Weekly Review 10 July 2026

Some interesting links that I Tweeted about in the last week (I also post these on Mastodon, Threads, Newsmast, and Bluesky):

1. The AI bubble is a lot like the dotcom boom of the 1990s, and when it pops it will take down the global economy: https://www.theregister.com/ai-and-ml/2026/06/29/how-the-ai-bubble-could-pop-and-take-down-the-global-economy-according-to-the-bis/5263793
2. Ford has to re-hire its experienced engineers after AI fails: https://www.theguardian.com/technology/2026/jun/30/ai-backfired-so-ford-had-to-rehire-humans-greybeard-engineers
3. How to add Claude AI to a Python application: https://www.kdnuggets.com/getting-started-with-the-claude-api-in-python
4. The energy demands of AI means Google has once again missed its climate goals: https://futurism.com/artificial-intelligence/google-missed-climate-goals-ai
5. Bills from using AI are starting to get out of control: https://www.theregister.com/ai-and-ml/2026/07/03/ai-bills-are-baffling-the-c-suite-after-shift-to-usage-based-pricing/5266383
6. AI has made posting pictures of your kids online dangerous: https://www.theguardian.com/society/2026/jul/03/ai-sexual-abuse-fears-uk-parents-warned-posting-images-children-national-crime-agency
7. A manager's obsessive use of AI leads to employees quitting: https://futurism.com/artificial-intelligence/bosses-obsessed-with-ai
8. What it really means when AI are described as "stochastic parrots": https://spectrum.ieee.org/stochastic-parrot
9. International collaboration on AI is needed before it has its "Chernobyl moment": https://futurism.com/artificial-intelligence/ai-chernobyl-moment
10. The pros and cons of AI fitness coaches: https://www.rnz.co.nz/life/wellbeing/ai-can-be-a-personal-trainer-in-your-pocket-but-is-it-safeThe
11. People who use AI the most to answer health questions are also the most likely to fall for anti-vax lies: https://www.theguardian.com/technology/2026/jun/30/ai-chatbot-use-anti-vaccine-myths-poll
12. A lawsuit over defamatory claims hallucinated by an AI: https://www.theregister.com/legal/2026/07/02/startup-sues-palo-alto-networks-koi-security-saying-an-ai-hallucinated-report-falsely-linked-it-to-chinese-espionage/5266201
13. Even ivy-league students will use AI to cheat: https://futurism.com/artificial-intelligence/brown-university-professor-cheating-scandal-ivy-league
14. If lazy university administrators continue to use a simple metric to measure academics' performance, academics will game that metric: https://www.the-scientist.com/a-researcher-s-suspiciously-high-h-index-revealed-a-vast-citation-ring-74625
15. Generative AI is really messing up the research grant application system: https://www.insidehighered.com/news/faculty/research/2026/07/02/new-ai-agents-pose-existential-threat-grant-awarding
16. The demands of AI are shortening the development cycle of chips: https://spectrum.ieee.org/ai-chip-design-fab-ucla
17. The problem with AI browsers is that websites can break their guard rails: https://arstechnica.com/security/2026/06/ai-browsers-can-be-lulled-into-a-dream-world-where-guardrails-no-longer-apply/
18. An overview of Claude Sonnet 5: https://www.techrepublic.com/article/news-claude-sonnet-5-everything-you-need-to-know/
19. AI puts so much demand on databases, we need AI to run the databases: https://www.theregister.com/ai-and-ml/2026/06/30/ai-agents-cause-of-database-sprawl-and-also-the-proposed-solution/5264430
20. AI will make inequality worse than it is now: https://www.theguardian.com/technology/2026/jul/01/un-report-ai-inequality
21. AI can find security vulnerabilities, but a lot of vulnerabilities are caused by basic stupidity: https://www.theregister.com/security/2026/06/29/ai-may-be-good-at-finding-security-vulnerabilities-but-it-cant-beat-human-stupidity/5263262
22. It's still possible to trick an AI into breaking its guard rails: https://www.theregister.com/ai-and-ml/2026/06/30/security-researchers-tricked-llms-into-giving-them-cocaine-recipes-by-abusing-role-models-for-prompt-injection/5264115
23. AI cannot yet draft a solid will: https://www.theregister.com/ai-and-ml/2026/06/30/where-theres-a-will-ai-still-has-work-to-do/5264033
24. Conventional IT governance approaches are not suitable for AI: https://www.informationweek.com/it-leadership/the-hidden-costs-cios-face-to-make-data-ai-ready
25. Cloudflare is now blocking AI web crawlers: https://dataconomy.com/2026/07/03/cloudflare-will-block-ai-crawlers-unless-sites-opt-in/
26. Companies that add AI end up adding more people, but not right away: https://www.theregister.com/ai-and-ml/2026/07/02/companies-that-add-more-ai-also-add-more-people/5266134

IEEE Transactions on Neural Networks and Learning Systems, Volume 37, Issue 7, July 2026

1) Deep Learning for Video Anomaly Detection: A Review

Author(s): P. Wu, C. Pan, Y. Yan, G. Pang, Q. Yan, P. Wang, Y. Zhang

Pages: 3010 - 3030

2) A Survey on Vision--Language--Action Models for Embodied AI

Author(s): Y. Ma, Z. Song, Y. Zhuang, J. Hao, I. King

Pages: 3031 - 3051

3) Graph Transformers: A Survey

Author(s): A. Shehzad, F. Xia, S. Abid, C. Peng, S. Yu, D. Zhang, K. Verspoor

Pages: 3052 - 3071

4) Robust Least Squares Twin Support Vector Machine With Adaptive Pinball Loss

Author(s): H. -J. Xing, S. -W. Wang, Z. -C. He, Y. -D. Wang

Pages: 3072 - 3086

5) MotifGT-DTI: Pivotal Motif-Based Graph Transformer Model Improves Drug--Target Interaction Prediction

Author(s): W. Tian, M. Zeng, J. Wang, C. Lu

Pages: 3087 - 3101

6) A High-Accuracy Probabilistic-Based Sigmoid Approximator Incorporating Memory-Saving and Time-Efficient Strategies

Author(s): W. Lu, C. -S. Leung, F. Qin, T. Cao, W. Zhang, Y. Shi, Y. Ke, Z. Zang

Pages: 3102 - 3115

7) Physical Parameter Dependencies in Mechanical Reservoir Computing: Structural Analysis, Actuation, and Improved Processing

Author(s): M. Austin, K. Nakajima

Pages: 3116 - 3130

8) HSA2M: Hierarchical Spike Aggregation Activation Map for Visual Explanations From Spiking Neural Networks

Author(s): M. Yang, X. Wu, M. Yu Wang

Pages: 3131 - 3145

9) Multiagent Deep Reinforcement Learning With Evolutionary Strategy for Mobile Charging Vehicles Dispatching

Author(s): H. Li, B. Jeong

Pages: 3146 - 3160

10) Exploiting Scale-Variant Attention for Segmenting Small Medical Objects

Author(s): W. Dai, R. Liu, Z. Wu, T. Wu, M. Wang, J. Zhou, Y. Yuan, J. Liu

Pages: 3161 - 3175

11) Accurate and Robust Neural Architecture Search via a Flexible Supernet

Author(s): Y. Feng, Y. Ou, Y. Sun

Pages: 3176 - 3190

12) CPFformer: A Hierarchical-Based Graph Modeling Fusion Framework for Making the Emotional Features of Chinese Poetry Pronunciation More Controllable

Author(s): Q. Wang, K. Li, J. Zhou, X. Wang, J. Qin, C. Yu

Pages: 3191 - 3205

13) Lightweight Multi-Dilated Transformer for Image Deblurring

Author(s): Z. Zhao, Z. Tao, J. Pan

Pages: 3206 - 3217

14) Funny-Valen-Tine: Planning Solution Distribution Enhances Machine Abstract Reasoning Ability

Author(s): R. Song, B. Yuan

Pages: 3218 - 3231

15) ScaDyG: A New Paradigm for Large-Scale Dynamic Graph Learning

Author(s): X. Wu, X. Li, R. -H. Li, K. Zhao, G. Wang

Pages: 3232 - 3246

16) Implicit Illumination-Aware Representation With Cross-Modal Prefusion Alignment for Universal Multispectral Pedestrian Detection

Author(s): Y. Gong, L. Lin, Y. Luo, H. Liu, Y. Gao, J. Zhao, Z. Song, X. Hu

Pages: 3247 - 3261

17) IEGSCL: Interaction-Enhanced Graph Neural Sequence Contrastive Learning for Microscopic Diffusion Prediction

Author(s): Y. Chang, F. Xiong, S. Pan, J. Wu, L. Wang, A. Beheshti

Pages: 3262 - 3276

18) DGNMF: Dynamic Diffusion Graph Nonnegative Matrix Factorization

Author(s): C. Tian, W. Wu, L. Jiao, L. Li, X. Liu, F. Liu, W. Ma, S. Yang

Pages: 3277 - 3289

19) Multisynchronization of Delayed Coupled Neural Networks With General Activation Functions via Impulsive Control

Author(s): Y. Liu, Z. Wang, X. Huang, M. Xiao

Pages: 3290 - 3299

20) Boosting Adversarial Training With Mitigating Hard Sample Interference

Author(s): B. Hu, K. Guo, T. Qiu, S. Guo

Pages: 3300 - 3310

21) Open Set Domain Adaptation via Known Joint Distribution Matching and Unknown Classification Risk Reformulation

Author(s): S. Chen, P. Xuan, L. He

Pages: 3311 - 3324

22) Self-Supervised Koopman Operator Learning for Distributed Final Synchronization Prediction of Networked Nonlinear Dynamics

Author(s): F. Hu, H. -T. Zhang, C. Lv, J. Wang

Pages: 3325 - 3335

23) Multiphase and Multitask Prompt Tuning for LLM-Based Context-Aware Machine Translation

Author(s): X. Lyu, J. Li, D. Wei, M. Zhang, S. Tao, H. Yang, M. Zhang

Pages: 3336 - 3348

24) HarmoFGL: Harmonizing GNN Latent Factors for Federated Graph Learning

Author(s): Y. Yan, Z. Zhu, S. Zheng, H. Xu, Y. Zhao, K. He, Y. Zhao

Pages: 3349 - 3359

25) Anomaly Subgraph Detection on Multiple Associated Attributed Networks

Author(s): N. Wu, Y. Sun, Y. Zhao, W. Wang, X. Liu, J. Li

Pages: 3360 - 3374

26) Large Language Models Are Multitask Chain-of-Thought Prompting Optimizers

Author(s): F. Jin, Y. Tan

Pages: 3375 - 3384

27) Rethinking Topic Modeling With Information Bottleneck Principle

Author(s): Z. Duan, X. Hu, B. Chen, C. Wang, X. Cao, F. Meng, M. Zhou

Pages: 3385 - 3398

28) Boosting Semi-Supervised Medical Image Segmentation Through Inter-Instance Information Complementarity

Author(s): S. Wu, R. Liu, H. Wei, L. Liu, J. Wen, Q. Miao

Pages: 3399 - 3410

29) A New Neural Network PI-Funnel Distributed Control for Cooperative Manipulator With Global Prescribed Performance

Author(s): C. -H. Zhang, Z. -Y. Hu, Y. -J. Li, Y. Zhang, C. -C. Hua

Pages: 3411 - 3419

30) Enhanced Residual Tensor Norm Minimization for Multiview Subspace Clustering

Author(s): Q. Zheng

Pages: 3420 - 3434

31) GHAttack: Generative Adversarial Attacks on Heterogeneous Graph Neural Networks

Author(s): S. Li, X. Liao, H. Zhu, J. Le, L. Chu

Pages: 3435 - 3449

32) A Dynamic Neural Network-Based Control Method Using Reinforcement Learning for Nonlinear Parameter-Varying System With Application to Morphing Aircraft

Author(s): C. -X. Li, H. -N. Wu

Pages: 3450 - 3462

33) Distributed Learning for Online Stochastic Mixed Equilibrium Problems With Heavy-Tailed Noises

Author(s): H. Xu, K. Lu, Y. -L. Wang, Q. Zhu

Pages: 3463 - 3474

34) Diffusion-Augmented Graph Contrastive Learning for Knowledge-Aware Recommendation

Author(s): J. Zhang, X. Jiang, Y. Wang, S. Meng, C. Zhou

Pages: 3475 - 3487

35) Brain-Inspired Chaotic Graph Backpropagation for Combinatorial Optimization

Author(s): P. Tao, K. Aihara, L. Chen

Pages: 3488 - 3500

Monday, July 6, 2026

Soft Computing, Volume 30, Issue 6, June 2026

1) Semi-De Morgan almost distributive lattices

Author(s): Gezahagne Mulat Addis, Wondwosen Zemene Norahun, B. Davvaz

Pages: 3783 - 3798

2) F-expansion method analysis of Navier-Bernoulli hypothesis and Love’s hypothesis driven nonlinear dispersive waves in Murnaghan’s cylindrical elastic rod

Author(s): Rathinavel Silambarasan, Adem Kilicman, Zakia Hammouch

Pages: 3799 - 3827

3) Enhancing grid stability reactive power management in photovoltaic and superconducting magnetic energy storage inverters using hybrid approach

Author(s): Dinesh Kumar Singh, Manoranjan Kumar Sinha, Sangram Keshari Das

Pages: 3829 - 3842

4) A hybrid atom search optimization algorithm and its application in quantitative structure–activity relationship modeling

Author(s): Yu Liu, Yu-kun Wang, Yu-tong Li

Pages: 3843 - 3871

5) Fuzzy Tsetlin automata and their application in analog computing

Author(s): Evgeny Kagan, Alexander Rybalov

Pages: 3873 - 3887

6) Credibilistic portfolio optimization with investors’ coherent perceptions: a three-way decision approach

Author(s): He Li, Xiu Jin, Yueli Liu

Pages: 3889 - 3928

7) Fractional dynamics in complex media: a meshless numerical framework for distributed-order models with Riesz diffusion

Author(s): Mohammad Hossein Derakhshan, Safar Irandoust Pakchin

Pages: 3929 - 3950

8) Entropy-based goodness-of-fit test for the Weibull distribution under fuzzy data

Author(s): Hadi Alizadeh Noughabi

Pages: 3951 - 3968

9) Integrated soft computing approach in modelling and optimising mechanical oil expression from pentaclethra macrophylla benth kernels

Author(s): Clement Adesoji Ogunlade, Ademola Kabir Aremu, Rahman Akinoso

Pages: 3969 - 3983

10) Deep learning techniques for early diagnosis of Alzheimer’s disease and frontotemporal dementia using EEG signals

Author(s): Amir Hossein Hachamnia, Ali MehriMaryam Jamaati

Pages: 3985 - 4002

11) A condition-based maintenance strategy for the aircraft routing problem to cost minimization and fair assignment of aircraft: a robust optimization approach

Author(s): Hiwa Esmaeilzadeh, Alireza Rashidi Komijan, Reza Tavakkoli-Moghaddam

Pages: 4003 - 4025

12) A redundancy allocation problem for a series–parallel system with multiple choice technologies considering fuzzy sense with ambiguity and vagueness

Author(s): Anushri Maji, Avijit Duary, Shyamal Kumar Mondal

Pages: 4027 - 4063

13) Cluster-based framework for metaheuristic empirical similarity

Author(s): Jair Pereira Junior, Claus Aranha

Pages: 4065 - 4085

14) Enhanced opposition-based sea horse optimizer to solve optimization problems

Author(s): Priteesha Sarangi, Prabhujit Mohapatra

Pages: 4087 - 4110

15) Access points deployment in data offloading using evolutionary optimization algorithms

Author(s): Maryam Jawad Kadhim, Rasool Sadeghi, Reihaneh Khorsand

Pages: 4111 - 4125

16) The single-dependence sequential testing problem for the living kidney donor workup process

Author(s): Joshua Nielsen, Hadi El-Amine, Naoru Koizumi

Pages: 4127 - 4142

17) Dynamic planar hub location considering stochastic time-dependent demand: A hybrid approach

Author(s): Amir Khaleghi

Pages: 4143 - 4168

18) Reciprocal results for the study of some optimization models

Author(s): Savin Treanţă

Pages: 4169 - 4177

19) Intelligent prediction of volcanic activity using 3D distributed mobile wireless sensor networks

Author(s): Fatma Sbiaa, Nadia Boufares, Mohamed Mabrouk

Pages: 4179 - 4199

20) Estimation of the microbial biomass carbon of soil using a hybrid multilayer perceptron-hunger games search algorithm

Author(s): Samad Emamgholizadeh, Changhyun Jun, Rasoul Ameri

Pages: 4201 - 4217

21) Preplysis: automation of time series data preprocessing & analysis

Author(s): Mehak Usmani, Zulfiqar Ali Memon

Pages: 4219 - 4236

22) A semi-supervised domain adaptive learning approach to unstructured road region semantic segmentation for greenhouse robots

Author(s): Bishu Gao, Liang Gong, Chengliang Liu

Pages: 4237 - 4249

23) Road crash severity classification: a novel integrated approach

Author(s): Rajendra Kumar Roul, Samridhi Mangla

Pages: 4251 - 4271

24) Coverage path planning for multiple UAVs in prioritized regions using ant colony optimization

Author(s): Sung Won Cho, Jae Hyeok Lee, Chulung Lee

Pages: 4273 - 4294

25) A hybrid approach to multi-objective unrelated parallel machine scheduling with a new interpretation of job batches and families

Author(s): Reza Alizadeh Foroutan

Pages: 4295 - 4326

26) Improved Grey Wolf Optimization and its application in regression testing

Author(s): Aishwarya Gupta, Bharat Krishan Mahaur

Pages: 4327 - 4346

27) A distributed PI-based dynamic task allocation method for multi-AUV systems

Author(s): Huizhen Yang, Jun Yang, Yuchen Lin

Pages: 4347 - 4364

28) MultiRel:Extracting multiple relation triplets by graph attention network

Author(s): Zixi Jia, Changzhi Duan, Jingyu Ru

Pages: 4365 - 4378

29) Neural network approaches for quantum energy level prediction

Author(s): Alireza Khalili Golmankhaneh, Roman Pasechnik, Palle E. T. Jørgensen

Pages: 4379 - 4385

30) Research on the application of the improved YOLOv10s algorithm in eye disease detection

Author(s): Hongfang Ma, Lihong Chang, Xue Bai

Pages: 4387 - 4412

31) Texture-aware 3D reconstruction via multi-level attention mechanisms and fission-based interactive learning

Author(s): Ashish Kumar Gupta, Piyush Kumar

Pages: 4413 - 4426

32) MB-PIRNN: Matrix-based physics-informed recurrent neural network for solving Lane-Emden type equation

Author(s): Maryam Babaei, Hassan Dana Mazraeh, Kourosh Parand

Pages: 4427 - 4446

33) Structure-enhanced embedding for attributed network with graph neural network in context of transfer learning

Author(s): Phu Pham

Pages: 4447 - 4466

34) Block-fused attention-driven adaptively-pooled ResNet model for improved cervical cancer classification

Author(s): Saurabh Saini, Kapil Ahuja, Akshat S. Chauhan

Pages: 4467 - 4495

35) Sub-factors based decision making with uncertainty for sustainable women empowerment

Author(s): Doli Adhikari, Kamal Hossain Gazi, Sankar Prasad Mondal

Pages: 4497 - 4542

36) Objective diagnosis of psychotic disorders using Multi-branch Deep Learning model on time-series motor activity signals

Author(s): Muzafar Mehraj Misgar, M. P. S. Bhatia

Pages: 4543 - 4560

37) Retraction Note: Sp-Closedness and convergent sequences in IFMS and its generalization to L-fuzzy metric space

Author(s): Vakeel A. Khan, Izhar Ali Khan, Mobeen Ahmad

Pages: 4561 - 4561

38) Retraction Note: Experimental and fuzzy modelling analysis on dynamic cutting force in micro milling

Author(s): Qun Ren, Marek Balazinski, Sofiane Achiche

Pages: 4563 - 4563

39) Retraction Note: Soft computing model using cluster-PCA in Port model for throughput forecasting

Author(s): Liupeng Jiang, He Jiang, Harry Haoxiang Wang

Pages: 4565 - 4565

40) Retraction Note: Artificial neural network-based secured communication strategy for vehicular ad hoc network

Author(s): B. V. D. S. Sekhar, Pamula Udayaraju, M. S. S. S. Srinivas

Pages: 4567 - 4567

Friday, July 3, 2026

Weekly Review 3 July 2026

Some interesting links that I Tweeted about in the last week (I also post these on Mastodon, Threads, Newsmast, and Bluesky):

1. AI find security vulnerabilities so quickly we need AI to find solutions: https://www.rnz.co.nz/news/science-and-technology/618615/fighting-ai-with-ai-the-only-way-to-keep-up-on-new-frenetic-frontier
2. AI coding costs will soon exceed the cost of human developers: https://www.theregister.com/ai-and-ml/2026/06/24/ai-coding-agents-could-soon-cost-more-than-the-developers-using-them/5260864
3. Loop engineering looks like a scheme to funnel more money to AI companies: https://www.theregister.com/ai-and-ml/2026/06/24/loop-engineering-latest-ai-buzzword-still-needs-humans-in-the-loop/5261735
4. People have no patience with AI service agents: https://futurism.com/artificial-intelligence/customers-fed-up-ai-service-agents
5. How to beomce an AI architect: https://www.kdnuggets.com/the-roadmap-to-becoming-an-ai-architect-in-2026
6. Microsoft used AI to analyse malware infrastructure, leading to it being taken down: https://www.theregister.com/security/2026/06/24/microsoft-uses-ai-to-link-two-malware-operations-in-racketeering-suit/5261656
7. What do mathematicians do now that AI can do maths?: https://spectrum.ieee.org/ai-in-mathematics
8. AI raises a lot of issues with disaster recovery planning: https://www.informationweek.com/incident-response/ai-disaster-recovery-planning-is-years-behind-ai-adoption
9. AI means that security incidents can quickly escalate: https://www.theregister.com/security/2026/06/23/five-eyes-spooks-warn-ai-means-infosec-incidents-can-become-major-operational-and-financial-crises/5259916
10. Games that used generative AI receive poorer reviews compared to human-only created games: https://www.extremetech.com/gaming/games-that-use-generative-ai-receive-53-poorer-firstmonth-reviews-study
11. Ideology should never be a reason to retract an article. Boycott the Journal of the New Zealand College of Clinical Psychologists. Do not submit to it, do not review for it, do not cite it: https://www.stuff.co.nz/nz-news/360997918/peer-reviewed-article-maori-author-removed-because-it-wasnt-line-organisations-values
12. Organisations need to start preparing now for the security risks posed by AI: https://www.rnz.co.nz/news/politics/616849/nz-organisations-told-to-prepare-for-significant-rise-in-risks-from-ai
13. There is a strong argument that the companies most responsible for replacing human workers with AI should be responsible for retraining those workers: https://www.theregister.com/ai-and-ml/2026/06/26/ai-giants-back-non-profit-to-retrain-workers-left-behind-by-ai/5262601
14. Medical AI can be tricked into disclosing confidential information: https://www.theregister.com/ai-and-ml/2026/06/24/medical-diagnosis-ais-can-be-tricked-into-telling-whose-data-trained-them/5261501
15. We need regulation of AI: https://www.rnz.co.nz/news/in-depth/618503/karen-hao-exposing-the-brute-force-of-ai-that-is-trying-to-make-humans-redundant
16. AI is starting to learn the nuances of human emotion: https://spectrum.ieee.org/emotion-ai-context
17. AI is driving up the price of everything: https://www.computerworld.com/article/4186923/the-ai-revolution-comes-with-a-hidden-tax.html
18. A project that uses AI to help screen for bowel cancer: https://www.rnz.co.nz/news/health/631840/ai-promises-breakthrough-in-bowel-cancer-detection
19. Organisations are rolling out AI faster than their infrastructure can cope with: https://www.theregister.com/devops/2026/06/24/companies-are-not-looking-before-theyre-leaping-into-the-ai-playpen/5261819
20. AI is the asbestos in the walls of our technological society says Cory Doctorow: https://arstechnica.com/gadgets/2026/06/how-to-burst-the-ai-bubble-strike-at-its-roots/
21. AI still can't tell the difference between fact and fiction: https://futurism.com/artificial-intelligence/duckduckgo-ai-trump-rabies
22. Adjusting the clock speed of GPU can reduce energy use without losing computation speed: https://spectrum.ieee.org/llm-training-energy-saving-trick
23. Experience software engineers are spending a lot of time fixing AI generated code: https://futurism.com/artificial-intelligence/software-engineers-crisis-drown-ai-code
24. AI helps to recover some of the text on a Roman scroll that was burned in the eruption of Vesuvius: https://www.theguardian.com/technology/2026/jun/24/ai-read-papyrus-scroll-burnt-vesuvius-eruption
25. Competitors can duplicate an AI if they can query it enough: https://www.computerworld.com/article/4189347/anthropic-accuses-alibaba-of-using-25000-fake-accounts-to-scrape-claude-ai-2.html

IEEE Transactions on Fuzzy Systems, Volume 34, Issue 7, July 2026

1) Fuzzy-Aware Loss for Source-Free Domain Adaptation in Visual Emotion Recognition

Author(s): Y. Zheng, Y. Zhang, Y. Wang, L. -P. Chau

Pages: 2077 - 2089

2) Multiview Fuzzy Clustering With Anchor Graph

Author(s): C. Liu, F. Nie, M. Chang, R. Wang, X. Li

Pages: 2090 - 2103

3) Partial Multilabel Feature Selection via Fuzzy Two-Stage Disambiguation and Weighted Pure Relevance

Author(s): C. Huang, D. Xu, Y. Kang, J. Dai

Pages: 2104 - 2117

4) Adaptive Fuzzy Consensus of Multiple Uncertain Euler–Lagrange Systems With Sampled-Data Output Interactions

Author(s): T. Wang, W. Zou, J. Guo

Pages: 2118 - 2128

5) Funnel-Based Predefined-Time Control for Heterogeneous Vehicles With General Narrow Tunnel Constraints

Author(s): T. Yang, S. Ding, G. Cui, Z. Lu

Pages: 2129 - 2138

6) Fuzzy Prescribed-Time Control for Bipartite Time-Varying Formation of Heterogeneous Multiagent Systems With Actuator Faults

Author(s): H. Zhang, W. Jin, Y. Yang, J. Zhang

Pages: 2139 - 2148

7) General Type-2 Hierarchical Fuzzy Model-Agnostic Explanation of Image Classification for XAI

Author(s): F. Yin, H. -K. Lam, D. Watson

Pages: 2149 - 2158

8) $\mathcal {L}_{1}$ Adaptive Fuzzy Control for Unmanned Aerial Vehicle With Disturbance Observer Under Uncertainties and Disturbances

Author(s): X. Xu, C. Wang, Z. Huang, J. Wang, H. Shen

Pages: 2159 - 2170

9) Power Fuzzy Clustering: Flexible Distance Metrics and Inclusion of Covariates

Author(s): P. T. Nguyen, C. Tortora, A. Punzo

Pages: 2171 - 2182

10) FMHC: A Fuzzy Multihierarchical Centrality Strategy for Node Evaluation in Hypergraphs

Author(s): S. Liu, Y. Tang, W. Pedrycz, K. Hirota, F. Yan

Pages: 2183 - 2196

11) Predicting Multiexpert Consensus in Medical Image Segmentation With Interpretability: An Enhanced Relative Fuzzy Connectedness Method

Author(s): T. Wu, Z. Xu, Y. Zheng

Pages: 2197 - 2210

12) MTSK-DA: Interpretable Multicenter Transfer via Discriminative Alignment and Attention-Guided Graph Regularization

Author(s): J. Yao, W. Fu, P. Qian, C. Wang, X. Guo, J. Liu, Z. Zhang

Pages: 2211 - 2224

13) Fin Stabilizer-Based Finite-Time ${{\mathcal{H}}_\infty }$ Interval Type-2 Fuzzy Synthesis for Ship Rolling Motion With Bouc–Wen Hysteresis Under Imperfect Premise Matching

Author(s): A. Arumugam, W. -J. Chang, Y. -C. Lee, Y. -H. Lin, L. Li, M. S. Aslam

Pages: 2225 - 2238

14) Explainable AI for Sentiment Classification With Type-1 Fuzzy and Type-2 Fuzzy Models

Author(s): S. Yadav, N. K. Verma

Pages: 2239 - 2251

15) Semisupervised Low-Rank Fuzzy Clustering for Hyperspectral Images

Author(s): Y. Wang, Z. Shi, L. Chen, J. Zhou, X. Shen, C. Zhang, W. Ding, C. L. P. Chen

Pages: 2252 - 2265

16) DioR: Distributed Cost-Sensitive Fuzzy-Entropy-Based Approach for Semisupervised Feature Selection

Author(s): H. Ju, L. Qiao, K. Liu, W. Ding, X. Yang, W. Pedrycz, M. Xu

Pages: 2266 - 2280

17) Fuzzy Intermittent Boundary Control for Nonlinear Delayed Markov Jump Distributed Parameter Systems

Author(s): Z. -P. Wang, H. -R. Su, J. Qiao, H. Han, H. -N. Wu, L. Huang

Pages: 2281 - 2295

18) Mechanism-Guided Virtual Sample Generation With Interval Type-2 Fuzzy Regulation: Application to Municipal Solid Waste Incineration

Author(s): J. Zhuang, H. Ding, J. Qiao

Pages: 2296 - 2307

19) Intensively Quantized Integrated Fuzzy Neural Network for High-Accuracy Image Classification

Author(s): J. Yao, Y. Guo

Pages: 2308 - 2322

20) Steering Angle Tracking Control Considering the Negative Effect of Unsprung Mass for the Kingpin Steering System Based on Interval Type-2 Fuzzy Logic Approach

Author(s): Z. Ma, Z. Zhang, C. Wang, W. Zhao, W. Cao

Pages: 2323 - 2336

21) Distributed Fuzzy Proportional-Integral State Estimation Over Sensor Networks With Pull-Type Gossip Protocols and Fading Data

Author(s): Y. Wang, Z. Wang, L. Zou, F. Wang

Pages: 2337 - 2350

22) $\varepsilon$-Nash Equilibrium Model Predictive Control for Takagi–Sugeno Fuzzy Multiagent Systems: A Finite-Horizon Noncooperative Game Approach

Author(s): Y. Dong, Z. Huang, Y. Yuan

Pages: 2351 - 2362

23) Dynamic Trend Modeling With Joint Interval Fuzzy Information Granulation: A Framework for Long-Term Forecasting of Interval-Valued Time Series

Author(s): Y. Jiang, F. Yu, W. Zeng, C. Ouyang, F. Li, J. Wang

Pages: 2363 - 2377

24) Multivariate Prediction Model With Adaptive Kernel Configuration Based on Asymmetric Transfer Entropy and Fuzzy $C$-Means in CNN-Transformer

Author(s): H. Hu, J. Zhan, J. H. Yoon, W. Ding

Pages: 2378 - 2392

25) Three-Way Conflict Resolution in Fuzzy Situation Tables With Nonlinear Conflict Functions

Author(s): J. Liu, M. Hu, W. Ding, W. Pedrycz, G. Lang

Pages: 2393 - 2407

26) A Predefined-Time Convergent Dual-Channel Fuzzy Attention RNN for Motion Planning of Robotic Systems: Application to Robot-Assisted Puncture

Author(s): B. Zheng, C. Li, D. Yan, Z. Zhang, J. Yu, P. X. Liu

Pages: 2408 - 2422

Wednesday, July 1, 2026

IEEE Transactions on Artificial Intelligence, Volume 7, Issue 7, July 2026

1) Emerging Synergies in Causality and Deep Generative Models: A Survey

Author(s): G. Zhou, S. Xie, G. -Y. Hao, S. Chen, B. Huang, X. Xu, C. Wang, L. Zhu, L. Yao, K. Zhang

Pages: 3634 - 3652

2) Methodologies for Diffusion Model Interpretability: A Systematic Review

Author(s): T. Lakhani, J. Wu, Y. -K. Lai, Z. Ji

Pages: 3653 - 3670

3) How Artificial Intelligence and Brain Connectivity Can Inform Outcome Prediction in Drug-Resistant Epilepsy

Author(s): E. Paolini, G. Menegaz, E. Tamilia, S. F. Storti

Pages: 3671 - 3687

4) A Survey of Progress in LLM Alignment From the Perspective of Reward Design

Author(s): M. Ji, Y. Wu, Z. Wu, S. Wang, J. Yang, M. Dras, U. Naseem

Pages: 3688 - 3702

5) Deployment-Aware Compression of Large Language Models for Edge Intelligence: A System-Level Survey

Author(s): E. Dritsas, M. Trigka

Pages: 3703 - 3718

6) Expanding Horizons of Level Diversity via Multiobjective Evolutionary Learning

Author(s): Q. Zhang, Z. Wang, Y. Li, K. Zhang, B. Yuan, J. Liu

Pages: 3719 - 3731

7) Federated Semi-Supervised Learning with Annotation Heterogeneity

Author(s): X. Shang, G. Huang, Y. Lu, J. Lou, B. Han, Y. -m. Cheung, H. Wang

Pages: 3732 - 3747

8) 1D-CXNet and 3D-CXNet: Enhancing Accuracy in Noncontact HR Monitoring With Limited Computational Resources

Author(s): A. A. Anil, S. Karthik, C. D. J. Poppen, M. Sivaprakasam, J. Joseph

Pages: 3748 - 3758

9) A Transducer-Adaptive Denoising Model for Medical Ultrasound Imaging

Author(s): M. Jiang, C. You, X. Li, X. Xiong, J. Li, M. Wang, Y. Guo, Y. Xiao, Y. Bai, D. Wu, T. Tan

Pages: 3759 - 3771

10) Inner-Probe: Discovering Copyright-Related Data Generation in LLM Architecture

Author(s): Q. Ma, R. -J. Zhu, P. Liu, R. Yan, F. Zhang, L. Liang, M. Li, Z. Yu, Z. Wang, Y. Cai, T. Huang

Pages: 3772 - 3786

11) LightningSHAP: A Cost-Effective Approach to Local Shapley Values Estimation

Author(s): D. Napolitano, L. Cagliero

Pages: 3787 - 3797

12) Energy-Efficient Supervised Learning With a Binary Stochastic Forward-Forward Algorithm

Author(s): R. Jaiswal, S. Datta, J. G. Makin

Pages: 3798 - 3807

13) ConSignformer: Conformer-Based Framework for Continuous Sign Language Recognition

Author(s): N. Aloysius, G. M, A. Sajjanhar, P. Nedungadi

Pages: 3808 - 3822

14) Harnessing Teacher’s Explanation for Improved Knowledge Distillation

Author(s): S. Chowdhury, B. Liang, A. Tizghadam, I. Albanese

Pages: 3823 - 3838

15) Uncertainty Estimation for Graph-Based Learning in Digital Pathology

Author(s): S. Heidari Gheshlaghi, N. Y. Soltani, M. Ganji

Pages: 3839 - 3849

16) Enhanced Masking-Differential Prompting (MDP): Defending Backdoor Attacks for Pre-trained Language Models Under Few-Shot Learning

Author(s): X. Zhong, K. W. Fok, V. L. L. Thing

Pages: 3850 - 3859

17) SWONA: Small-World Inspired Optimal Neural Architecture for Smart Neuropsychiatric Diagnostics

Author(s): S. Dwivedi, O. J. Pandey, R. M. Hegde

Pages: 3860 - 3871

18) Insider Threat Detection Using GCN and Bi-LSTM With Explicit and Implicit Graph Representations

Author(s): R. Yumlembam, B. Issac, S. M. Jacob, L. Yang, D. Krishnan

Pages: 3872 - 3883

19) ICAFS: Inter-Client-Aware Feature Selection for Vertical Federated Learning

Author(s): R. Jin, B. Tong, S. Yang, B. Hou, L. Shen

Pages: 3884 - 3896

20) Graph Machine Learning Framework for Gravimetry Data Analysis and Cavity Detection

Author(s): G. Panda, V. K. Singh, A. Kumar, M. Saharia, S. Kumar

Pages: 3897 - 3912

21) Enhancing Robustness in Deep Convolutional Neural Networks Through Multiresolution Learning

Author(s): H. Zhou, Y. Liang

Pages: 3913 - 3925

22) Occupant-Aware Deep Learning Model for Energy Prediction in Smart Buildings

Author(s): M. Jayashankara, B. Adhirathan, P. Chanak, S. K. Singh

Pages: 3926 - 3937

23) Finite-Time Bipartite Synchronization of Delayed Antagonistic Memristive Neural Networks: Optimizing Event-Triggered Controller Parameters

Author(s): X. Si, Z. Wang, X. Huang, M. Xiao

Pages: 3938 - 3949

24) Learning From M-Tuple Dominant Positive and Unlabeled Data

Author(s): J. Qin, J. Li, C. Hua, Y. Yang

Pages: 3950 - 3964

25) $\ell_{0}$-Norm Penalty Embedded Feature Selection in Universum Learning

Author(s): C. Li, J. Yin, Y. Shao, Y. Pan, W. Chen, Y. Song, I. W. Tsang

Pages: 3965 - 3978

26) DeepFilter: A Transformer-Style Framework for Accurate and Efficient Process Monitoring

Author(s): H. Wang, Z. Chen, L. Pan, X. Jiang, Y. Song, Q. He, X. Liu

Pages: 3979 - 3989

27) UNA-SAC: An Uncertainty-Aware Nonlinear Arbitration Method for Human–AI Shared Control

Author(s): S. Jiang, Y. -B. Zhao, Y. Kang, F. Xie, Y. -S. Zhao

Pages: 3990 - 4003

28) Alleviating Seasickness Through Brain–Computer Interface-Based Attention Shift

Author(s): X. Bao, K. Xu, J. Zhu, H. Huang, Q. Huang, Y. Li

Pages: 4004 - 4015

29) Smartphone-Based Noninvasive Automatic Dengue Detection Using Fingertip Video

Author(s): M. Mahmuda, B. Barkatullah, M. A. Rahman, J. Akter, N. Jahan, T. R. Prome, E. Haque, F. Ahmed

Pages: 4016 - 4030

30) Co-LLIETrack: Cotrained Low Light Image Enhancement Tracker for UAV Tracking

Author(s): V. Nageli, A. Jamal, R. K. Sai S Gorthi

Pages: 4031 - 4043

31) From Generation to Detection: Multimodal Generative AI and the Threat of Automated Misinformation

Author(s): R. Kumar, P. Bansal, S. Singh, S. Saha, A. Jatowt

Pages: 4044 - 4056

32) Acknowledging Valued Perspectives! User-Assisted Summarization by Leveraging Opinions and LLMs

Author(s): R. Kumar, T. Gupta, K. Kalra, S. Saha

Pages: 4057 - 4068

33) A Multitask GRU Deep Learning Model for Early Stage Prediction of Spatial Spread

Author(s):  . Rimjhim, S. K. Dandapat

Pages: 4069 - 4080

34) Handling Condition-Aware Noise and Outlier Disparities: A Transfer Learning Framework for Robust Cross-Domain Process Monitoring

Author(s): K. Zhong, W. Zhang, Z. Fan, D. Huang

Pages: 4081 - 4093

35) A Hybrid KAN-ANN Based Model for Interpretable and Enhanced Short-Term Load Forecasting

Author(s): B. Jiang, Y. Wang, Q. Wang, H. Geng

Pages: 4094 - 4105

36) Histoformer: A Frequency Domain-Based Convolutional Transformer for Improved Breast Cancer Classification

Author(s): Babita, D. R. Nayak

Pages: 4106 - 4117

37) ECG-Based Seizure Prediction Using Progressive Feature Fusion Mamba

Author(s): K. Shu, L. Wu, C. Yu, A. Liu, R. Qian, X. Chen

Pages: 4118 - 4133

38) From Numerals to Letters: A Meta Learning-Based Robotic Calligraphy System

Author(s): X. Chang, Z. -H. Guo, F. Chao, L. Yang, C. Shang, N. Copner, C. Finlayson, Q. Shen

Pages: 4134 - 4145

39) Online Safety-Embedded Critic Learning for Uncertain Systems With Self-Triggered Mechanism

Author(s): Z. Shangguan, B. Yang, Q. Li, W. Xiao, X. Guan

Pages: 4146 - 4160

40) An Evidential Deep Neural Network for Set-Valued Classification and Novelty Detection

Author(s): L. Jiao, X. Xiao, S. Gou, Q. Pan

Pages: 4161 - 4175

41) A Quantum Multilayer Perceptron for Intraoperative Nociception Prediction

Author(s): O. M. T. Abdel Deen, S. -Z. Fan, F. Doctor, J. -S. Shieh

Pages: 4176 - 4191

42) An Enhanced Air Quality Forecasting Method Integrating Feature Mode Decomposition and Multilayer Plasticity Echo State Network

Author(s): X. Xu, J. Liu, L. Hu, X. Miao, Y. Li, S. Liu

Pages: 4192 - 4206

43) A Semisupervised Domain Adaptation Framework Using Dynamic Distribution Alignment and Manifold Regularization

Author(s): M. G. Rahman, M. Z. Islam

Pages: 4207 - 4220

44) LDDER: Learning Distinguishable and Dynamically Enhanced Representation for Visual Reinforcement Learning

Author(s): Y. Yang, H. Xu, J. Fan, H. He, J. Shao

Pages: 4221 - 4233

Friday, June 26, 2026

Weekly Review 26 June 2026

Some interesting links that I Tweeted about in the last week (I also post these on Mastodon, Threads, Newsmast, and Bluesky):

1. AI coding agents can learn how to control robots: https://arstechnica.com/ai/2026/06/ai-coding-agents-can-autonomously-direct-robot-training/
2. Why the majority of AI projects actually fail: https://www.hpcwire.com/bigdatawire/2026/06/15/why-most-agentic-ai-projects-fail-in-production/
3. AI is useful for advertising but it can't do everything: https://www.insidehighered.com/opinion/columns/call-action/2026/06/18/what-ai-cant-do-your-marketing-strategy
4. UK companies are hiring more people who can use AI within existing business functions: https://www.theregister.com/ai-and-ml/2026/06/15/uk-ai-hiring-surges-as-firms-seek-people-to-babysit-the-bots/5255437
5. Despite US government attempts to regulate them, dangerous AI models are going to become widely available anyway: https://arstechnica.com/ai/2026/06/dangerous-ai-models-are-coming-no-matter-what/
6. The greatest advantage universities have in the age of AI is being human: https://www.insidehighered.com/opinion/columns/editors-note/2026/06/18/age-ai-higher-eds-edge-being-human
7. Why HR needs to be involved in setting policies using AI: https://www.techtarget.com/searchhrsoftware/news/366644954/HR-must-have-a-say-in-AI-policy-to-forestall-legal-risks
8. Implementing neuromorphic AI systems using soundwaves: https://spectrum.ieee.org/neuromorphic-computing-acoustic-chips
9. At least one UK police officer has used AI to fake evidence in multiple cases: https://futurism.com/artificial-intelligence/cop-ai-fake-evidence-uk
10. AI still struggles to tell the difference between truth and fiction: https://futurism.com/artificial-intelligence/google-ai-overview-scp-horror-fiction-real
11. AI is accelerating the transition to a gig economy: https://www.theguardian.com/technology/2026/jun/18/ai-threatens-gig-work-rise
12. A framework for integrating AI into teaching without crippling students' ability to think: https://www.insidehighered.com/opinion/career-advice/carpe-careers/2026/06/15/practical-framework-help-students-use-ai-opinion
13. An AI skeptic finds an AI tool from Amazon that doesn't completely suck: https://www.theregister.com/ai-and-ml/2026/06/18/committed-skeptic-finds-himself-warming-to-new-amazon-ai-products-that-actually-dont-suck/5258414
14. KPMG's latest report on AI was found to be full of hallucinations from an AI: https://futurism.com/artificial-intelligence/consulting-firms-ai-report-hallucinations
15. An AI hospital scheduling system caused a patient's death when it didn't send her to intensive care when it should have: https://futurism.com/artificial-intelligence/woman-death-hospital-brazil-ai-icu-beds
16. More legal action is brewing against AI, this time from the use of copyrighted music in training data: https://dataconomy.com/2026/06/16/ai-training-copyrighted-music-taylor-swift-bad-bunny/
17. Now the Pentagon is using AI to write report to the US government: https://arstechnica.com/ai/2026/06/pentagon-boasts-of-using-ai-to-write-reports-mandated-by-congress/
18. Using transfer learning in AI to explore new physics in cosmology: https://dataconomy.com/2026/06/15/ai-transfer-learning-new-physics-discoveries/
19. An AI nose for detecting disease from patients' breath: https://www.theregister.com/ai-and-ml/2026/06/18/ai-nose-uses-smell-language-model-to-sniff-out-signs-of-disease/5258190
20. What universities need to put in place to handle students using AI to cheat: https://www.insidehighered.com/opinion/career-advice/2026/06/17/decision-framework-suspected-ai-misuse-opinion
21. AI are not reliable investment advisors: https://www.stuff.co.nz/money/360994712/heres-how-many-kiwis-are-turning-ai-investing-advice-what-could-go-wrong
22. Some commonly used AI terms explained: https://www.stuff.co.nz/world-news/360988248/whats-your-p-doom-six-increasingly-frightening-bits-ai-jargon-explained
23. Australia needs to put more resources into AI to maintain strategic independence: https://www.theguardian.com/australia-news/2026/jun/15/andrew-hastie-ai-artificial-intelligence-power-cold-war-nuclear-arms-race-comparison-australia
24. Why AI is burning out CIO: https://www.informationweek.com/it-leadership/why-ai-is-burning-out-it-leaders-and-what-cios-say-helps
25. Using AI for plant and fungus conservation: https://www.theguardian.com/environment/2026/jun/16/ai-could-help-win-race-against-extinction-of-vital-plants-say-botanists

Friday, June 19, 2026

Weekly Review 19 June 2026

Some interesting links that I Tweeted about in the last week (I also post these on Mastodon, Threads, Newsmast, and Bluesky):

1. Models should be compensated if their likeness is used by an AI to generate an image: https://www.rnz.co.nz/life/lifestyle/style/nz-fashion-faces-ai-reckoning-after-huffer-allegations
2. The organisations that are using AI to generate their advertising are the kinds of organisations that wouldn't use ad agencies anyway: https://www.rnz.co.nz/news/business/598109/why-everyone-from-your-local-restaurants-to-the-school-fair-is-using-the-same-ads
3. The more personalised an AI becomes, the more likely it is to tell you what you want to hear: https://www.theregister.com/ai-and-ml/2026/06/11/memory-and-personalization-make-ai-more-likely-to-tell-you-what-you-want-to-hear/5253850
4. It appears that Microsoft is finding more and more bugs in its offerings using AI: https://www.theregister.com/patches/2026/06/09/ai-is-making-patch-tuesday-kinda-fun-again/5253225
5. AI isn't the only cause, but is a major contributor to new tertiary students' inability to read: https://futurism.com/future-society/college-students-losing-ability-read
6. Students want AI integrated into their learning, but most institutions aren't doing so: https://www.insidehighered.com/news/student-success/academic-life/2026/06/11/why-students-arent-all-ai-and-what-they-want-colleges
7. A German court has ruled that Google is liable for defamatory statements made by its AI: https://www.computerworld.com/article/4184220/google-is-held-liable-for-false-information-from-its-ai.html
8. Now both sides in a court case have been caught using AI to generate their filings: https://futurism.com/artificial-intelligence/judge-cancels-trial-lawyers-both-sides-ai
9. The extreme scenarios pundits predict for AI are unlikely to occur: https://www.theguardian.com/technology/2026/jun/11/ai-absolutism-apocalyptic-future
10. An open standard for sharing AI: https://www.techtarget.com/searchdatamanagement/news/366644177/Databricks-intros-OpenSharing-a-new-standard-for-sharing-AI
11. Using AI to track glacial melt from satellite images: https://spectrum.ieee.org/tracking-glacier-melting-ai
12. British fraudsters are using AI to doctor insurance claims: https://www.theregister.com/ai-and-ml/2026/06/08/motor-insurance-frausters-abusing-ai-to-exaggerate-claims/5252024
13. AI agents cannot yet fully replicate published experiments: https://www.hpcwire.com/bigdatawire/2026/06/09/can-ai-agents-replicate-science-argonnes-rick-stevens-puts-them-to-the-test/
14. CIOs need to start culling AI projects: https://www.informationweek.com/machine-learning-ai/time-for-an-ai-exit-strategy-how-cios-are-cutting-ai-waste
15. AI data centres are posing a threat to the stability of Australia's power grid: https://www.techrepublic.com/article/news-ai-data-centers-grid-risk-apac-australia/
16. How Lenovo is using AI at the football world cup: https://www.informationweek.com/it-sectors/lenovo-takes-a-shot-at-boosting-its-ai-game-at-the-fifa-world-cup
17. AI toys are outright dangerous for kids, especially preschoolers: https://www.rnz.co.nz/life/wellbeing/chatbot-teddies-for-three-year-olds-why-ai-toys-are-risky-for-kids
18. AI generated code has a lot of security holes in it, but time pressures mean it gets shipped anyway: https://www.theregister.com/devops/2026/06/09/devs-know-ai-code-is-riddled-with-holes-but-ship-it-anyway/5252824
19. The war is Ukraine is making the role of AI in warfare more ethically muddy: https://dataconomy.com/2026/06/10/geoffrey-hinton-ai-warfare-ukraine-drones/
20. Weather forecasting with AI isn't particularly new or original: https://arstechnica.com/science/2026/06/the-weather-and-climate-science-ai-revolution-isnt-revolutionary/
21. Amazon's AI tools are incredibly unpopular and make their workers less productive: https://www.extremetech.com/computing/amazon-workers-hate-their-internal-ai-tools-too
22. Using an AI to write a CV that will probably be screened by another AI seems like a bit of a slippery slope: https://www.theregister.com/ai-and-ml/2026/06/08/department-of-work-and-pensions-answer-to-ai-job-fears-is-a-bot-to-polish-your-cv/5251983
23. Medical staff could be liable if AI makes a mistake: https://www.theguardian.com/society/2026/jun/09/doctors-nhs-could-be-sued-mistakes-ai-tools-medical-protection-society-report
24. Trump's latest executive order on AI doesn't have a lot of substance to it: https://www.computerworld.com/article/4182531/trumps-new-ai-order-hallucinations-arent-just-for-llms.html
25. A hand-cranked AI box. As in, if you want to ask it a question, you have to turn the crank to power it: https://www.theregister.com/offbeat/2026/06/11/hand-cranked-ai-box-lets-you-get-a-workout-while-you-wait-for-answers/5254333
26. If you advertise your AI as being able to detect weapons, it helps if it can actually detect weapons: https://arstechnica.com/tech-policy/2026/06/school-shooting-survivor-sues-ai-gun-detection-firm-after-system-failed-to-spot-weapon/
27. When the US government starts picking which AI companies should be the winners or losers, the AI market is in a dire state: https://www.theregister.com/ai-and-ml/2026/06/09/uncle-sam-considers-buying-a-seat-on-the-titanic/5252598
28. The greatest issue with moving AI data centres into orbit is cooling: https://spectrum.ieee.org/orbital-data-centers-heat
29. Google's newest AI tool has gone full-on creepy: https://www.computerworld.com/article/4182583/ai-creepy-era.html
30. Infrastructure needs for a successful AI rollout: https://dataconomy.com/2026/06/10/ai-ready-infrastructure-the-foundation-for-scalable-ai-workloads/
31. People will always be misidentified by AI facial recognition systems, because the people using the systems are lazy: https://arstechnica.com/tech-policy/2026/06/man-jailed-due-to-faulty-face-recognition-says-florida-cops-ignored-other-evidence/
32. Argentina's president calls for corporations to be run by AI: https://futurism.com/artificial-intelligence/argentina-legalize-non-human-corporations-ai

Thursday, June 18, 2026

IEEE Transactions on Games, Volume 18, Issue 2, June 2026

1) From Play to Pedagogy: A Structured Topic Modeling Analysis of Escape Rooms Research

Author(s): S. López-Pernas, A. Santamaría-Urbieta, A. Gordillo, E. Barra, D. López-Fernández, M. Saqr

Pages: 233 - 245

2) Switch, Reason, and Revise: Enhancing Reasoning Capability of Video Game AI by Large Language Models

Author(s): W. Li, H. Liu, J. Lv, K. Huang, A. Song, Z. Lei

Pages: 246 - 263

3) MobaQA: MOBA Games Prediction Based on Large Language Model Fine-Tuning

Author(s): T. Nie, J. Wang, D. Hou, D. Shen, Y. Kou

Pages: 264 - 274

4) Enhancing ADHD Early Screening With a Mobile Serious Game: A Combined Continuous Screening Paradigm

Author(s): Y. Zhang, D. Cao, H. Hou, M. Hu, J. Li, P. Sun, S. Ni

Pages: 275 - 284

5) Checkmating One, by Using Many: Combining Mixture of Experts With MCTS to Improve in Chess

Author(s): F. Helfenstein, J. Czech, J. Blüml, M. Eisel, K. Kersting

Pages: 285 - 294

6) PQDAST: Depth-Aware Arbitrary Style Transfer for Games via Perceptual Quality-Guided Distillation

Author(s): E. Ioannou, S. Maddock

Pages: 295 - 305

7) Elysian: Building Emotionally Responsive Nonplayable Characters Using Integration of FSM and Generative AI for Real-Time Dialogues in Visual Games

Author(s): R. K. Singh, S. D. Patil

Pages: 306 - 315

8) A Multidimensional Assessment of Embodied Interaction in Large-Scale Full-Body Interactive Environments

Author(s): S. B. Ercan, I. Lorena Alessandrini, L. Guardia Vela, O. Gali Perez, N. Pares

Pages: 316 - 326

9) Symmetric Sudoku-Type Games From Perfect Codes

Author(s): J. An, J. -H. Baek, K. -H. Kim, H. Lim, J. -L. Kim

Pages: 327 - 339

10) Enhanced Policy Update Mechanism for PPO-Inspired Algorithms in Intelligent Agent-Based Games

Author(s): X. Jin, Y. Cao, H. Yu, H. Deng, X. Chen

Pages: 340 - 348

11) Micro-Analysis: Trends in Player Sentiment Toward AI Companions in Modern Games

Author(s): C. Mudlapur, O. P. Singh

Pages: 349 - 358

12) Can a Serious Video Game to Teach Scrum Be More Effective Than Traditional Methods?: A Randomized Controlled Trial

Author(s): D. López-Fernández, J. Mayor, J. Alegre

Pages: 359 - 368

13) Explainable AI for Player Retention: Hyperpersonalized Promotions to Prevent Game User Churn

Author(s): Y. Jung, H. Jang, S. Kim

Pages: 369 - 382

14) Acute Effects of Exergaming Session and Play Mode on Physiological and Psychosocial Responses in Sedentary Young Adults: A Quasi-Experimental Study

Author(s): Y. Xu, R. Zhong, X. Yang

Pages: 383 - 392

15) Emoception: Selective Affective Layer Fine-Tuning of Video Vision Transformers for Player Arousal Change Recognition From Gameplay Footage

Author(s): Y. Xia, I. Khan, M. F. Dewantoro, W. Ouyang, R. Thawonmas

Pages: 393 - 403

16) REGEN: Real-Time Photorealism Enhancement in Games via a Dual-Stage Generative Network Framework

Author(s): S. Pasios, N. Nikolaidis

Pages: 404 - 410

17) Subgame Pruning: Efficiently Solving Two-Player Imperfect Information Games by Accelerated Public Tree Traversal in CFR

Author(s): S. Zhang, P. Yang, Z. Zeng, J. Zhang

Pages: 411 - 417

18) Letter to the Editor: Risk Management in Game Development

Author(s): D. Şengül

Pages: 418 - 421

Friday, June 12, 2026

Weekly Review 12 June 2026

Some interesting links that I Tweeted about in the last week (I also post these on Mastodon, Threads, Newsmast, and Bluesky):

1. Another long-term maths problem solved by AI: https://arstechnica.com/ai/2026/06/openais-math-breakthrough-played-to-ais-strengths/
2. AI security tools are needed to counter AI cracking tools: https://www.techtarget.com/searchitoperations/news/366643790/Cisco-agentic-AI-security-push-faces-enterprise-trust-gap
3. AI now poses a threat to mathematics as a profession: https://arstechnica.com/tech-policy/2026/06/mathematicians-warn-of-ai-threats-to-profession-as-industry-encroaches/
4. There is a one in five chance that AI ends the world: https://www.stuff.co.nz/world-news/360987487/what-your-p-doom-terrifying-metric-used-ai-experts
5. AI data centres are being built faster than the workforce to run them is being trained: https://www.hpcwire.com/bigdatawire/2026/06/01/data-centers-are-scaling-fast-the-workforce-isnt-ai-has-to-close-the-gap/
6. AI saves workers time, but it doesn't make them more productive: https://www.computerworld.com/article/4181083/ai-saves-workers-a-day-a-week-but-they-dont-know-what-to-do-with-it-2.html
7. An AI worm that can exploit systems without human involvement: https://dataconomy.com/2026/06/04/ai-worm-exploits-systems/
8. Backlash against the developer of rsync after it emerged he used AI to generate some of the code in recent versions: https://www.theregister.com/ai-and-ml/2026/06/04/please-do-not-vibe-f-up-this-software-broken-backups-spark-ai-coding-row-in-rsync-project/5251189
9. The California town that banned AI data centres: https://www.theguardian.com/us-news/2026/jun/03/california-monterey-park-datacenters-ban
10. Professors resort to failing students who use AI in their assignments: https://futurism.com/future-society/professor-fail-any-student-uses-ai
11. Canada invests in AI to reduce its reliance on US technology: https://www.theregister.com/ai-and-ml/2026/06/04/canada-wants-its-own-ai-less-reliance-on-us-tech/5251404
12. How to tell when an AI project should be terminated: https://www.informationweek.com/it-leadership/ask-the-experts-the-red-flags-that-signal-an-ai-project-isn-t-worth-pursuing
13. Can AI weapons be given morality? https: https://www.theguardian.com/world/2026/jun/03/can-autonomous-ai-powered-killer-drones-take-morality-onboard
14. Kids are using AI so much that they can't do even basic maths: https://futurism.com/future-society/professors-incoming-students-dont-understand-math
15. Another lawsuit after a mentally ill person commits murder after chatting with AI: https://arstechnica.com/tech-policy/2026/06/florida-sues-openai-sam-altman-after-multiple-chatgpt-linked-murders/
16. Five academic papers that explain Large Language Model AI: https://www.kdnuggets.com/5-fun-papers-that-explain-llms-clearly
17. The rise of remote work has reduced job prospects for the young, not AI: https://www.theregister.com/cxo/2026/06/02/remote-work-not-ai-is-killing-job-prospects-for-the-youth/5250241
18. AI combined with synthetic DNA sequences could make it easier to acquire bioweapons: https://www.theregister.com/ai-and-ml/2026/06/04/ai-heavyweights-warn-their-tech-could-erode-barriers-to-bioweapons/5251340
19. We need to slow down before we get to the stage that AI can build AI: https://www.stuff.co.nz/world-news/360988348/anthropic-warns-ai-could-soon-build-itself-calls-slowdown
20. We need regulations around AI toys for kids: https://www.techrepublic.com/article/news-ai-toys-privacy-risks/
21. Backlash against Martin Scorsese for using AI to generate storyboards: https://www.theguardian.com/film/2026/jun/03/martin-scorsese-accused-of-throwing-artists-under-bus-with-ai-storyboards
22. AI is not very good at giving DIY advice: https://www.theguardian.com/technology/commentisfree/2026/jun/05/ai-artificial-intelligence-help-with-diy-valuable-lessons
23. The problem with using AI generated images in product searches is customers can't be certain that the products really exist: https://dataconomy.com/2026/06/04/amazon-ai-generated-product-images/
24. Energy and water are both being guzzled by AI, and it's affecting the environment: https://www.rnz.co.nz/news/science-and-technology/597181/the-real-world-cost-of-ai

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