven Distributed Intelligence
Lunar surface operations impose stringent requirements on wireless communication systems, including autonomy, robustness to disruption, and the ability to adapt to environmental and mission-driven context. While Space-O-RAN provides a distributed orchestration model aligned with 3GPP standards, its decision logic is limited to static policies and lacks semantic integration. We propose a novel extension incorporating a semantic agentic layer enabled by the Model Context Protocol (MCP) and Agent-…

This is of historical interest on so many levels.
When the notion of AI first appeared, chess was considered the epitome of intelligence (before that it was calculating)—which, of course, it isn’t. Now AI is all about pattern recognition, which certainly covers more of what we associate with human intelligence, but go figure, it’s not *just* pattern recognition either. ⇢

This is of historical interest on so many levels.
When the notion of AI first appeared, chess was considered the epitome of intelligence (before that it was calculating)—which, of course, it isn’t. Now AI is all about pattern recognition, which certainly covers more of what we associate with human intelligence, but go figure, it’s not *just* pattern recognition either. ⇢

A Survey on the Role of Artificial Intelligence and Machine Learning in 6G-V2X Applications
Donglin Wang, Anjie Qiu, Qiuheng Zhou, Hans D. Schotten
https://arxiv.org/abs/2506.09512

A Survey on the Role of Artificial Intelligence and Machine Learning in 6G-V2X Applications
The rapid advancement of Vehicle-to-Everything (V2X) communication is transforming Intelligent Transportation Systems (ITS), with 6G networks expected to provide ultra-reliable, low-latency, and high-capacity connectivity for Connected and Autonomous Vehicles (CAVs). Artificial Intelligence (AI) and Machine Learning (ML) have emerged as key enablers in optimizing V2X communication by enhancing network management, predictive analytics, security, and cooperative driving due to their outstanding p…

Unitary Scrambling and Collapse: A Quantum Diffusion Framework for Generative Modeling
Yihua Li, Jiayi Chen, Tamanna S. Kumavat, Kyriakos Flouris
https://arxiv.org/abs/2506.10571 …

Unitary Scrambling and Collapse: A Quantum Diffusion Framework for Generative Modeling
Quantum computing, with its promise of exponential speedups, is rapidly emerging as a powerful paradigm for advancing artificial intelligence. We propose QSC-Diffusion, the first fully quantum diffusion-based framework for image generation. Our method integrates classical Gaussian noise with quantum scrambling in the forward process, and employs parameterized quantum circuits with measurement-induced collapse for reverse denoising -- enabling end-to-end sampling without reliance on classical ne…

Are We Generalizing from the Exception? An In-the-Wild Study on Group-Sensitive Conversation Design in Human-Agent Interactions
Ana M\"uller, Sabina Jeschke, Anja Richert
https://arxiv.org/abs/2506.10462

Are We Generalizing from the Exception? An In-the-Wild Study on Group-Sensitive Conversation Design in Human-Agent Interactions
This paper investigates the impact of a group-adaptive conversation design in two socially interactive agents (SIAs) through two real-world studies. Both SIAs - Furhat, a social robot, and MetaHuman, a virtual agent - were equipped with a conversational artificial intelligence (CAI) backend combining hybrid retrieval and generative models. The studies were carried out in an in-the-wild setting with a total of $N = 188$ participants who interacted with the SIAs - in dyads, triads or larger group…

The current LLM “focus on anthropomorphic interfaces—just have a chat!—makes them charming, misguides us into attributing more agency and intelligence than they have, which makes it even more challenging for people to control or use them predictably. Sycophancy is one of the many challenges here, for example.”
“Coding assistants, particularly agents, are narrower in their interface, but they build on a similar interaction model. They aim to look like developers, independent entities that can do the actual work.”
7/

What Users Value and Critique: Large-Scale Analysis of User Feedback on AI-Powered Mobile Apps
Vinaik Chhetri, Krishna Upadhyay, A. B. Siddique, Umar Farooq
https://arxiv.org/abs/2506.10785

What Users Value and Critique: Large-Scale Analysis of User Feedback on AI-Powered Mobile Apps
Artificial Intelligence (AI)-powered features have rapidly proliferated across mobile apps in various domains, including productivity, education, entertainment, and creativity. However, how users perceive, evaluate, and critique these AI features remains largely unexplored, primarily due to the overwhelming volume of user feedback. In this work, we present the first comprehensive, large-scale study of user feedback on AI-powered mobile apps, leveraging a curated dataset of 292 AI-driven apps ac…

Superstudent intelligence in thermodynamics
Rebecca Loubet, Pascal Zittlau, Marco Hoffmann, Luisa Vollmer, Sophie Fellenz, Heike Leitte, Fabian Jirasek, Johannes Lenhard, Hans Hasse
https://arxiv.org/abs/2506.09822

Superstudent intelligence in thermodynamics
In this short note, we report and analyze a striking event: OpenAI's large language model o3 has outwitted all students in a university exam on thermodynamics. The thermodynamics exam is a difficult hurdle for most students, where they must show that they have mastered the fundamentals of this important topic. Consequently, the failure rates are very high, A-grades are rare - and they are considered proof of the students' exceptional intellectual abilities. This is because pattern learning does…

Thief of Truth: VR comics about the relationship between AI and humans
Joonhyung Bae
https://arxiv.org/abs/2506.10012 https://arxiv.o…

Thief of Truth: VR comics about the relationship between AI and humans
Thief of Truth is a first-person perspective Virtual Reality (VR) comic that explores the relationship between humans and artificial intelligence (AI). The work tells the story of a mind-uploaded human being reborn as a new subject while interacting with an AI that is looking for the meaning of life. In order to experiment with the expandability of VR comics, the work was produced by focusing on three problems. First, the comic is designed using the viewing control effect of VR. Second, through…

Apple Intelligence has labeled a photo I’ve taken of a neighbour’s calico tabby as “American Wirehair”. I’m not an expert, so who knows, but based on geotags it would seem unlikely.

TinyML-Based Adaptive Pulse Shaping for Edge Intelligence in IoT/IIoT
Afan Ali
https://arxiv.org/abs/2506.05789 https://arxiv.org/pdf…

TinyML-Based Adaptive Pulse Shaping for Edge Intelligence in IoT/IIoT
Edge intelligence in IoT and IIoT demands lightweight algorithms for data processing on resource-constrained devices. This paper introduces a novel adaptive pulse shape filter based on TinyML for PAPR and SER optimization on edge devices used in uplink IoT communication. Implemented on IoT nodes such as sensors, our pruned neural network provides up to 2 dB PAPR saving over root-raised-cosine (RRC) filters. Mass simulations validate its efficacy in DFT-s-OFDM systems and offer an energy-efficie…

"The real threat posed by generative AI is not that it will eliminate work on a mass scale, rendering human labour obsolete. It is that, left unchecked, it will continue to transform work in ways that deepen precarity, intensify surveillance, and widen existing inequalities."
"The current trajectory of generative AI reflects the priorities of firms seeking to lower costs, discipline workers, and consolidate profits — not any drive to enhance human flourishing. If we allo…

Is the AI Bubble About to Burst?
In the years since Automation and the Future of Work first appeared, a new wave of technological enthusiasm has swept across the popular imagination. The catalyst this time has been the rapid advances in generative artificial intelligence, spearheaded by companies like OpenAI, Google DeepMind, and Meta. Once again, a c

Less is More: some Computational Principles based on Parcimony, and Limitations of Natural Intelligence
Laura Cohen, Xavier Hinaut, Lilyana Petrova, Alexandre Pitti, Syd Reynal, Ichiro Tsuda
https://arxiv.org/abs/2506.07060

Less is More: some Computational Principles based on Parcimony, and Limitations of Natural Intelligence
Natural intelligence (NI) consistently achieves more with less. Infants learn language, develop abstract concepts, and acquire sensorimotor skills from sparse data, all within tight neural and energy limits. In contrast, today's AI relies on virtually unlimited computational power, energy, and data to reach high performance. This paper argues that constraints in NI are paradoxically catalysts for efficiency, adaptability, and creativity. We first show how limited neural bandwidth promotes conci…

Bridging Perspectives: A Survey on Cross-view Collaborative Intelligence with Egocentric-Exocentric Vision
Yuping He, Yifei Huang, Guo Chen, Lidong Lu, Baoqi Pei, Jilan Xu, Tong Lu, Yoichi Sato
https://arxiv.org/abs/2506.06253

Bridging Perspectives: A Survey on Cross-view Collaborative Intelligence with Egocentric-Exocentric Vision
Perceiving the world from both egocentric (first-person) and exocentric (third-person) perspectives is fundamental to human cognition, enabling rich and complementary understanding of dynamic environments. In recent years, allowing the machines to leverage the synergistic potential of these dual perspectives has emerged as a compelling research direction in video understanding. In this survey, we provide a comprehensive review of video understanding from both exocentric and egocentric viewpoint…

Multiverse Privacy Theory for Contextual Risks in Complex User-AI Interactions
Ece Gumusel
https://arxiv.org/abs/2506.10042 https://a…

Multiverse Privacy Theory for Contextual Risks in Complex User-AI Interactions
In an era of increasing interaction with artificial intelligence (AI), users face evolving privacy decisions shaped by complex, uncertain factors. This paper introduces Multiverse Privacy Theory, a novel framework in which each privacy decision spawns a parallel universe, representing a distinct potential outcome based on user choices over time. By simulating these universes, this theory provides a foundation for understanding privacy through the lens of contextual integrity, evolving preferenc…

A centralized intelligence database on all Americans is not inherently legal.
It likely breaks the Privacy Act of 1974, the Foreign Intelligence Surveillance Act (FISA), the 1st, 4th and 5th Amendments.
This must be stopped. Contact your Senators and Representative and ask them to stop it. I use @… to call mine.

Trump Taps Palantir to Create Master Database on Every American
Trump’s dystopian plan is already underway.

Efficient Fireworks Algorithm Equipped with an Explosion Mechanism based on Student's T-distribution
Cen Shipeng, Tan Ying
https://arxiv.org/abs/2506.08484

Efficient Fireworks Algorithm Equipped with an Explosion Mechanism based on Student's T-distribution
Many real-world problems can be transformed into optimization problems, which can be classified into convex and non-convex. Although convex problems are almost completely studied in theory, many related algorithms to many non-convex problems do not work well and we need more optimization techniques. As a swarm intelligence optimization algorithm, the Fireworks Algorithm(FWA) has been widely studied and applied to many real-world scenarios, even including large language model fine-tuning. But th…

SAG-AFTRA ends the 300 day video game actors strike after reaching a tentative deal for a new Interactive Media Agreement with the major video game companies (Erik Hayden/The Hollywood Reporter)
https://www.hollywoodreporter.com/business

SAG-AFTRA Suspends Strike Against Video Game Companies, Paving Way for Return to Work
The union had taken a stand on artificial intelligence, among other concerns, as it looked to advocate for voice and performance capture workers.

Explainable-AI powered stock price prediction using time series transformers: A Case Study on BIST100
Sukru Selim Calik, Andac Akyuz, Zeynep Hilal Kilimci, Kerem Colak
https://arxiv.org/abs/2506.06345

Explainable-AI powered stock price prediction using time series transformers: A Case Study on BIST100
Financial literacy is increasingly dependent on the ability to interpret complex financial data and utilize advanced forecasting tools. In this context, this study proposes a novel approach that combines transformer-based time series models with explainable artificial intelligence (XAI) to enhance the interpretability and accuracy of stock price predictions. The analysis focuses on the daily stock prices of the five highest-volume banks listed in the BIST100 index, along with XBANK and XU100 in…

We in Game Workers Unite Ireland stand in solidarity with Animation Workers of Ireland, and the international trade union coalition happening to organise against the threat of AI in the animation industry, and we support their call to acton.
Join them Thursday 12 June at 14:00 at the Pâquier in Annecy!!
#Animation

This is one of the better articles I’ve seen on where AI might lead, trying to find a middle ground between “it’s a load of hype” and “it’s going to solve world hunger/kill us all”.
A choice quote:
Which is it: business as usual or the end of the world? “The test of a first-rate intelligence,” F. Scott Fitzgerald famously claimed, “is the ability to hold two opposed ideas in the mind at the same time, and still retain the ability to function.” Reading these reports back-to-back,…

Two Paths for A.I.
Joshua Rothman on two papers about the future of A.I., by deeply knowledgeable experts, which arrive at absurdly divergent conclusions about the threat the tech poses.

A Comprehensive Study on Medical Image Segmentation using Deep Neural Networks
Loan Dao, Ngoc Quoc Ly
https://arxiv.org/abs/2506.04121 https://

A Comprehensive Study on Medical Image Segmentation using Deep Neural Networks
Over the past decade, Medical Image Segmentation (MIS) using Deep Neural Networks (DNNs) has achieved significant performance improvements and holds great promise for future developments. This paper presents a comprehensive study on MIS based on DNNs. Intelligent Vision Systems are often evaluated based on their output levels, such as Data, Information, Knowledge, Intelligence, and Wisdom (DIKIW),and the state-of-the-art solutions in MIS at these levels are the focus of research. Additionally, …

Intelligent System of Emergent Knowledge: A Coordination Fabric for Billions of Minds
Moshi Wei, Sparks Li
https://arxiv.org/abs/2506.09335 https://…

Intelligent System of Emergent Knowledge: A Coordination Fabric for Billions of Minds
The Intelligent System of Emergent Knowledge (ISEK) establishes a decentralized network where human and artificial intelligence agents collaborate as peers, forming a self-organizing cognitive ecosystem. Built on Web3 infrastructure, ISEK combines three fundamental principles: (1) a decentralized multi-agent architecture resistant to censorship, (2) symbiotic AI-human collaboration with equal participation rights, and (3) resilient self-adaptation through distributed consensus mechanisms. The…

LLMs Cannot Reliably Judge (Yet?): A Comprehensive Assessment on the Robustness of LLM-as-a-Judge
Songze Li, Chuokun Xu, Jiaying Wang, Xueluan Gong, Chen Chen, Jirui Zhang, Jun Wang, Kwok-Yan Lam, Shouling Ji
https://arxiv.org/abs/2506.09443

LLMs Cannot Reliably Judge (Yet?): A Comprehensive Assessment on the Robustness of LLM-as-a-Judge
Large Language Models (LLMs) have demonstrated remarkable intelligence across various tasks, which has inspired the development and widespread adoption of LLM-as-a-Judge systems for automated model testing, such as red teaming and benchmarking. However, these systems are susceptible to adversarial attacks that can manipulate evaluation outcomes, raising concerns about their robustness and, consequently, their trustworthiness. Existing evaluation methods adopted by LLM-based judges are often pie…

This https://arxiv.org/abs/2402.16887 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSI_…

A Comprehensive Survey on Artificial Intelligence for Complex Network: Potential, Methodology and Application
Complex networks pervade various real-world systems, from the natural environment to human societies. The essence of these networks is in their ability to transition and evolve from microscopic disorder-where network topology and node dynamics intertwine-to a macroscopic order characterized by certain collective behaviors. Over the past two decades, complex network science has significantly enhanced our understanding of the statistical mechanics, structures, and dynamics underlying real-world n…

"AI-Powered Cameras Have Issued Nearly 10,000 Tickets in L.A."
I wonder if this means they can reduce the $2.14 billion LAPD budget. 😳
https://www.govtech.com/artificial-intelligence/ai-powered-cameras-hav…

Google’s AI Chief on the State of Artificial Intelligence (New York Times, 23 May 2025)
https://www.nytimes.com/2025/05/23/podcasts/google-ai-demis-hassabi…

Google DeepMind’s Demis Hassabis on AGI, Innovation and More
Demis Hassabis, the chief executive of Google DeepMind, says that “we’re quite close” to human-level artificial intelligence. After that, all bets are off.

Apple is bringing polls to iMessage group chats and says Apple Intelligence will suggest polls based on a conversation's context (Aisha Malik/TechCrunch)
https://techcrunch.com/2025/06/09/apple-is-bringing-polls-to-imessage/

Apple is bringing polls to iMessage | TechCrunch
Apple announced at WWDC on Monday that it's bringing polls to iMessage. The feature has been highly requested by users, and is one that has been long adopted by services like WhatsApp and Telegram.

Some creatives and academics are rejecting AI on environmental and ethical grounds, and describe the pressure they feel to use AI to "keep up" with others (Emine Saner/The Guardian)
https://www.theguardian.com/technology/202

This https://arxiv.org/abs/2506.02791 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Rethinking the effects of data contamination in Code Intelligence
In recent years, code intelligence has gained increasing importance in the field of automated software engineering. Meanwhile, the widespread adoption of Pretrained Language Models (PLMs) and Large Language Models (LLMs) has raised concerns regarding data contamination and its potential impact on model performance evaluation. This paper presents a systematic empirical study to investigate the fine-grained data contamination on code intelligence tasks. Our study involves diverse representative P…

The Cloud Next Door: Investigating the Environmental and Socioeconomic Strain of Datacenters on Local Communities
Wacuka Ngata, Noman Bashir, Michelle Westerlaken, Laurent Liote, Yasra Chandio, Elsa Olivetti
https://arxiv.org/abs/2506.03367

The Cloud Next Door: Investigating the Environmental and Socioeconomic Strain of Datacenters on Local Communities
Datacenters have become the backbone of modern digital infrastructure, powering the rapid rise of artificial intelligence and promising economic growth and technological progress. However, this expansion has brought growing tensions in the local communities where datacenters are already situated or being proposed. While the mainstream discourse often focuses on energy usage and carbon footprint of the computing sector at a global scale, the local socio-environmental consequences -- such as heal…

Can Artificial Intelligence Trade the Stock Market?
J\k{e}drzej Maskiewicz, Pawe{\l} Sakowski
https://arxiv.org/abs/2506.04658 https://

Can Artificial Intelligence Trade the Stock Market?
The paper explores the use of Deep Reinforcement Learning (DRL) in stock market trading, focusing on two algorithms: Double Deep Q-Network (DDQN) and Proximal Policy Optimization (PPO) and compares them with Buy and Hold benchmark. It evaluates these algorithms across three currency pairs, the S&P 500 index and Bitcoin, on the daily data in the period of 2019-2023. The results demonstrate DRL's effectiveness in trading and its ability to manage risk by strategically avoiding trades in unfavorab…

Another of my forays into AI ethics is just out! This time the focus is on the ethics (or lack thereof) of Reinforcement Learning Feedback (RLF) techniques aimed at increasing the 'alignment' of LLMs.
The paper is fruit of the joint work of a great team of collaborators, among whom @… and @…

Helpful, harmless, honest? Sociotechnical limits of AI alignment and safety through Reinforcement Learning from Human Feedback - Ethics and Information Technology
This paper critically evaluates the attempts to align Artificial Intelligence (AI) systems, especially Large Language Models (LLMs), with human values and intentions through Reinforcement Learning from Feedback methods, involving either human feedback (RLHF) or AI feedback (RLAIF). Specifically, we show the shortcomings of the broadly pursued alignment goals of honesty, harmlessness, and helpfulness. Through a multidisciplinary sociotechnical critique, we examine both the theoretical underpinni…

This is the first I've heard of this:
“They’re finding backdoors in Barbie dolls,” said Antani, now CEO of Horizon3.ai, a cybersecurity firm, referring to concerns from researchers who successfully hacked the microphone of a digitally connected version of the toy."
https://

Smartphones have become an intelligence treasure trove
Hackers tied to China's government have tried repeatedly to access the phones of prominent Americans, part of Beijing's sprawling cyberespionage efforts. Smartphones and other mobile devices present significant national security and cybersecurity risks, as foreign government hackers exploit vulnerabilities in mobile networks and apps to spy on people and steal secrets. And people's careless use of mobile devices to share sensitive information is another concern. National security experts say th…

Ukraine's military intelligence claims cyberattack on Russian strategic bomber maker https://therecord.media/ukraine-military-russia-strategic-bomber

Recommender systems, stigmergy, and the tyranny of popularity
Zackary Okun Dunivin, Paul E. Smaldino
https://arxiv.org/abs/2506.06162 https://

Recommender systems, stigmergy, and the tyranny of popularity
Scientific recommender systems, such as Google Scholar and Web of Science, are essential tools for discovery. Search algorithms that power work through stigmergy, a collective intelligence mechanism that surfaces useful paths through repeated engagement. While generally effective, this ``rich-get-richer'' dynamic results in a small number of high-profile papers that dominate visibility. This essay argues argue that these algorithm over-reliance on popularity fosters intellectual homogeneity and…

This https://arxiv.org/abs/2502.18744 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

ZEBRA: Leveraging Model-Behavioral Knowledge for Zero-Annotation Preference Dataset Construction
Recent efforts in LLM alignment have focused on constructing large-scale preference datasets via human or Artificial Intelligence (AI) annotators. However, such approaches rely on instance-wise supervision, incurring substantial annotation cost and limited interpretability. In this paper, we propose ZEBRA - a model behavior-wise zero-annotation framework that constructs preference data by leveraging model behavior knowledge derived from benchmark performances. ZEBRA binarizes response pairs by …

Apple announces Workout Buddy, bringing Apple Intelligence to Apple Watch fitness workouts by providing personalized insights during exercise sessions (Tim Hardwick/MacRumors)
https://www.macrumors.com/2025/06/09/ai-powered-workout-buddy-coming…

Apple Unveils AI-Powered 'Workout Buddy' for Apple Watch at WWDC
Apple at WWDC just announced Workout Buddy, which brings Apple Intelligence to fitness workouts on Apple Watch for the first time. The new feature...

The return of Attack of the Killer Tomatoes in the theaters was NOT on my bingo card. 😁
✅ 'Attack of the Killer Tomatoes' Reboot In Works With David Koechner, More
https://deadline.com/2025/06/attack-of-the-killer-tomatoe…

‘Attack Of The Killer Tomatoes: Organic Intelligence’: Cult Classic Reborn With David Koechner, Eric Roberts, Dan Bakkedahl, John Astin & More
EXCLUSIVE: Never, ever think of holding a Z-grade movie franchise down. Attack of the Killer Tomatoes is alive again in a fifth movie, Attack of the Killer Tomatoes: Organic Intelligence, from filmmaker David Ferino. Attack of the Killer Tomatoes: Organic Intelligence is billed as “pitting the eternal power of nature against A.I.’s best and brightest.” […]

Frugal Machine Learning for Energy-efficient, and Resource-aware Artificial Intelligence
John Violos, Konstantina-Christina Diamanti, Ioannis Kompatsiaris, Symeon Papadopoulos
https://arxiv.org/abs/2506.01869

Frugal Machine Learning for Energy-efficient, and Resource-aware Artificial Intelligence
Frugal Machine Learning (FML) refers to the practice of designing Machine Learning (ML) models that are efficient, cost-effective, and mindful of resource constraints. This field aims to achieve acceptable performance while minimizing the use of computational resources, time, energy, and data for both training and inference. FML strategies can be broadly categorized into input frugality, learning process frugality, and model frugality, each focusing on reducing resource consumption at different…

Assessing the Impact of Refactoring Energy-Inefficient Code Patterns on Software Sustainability: An Industry Case Study
Rohit Mehra, Priyavanshi Pathania, Vibhu Saujanya Sharma, Vikrant Kaulgud, Sanjay Podder, Adam P. Burden
https://arxiv.org/abs/2506.09370

Assessing the Impact of Refactoring Energy-Inefficient Code Patterns on Software Sustainability: An Industry Case Study
Advances in technologies like artificial intelligence and metaverse have led to a proliferation of software systems in business and everyday life. With this widespread penetration, the carbon emissions of software are rapidly growing as well, thereby negatively impacting the long-term sustainability of our environment. Hence, optimizing software from a sustainability standpoint becomes more crucial than ever. We believe that the adoption of automated tools that can identify energy-inefficient p…

Stream DaQ: Stream-First Data Quality Monitoring
Vasileios Papastergios, Anastasios Gounaris
https://arxiv.org/abs/2506.06147 https://

Stream DaQ: Stream-First Data Quality Monitoring
Data quality is fundamental to modern data science workflows, where data continuously flows as unbounded streams feeding critical downstream tasks, from elementary analytics to advanced artificial intelligence models. Existing data quality approaches either focus exclusively on static data or treat streaming as an extension of batch processing, lacking the temporal granularity and contextual awareness required for true streaming applications. In this paper, we present a novel data quality monit…

MOSAIC-F: A Framework for Enhancing Students' Oral Presentation Skills through Personalized Feedback
Alvaro Becerra, Daniel Andres, Pablo Villegas, Roberto Daza, Ruth Cobos
https://arxiv.org/abs/2506.08634

MOSAIC-F: A Framework for Enhancing Students' Oral Presentation Skills through Personalized Feedback
In this article, we present a novel multimodal feedback framework called MOSAIC-F, an acronym for a data-driven Framework that integrates Multimodal Learning Analytics (MMLA), Observations, Sensors, Artificial Intelligence (AI), and Collaborative assessments for generating personalized feedback on student learning activities. This framework consists of four key steps. First, peers and professors' assessments are conducted through standardized rubrics (that include both quantitative and qualitat…

Meteorologically-Informed Adaptive Conformal Prediction for Tropical Cyclone Intensity Forecasting
Xuepeng Chen, Jing-Jia Luo, Qingqing Li, Fan Meng
https://arxiv.org/abs/2506.06638

Meteorologically-Informed Adaptive Conformal Prediction for Tropical Cyclone Intensity Forecasting
Rapid intensification (RI) of tropical cyclones (TCs) poses a great challenge due to their highly nonlinear dynamics and inherent uncertainties. Conventional statistical dynamics and artificial intelligence prediction models typically rely on static parameterization schemes, which limits their ability to capture the non-stationary error structure in the intensity evolution. To address this issue, we propose a physically-inspired covariate adaptive conformal prediction framework that dynamically…

This https://arxiv.org/abs/2409.09268 has been replaced.
initial toot: https://mastoxiv.page/@arX…

Spintronic Neuron Using a Magnetic Tunnel Junction for Low-Power Neuromorphic Computing
This paper proposes a novel spiking artificial neuron design based on a combined spin valve/magnetic tunnel junction (SV/MTJ). Traditional hardware used in artificial intelligence and machine learning faces significant challenges related to high power consumption and scalability. To address these challenges, spintronic neurons, which can mimic biologically inspired neural behaviors, offer a promising solution. We present a model of an SV/MTJ-based neuron which uses technologies that have been s…

Sam Altman says "intelligence and energy", the "limiters on human progress", will be abundant in the 2030s, and superintelligence should be widely distributed (Sam Altman)
https://blog.samaltman.com/the-gentle-singularity

That… is quite a number. I wonder what the return on that investment will look like?
https://finance.yahoo.com/news/how-nvidia-played-a-central-role-in-the-306-billion-ai-startup-boom-195741749.html

How Nvidia 'played a central role' in the $306 billion AI startup boom
Nvidia's AI chips laid the groundwork for a massive wave of investment in artificial intelligence.

'Shooting Russia in the back' — Serbian companies supplying ammunition to Ukraine, Moscow claims: https://benborges.xyz/2025/05/29/shooting-russia-in-the-back.html

Can AI erase the tedium of managing digital collections without also erasing what makes them distinctive? Find out in this recording of last month's webinar with Sara and Ben Brumfield of FromThePage, who explore the good, bad, and ugly of AI in archives.
https://digitalc…

This https://arxiv.org/abs/2506.05394 has been replaced.
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Attacking Attention of Foundation Models Disrupts Downstream Tasks
Foundation models represent the most prominent and recent paradigm shift in artificial intelligence.Foundation models are large models, trained on broad data that deliver high accuracy in many downstream tasks, often without fine-tuning. For this reason, models such as CLIP , DINO or Vision Transfomers (ViT), are becoming the bedrock of many industrial AI-powered applications. However, the reliance on pre-trained foundation models also introduces significant security concerns, as these models a…

[VIDEO] The Government Knows AGI is Coming | The Ezra Klein Show
#AI

Trump cyber executive order drops Biden-era provisions https://therecord.media/trump-cybersecurity-executive-order-june-2025

Collective Intelligence Outperforms Individual Talent: A Case Study in League of Legends
Angelo Josey Caldeira, Sajan Maharjan, Srijoni Majumdar, Evangelos Pournaras
https://arxiv.org/abs/2506.02706

Collective Intelligence Outperforms Individual Talent: A Case Study in League of Legends
Gaming environments are popular testbeds for studying human interactions and behaviors in complex artificial intelligence systems. Particularly, in multiplayer online battle arena (MOBA) games, individuals collaborate in virtual environments of high realism that involves real-time strategic decision-making and trade-offs on resource management, information collection and sharing, team synergy and collective dynamics. This paper explores whether collective intelligence, emerging from cooperative…

Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa RYu
https://arxiv.org/abs/2506.00056

Toward Knowledge-Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human-AI Synergy
Artificial intelligence (AI) is reshaping inverse design across manufacturing domain, enabling high-performance discovery in materials, products, and processes. However, purely data-driven approaches often struggle in realistic settings characterized by sparse data, high-dimensional design spaces, and nontrivial physical constraints. This perspective argues for a new generation of design systems that transcend black-box modeling by integrating domain knowledge, physics-informed learning, and in…

A live blog of WWDC, where OS redesigns, new naming conventions, and more are expected, after failing to deliver on Apple Intelligence, unveiled at WWDC 2024 (Allison Johnson/The Verge)
https://www.theverge.com/tech/681646/apple-wwdc-2025-news-rumors-ios-26…

WWDC 2025: all the news from Apple’s annual developer conference
Apple faces some unusually high stakes at this year’s WWDC.

This https://arxiv.org/abs/2505.02198 has been replaced.
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Student Perspectives on the Benefits and Risks of AI in Education
The use of chatbots equipped with artificial intelligence (AI) in educational settings has increased in recent years, showing potential to support teaching and learning. However, the adoption of these technologies has raised concerns about their impact on academic integrity, students' ability to problem-solve independently, and potential underlying biases. To better understand students' perspectives and experiences with these tools, a survey was conducted at a large public university in the Uni…

A Comprehensive Survey on Bio-Inspired Algorithms: Taxonomy, Applications, and Future Directions
Shriyank Somvanshi, Md Monzurul Islam, Syed Aaqib Javed, Gaurab Chhetri, Kazi Sifatul Islam, Tausif Islam Chowdhury, Sazzad Bin Bashar Polock, Anandi Dutta, Subasish Das
https://arxiv.org/abs/2506.04238…

A Comprehensive Survey on Bio-Inspired Algorithms: Taxonomy, Applications, and Future Directions
Bio-inspired algorithms (BIAs) utilize natural processes such as evolution, swarm behavior, foraging, and plant growth to solve complex, nonlinear, high-dimensional optimization problems. This survey categorizes BIAs into eight groups: evolutionary, swarm intelligence, physics-inspired, ecosystem and plant-based, predator-prey, neural-inspired, human-inspired, and hybrid approaches, and reviews their core principles, strengths, and limitations. We illustrate the usage of these algorithms in mac…

This https://arxiv.org/abs/2404.06432 has been replaced.
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Missing Pieces: How Do Designs that Expose Uncertainty Longitudinally Impact Trust in AI Decision Aids? An In Situ Study of Gig Drivers
Decision aids based on artificial intelligence (AI) induce a wide range of outcomes when they are deployed in uncertain environments. In this paper, we investigate how users' trust in recommendations from an AI decision aid is impacted over time by designs that expose uncertainty in predicted outcomes. Unlike previous work, we focus on gig driving - a real-world, repeated decision-making context. We report on a longitudinal mixed-methods study ($n=51$) where we measured gig drivers' trust as th…

This https://arxiv.org/abs/2503.09969 has been replaced.
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Detecting Dataset Bias in Medical AI: A Generalized and Modality-Agnostic Auditing Framework
Artificial Intelligence (AI) is now firmly at the center of evidence-based medicine. Despite many success stories that edge the path of AI's rise in healthcare, there are comparably many reports of significant shortcomings and unexpected behavior of AI in deployment. A major reason for these limitations is AI's reliance on association-based learning, where non-representative machine learning datasets can amplify latent bias during training and/or hide it during testing. To unlock new tools capa…

Using Diffusion Models to do Data Assimilation
Daniel Hodyss, Matthias Morzfeld
https://arxiv.org/abs/2506.02249 https://arxiv.org/pd…

Using Diffusion Models to do Data Assimilation
The recent surge in machine learning (ML) methods for geophysical modeling has raised the question of how these same ML methods might be applied to data assimilation (DA). We focus on diffusion modeling (a form of generative artificial intelligence) and on systems that can perform the entire DA, rather than on ML-based tools that are used within an otherwise conventional DA system. We explain that there are (at least) three different types of diffusion-based DA systems and we show in detail tha…

Nvidia CEO Jensen Huang warns the UK lacks the digital infrastructure needed to capitalize on AI despite "incredible" research talent, as PM Starmer pledges £1B (Tim Bradshaw/Financial Times)
https://www.ft.com/content/cc04adfb-81b2-477f-b85c-ce042e8f83a8…

Nvidia chief says UK lacks digital infrastructure as Keir Starmer pledges £1bn for AI
Jensen Huang seeks ‘sovereign’ artificial intelligence deals that diversify US chip giant’s business away from Big Tech groups

This https://arxiv.org/abs/2207.04285 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Closer Look into Transformer-Based Code Intelligence Through Code Transformation: Challenges and Opportunities
Transformer-based models have demonstrated state-of-the-art performance in many intelligent coding tasks such as code comment generation and code completion. Previous studies show that deep learning models are sensitive to the input variations, but few studies have systematically studied the robustness of Transformer under perturbed input code. In this work, we empirically study the effect of semantic-preserving code transformation on the performance of Transformer. Specifically, 24 and 27 code…

This https://arxiv.org/abs/2506.01848 has been replaced.
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Identifying Key Expert Actors in Cybercrime Forums Based on their Technical Expertise
The advent of Big Data has made the collection and analysis of cyber threat intelligence challenging due to its volume, leading research to focus on identifying key threat actors; yet these studies have failed to consider the technical expertise of these actors. Expertise, especially towards specific attack patterns, is crucial for cybercrime intelligence, as it focuses on targeting actors with the knowledge and skills to attack enterprises. Using CVEs and CAPEC classifications to build a bimod…

Conversational Alignment with Artificial Intelligence in Context
Rachel Katharine Sterken (University of Hong Kong), James Ravi Kirkpatrick (University of Oxford,Magdalen College, Oxford)
https://arxiv.org/abs/2505.22907

Conversational Alignment with Artificial Intelligence in Context
The development of sophisticated artificial intelligence (AI) conversational agents based on large language models raises important questions about the relationship between human norms, values, and practices and AI design and performance. This article explores what it means for AI agents to be conversationally aligned to human communicative norms and practices for handling context and common ground and proposes a new framework for evaluating developers' design choices. We begin by drawing on th…

What Comes After Harm? Mapping Reparative Actions in AI through Justice Frameworks
Sijia Xiao, Haodi Zou, Alice Qian Zhang, Deepak Kumar, Hong Shen, Jason Hong, Motahhare Eslami
https://arxiv.org/abs/2506.05687

What Comes After Harm? Mapping Reparative Actions in AI through Justice Frameworks
As Artificial Intelligence (AI) systems are integrated into more aspects of society, they offer new capabilities but also cause a range of harms that are drawing increasing scrutiny. A large body of work in the Responsible AI community has focused on identifying and auditing these harms. However, much less is understood about what happens after harm occurs: what constitutes reparation, who initiates it, and how effective these reparations are. In this paper, we develop a taxonomy of AI harm rep…

ExDiff: A Framework for Simulating Diffusion Processes on Complex Networks with Explainable AI Integration
Annamaria Defilippo, Ugo Lomoio, Barbara Puccio, Pierangelo Veltri, Pietro Hiram Guzzi
https://arxiv.org/abs/2506.04271

ExDiff: A Framework for Simulating Diffusion Processes on Complex Networks with Explainable AI Integration
Understanding and controlling diffusion processes in complex networks is critical across domains ranging from epidemiology to information science. Here, we present ExDiff, an interactive and modular computational framework that integrates network simulation, graph neural networks (GNNs), and explainable artificial intelligence (XAI) to model and interpret diffusion dynamics. ExDiff combines classical compartmental models with deep learning techniques to capture both the structural and temporal …

Rethinking the effects of data contamination in Code Intelligence
Zhen Yang, Hongyi Lin, Yifan He, Jie Xu, Zeyu Sun, Shuo Liu, Pengpeng Wang, Zhongxing Yu, Qingyuan Liang
https://arxiv.org/abs/2506.02791

Rethinking the effects of data contamination in Code Intelligence
In recent years, code intelligence has gained increasing importance in the field of automated software engineering. Meanwhile, the widespread adoption of Pretrained Language Models (PLMs) and Large Language Models (LLMs) has raised concerns regarding data contamination and its potential impact on model performance evaluation. This paper presents a systematic empirical study to investigate the fine-grained data contamination on code intelligence tasks. Our study involves diverse representative P…

Sources: Mistral AI has closed or is closing a handful of commercial contracts, each worth $100M over three to five years, as it expands its own infrastructure (Financial Times)
https://www.ft.com/content/65f79839-d637-48a7-a0f2-3fab8952b315

Europe’s Mistral benefits from search for artificial intelligence alternatives
Start-up has embarked on expansion of its own infrastructure and secured significant contracts

US military IT specialist arrested for allegedly trying to leak secrets to foreign government https://therecord.media/defense-intelligence-agency-it-specialist-suspected-leak-foreign-government

This https://arxiv.org/abs/2205.09337 has been replaced.
link: https://scholar.google.com/scholar?q=a

Deep Learning in Business Analytics: A Clash of Expectations and Reality
Our fast-paced digital economy shaped by global competition requires increased data-driven decision-making based on artificial intelligence (AI) and machine learning (ML). The benefits of deep learning (DL) are manifold, but it comes with limitations that have, so far, interfered with widespread industry adoption. This paper explains why DL, despite its popularity, has difficulties speeding up its adoption within business analytics. It is shown that the adoption of deep learning is not only aff…

The UK High Court warns lawyers of possible criminal charges for using AI-generated fake legal material, citing two recent cases with hallucinated content (Lizzie Dearden/New York Times)
https://www.nytimes.com/2025/06/06/world/europe/england-high-court-…

UK Court Warns Lawyers Can Be Prosecuted Over A.I. Tools That ‘Hallucinate’ Fake Material
A senior judge said on Friday that lawyers could be prosecuted for presenting material that had been “hallucinated” by artificial intelligence tools.

Scenarios in Computing Research: A Systematic Review of the Use of Scenario Methods for Exploring the Future of Computing Technologies in Society
Julia Barnett, Kimon Kieslich, Jasmine Sinchai, Nicholas Diakopoulos
https://arxiv.org/abs/2506.05605

Scenarios in Computing Research: A Systematic Review of the Use of Scenario Methods for Exploring the Future of Computing Technologies in Society
Scenario building is an established method to anticipate the future of emerging technologies. Its primary goal is to use narratives to map future trajectories of technology development and sociotechnical adoption. Following this process, risks and benefits can be identified early on, and strategies can be developed that strive for desirable futures. In recent years, computer science has adopted this method and applied it to various technologies, including Artificial Intelligence (AI). Because c…

AI Data Development: A Scorecard for the System Card Framework
Tadesse K. Bahiru, Haileleol Tibebu, Ioannis A. Kakadiaris
https://arxiv.org/abs/2506.02071 …

AI Data Development: A Scorecard for the System Card Framework
Artificial intelligence has transformed numerous industries, from healthcare to finance, enhancing decision-making through automated systems. However, the reliability of these systems is mainly dependent on the quality of the underlying datasets, raising ongoing concerns about transparency, accountability, and potential biases. This paper introduces a scorecard designed to evaluate the development of AI datasets, focusing on five key areas from the system card framework data development life cy…

Is PMBOK Guide the Right Fit for AI? Re-evaluating Project Management in the Face of Artificial Intelligence Projects
Alexey Burdakov, Max Jaihyun Ahn
https://arxiv.org/abs/2506.02214

Is PMBOK Guide the Right Fit for AI? Re-evaluating Project Management in the Face of Artificial Intelligence Projects
This paper critically evaluates the applicability of the Project Management Body of Knowledge (PMBOK) Guide framework to Artificial Intelligence (AI) software projects, highlighting key limitations and proposing tailored adaptations. Unlike traditional projects, AI initiatives rely heavily on complex data, iterative experimentation, and specialized expertise while navigating significant ethical considerations. Our analysis identifies gaps in the PMBOK Guide, including its limited focus on data …

Private GPTs for LLM-driven testing in software development and machine learning
Jakub Jagielski, Markus Abel
https://arxiv.org/abs/2506.06509 https://

Private GPTs for LLM-driven testing in software development and machine learning
In this contribution, we examine the capability of private GPTs to automatically generate executable test code based on requirements. More specifically, we use acceptance criteria as input, formulated as part of epics, or stories, which are typically used in modern development processes. This gives product owners, or business intelligence, respectively, a way to directly produce testable criteria through the use of LLMs. We explore the quality of the so-produced tests in two ways: i) directly b…

An interview with Jony Ive and Laurene Powell Jobs on tech's next chapter, meeting in 1997, Steve Jobs, Apple, Powell Jobs' io investment in 2019, AI, and more (Matthew Garrahan/Financial Times)
https://www.ft.com/content/7f0a45b0-a3cc-4e1c-be71-1b7b42958d4…

‘Humanity deserves better’: Jony Ive and Laurene Powell Jobs on tech’s next chapter
After Apple, the Silicon Valley visionaries are looking to artificial intelligence to shape the future again

Feeling Guilty Being a c(ai)borg: Navigating the Tensions Between Guilt and Empowerment in AI Use
Konstantin Aal, Tanja Aal, Vasil Navumau, David Unbehaun, Claudia M\"uller, Volker Wulf, Sarah R\"uller
https://arxiv.org/abs/2506.00094

Feeling Guilty Being a c(ai)borg: Navigating the Tensions Between Guilt and Empowerment in AI Use
This paper explores the emotional, ethical and practical dimensions of integrating Artificial Intelligence (AI) into personal and professional workflows, focusing on the concept of feeling guilty as a 'c(ai)borg' - a human augmented by AI. Inspired by Donna Haraway's Cyborg Manifesto, the study explores how AI challenges traditional notions of creativity, originality and intellectual labour. Using an autoethnographic approach, the authors reflect on their year-long experiences with AI tools, re…

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things
Kai Li, Conggai Li, Xin Yuan, Shenghong Li, Sai Zou, Syed Sohail Ahmed, Wei Ni, Dusit Niyato, Abbas Jamalipour, Falko Dressler, Ozgur B. Akan
https://arxiv.org/abs/2505.23792

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things
This paper focuses on Zero-Trust Foundation Models (ZTFMs), a novel paradigm that embeds zero-trust security principles into the lifecycle of foundation models (FMs) for Internet of Things (IoT) systems. By integrating core tenets, such as continuous verification, least privilege access (LPA), data confidentiality, and behavioral analytics into the design, training, and deployment of FMs, ZTFMs can enable secure, privacy-preserving AI across distributed, heterogeneous, and potentially adversari…

Some creatives and academics are rejecting AI on environmental and ethical grounds, and describe the pressure they feel to use AI to "keep up" with others (Emine Saner/The Guardian)
https://www.theguardian.com/technology/202

This https://arxiv.org/abs/2505.22767 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

In Dialogue with Intelligence: Rethinking Large Language Models as Collective Knowledge
Large Language Models (LLMs) are typically analysed through architectural, behavioural, or training-data lenses. This article offers a theoretical and experiential re-framing: LLMs as dynamic instantiations of Collective human Knowledge (CK), where intelligence is evoked through dialogue rather than stored statically. Drawing on concepts from neuroscience and AI, and grounded in sustained interaction with ChatGPT-4, I examine emergent dialogue patterns, the implications of fine-tuning, and the …

From Theory to Practice: Real-World Use Cases on Trustworthy LLM-Driven Process Modeling, Prediction and Automation
Peter Pfeiffer, Alexander Rombach, Maxim Majlatow, Nijat Mehdiyev
https://arxiv.org/abs/2506.03801

From Theory to Practice: Real-World Use Cases on Trustworthy LLM-Driven Process Modeling, Prediction and Automation
Traditional Business Process Management (BPM) struggles with rigidity, opacity, and scalability in dynamic environments while emerging Large Language Models (LLMs) present transformative opportunities alongside risks. This paper explores four real-world use cases that demonstrate how LLMs, augmented with trustworthy process intelligence, redefine process modeling, prediction, and automation. Grounded in early-stage research projects with industrial partners, the work spans manufacturing, modeli…

This https://arxiv.org/abs/2409.14644 has been replaced.
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An Effective Approach to Embedding Source Code by Combining Large Language and Sentence Embedding Models
The advent of large language models (LLMs) has significantly advanced artificial intelligence (AI) in software engineering (SE), with source code embeddings playing a crucial role in tasks such as source code clone detection and source code clustering. However, existing methods for source code embedding, including those based on LLMs, often rely on costly supervised training or fine-tuning for domain adaptation. This paper proposes a novel approach to embedding source code by combining large la…

A Systematic Mapping Study on Software Architecture for AI-based Mobility Systems
Amra Ramic, Stefan Kugele
https://arxiv.org/abs/2506.01595 https://

A Systematic Mapping Study on Software Architecture for AI-based Mobility Systems
Background: Due to their diversity, complexity, and above all importance, safety-critical and dependable systems must be developed with special diligence. Criticality increases as these systems likely contain artificial intelligence (AI) components known for their uncertainty. As software and reference architectures form the backbone of any successful system, including safety-critical dependable systems with learning-enabled components, choosing the suitable architecture that guarantees safety …