Some say I’m too rational, no, too realistic, when I say: one day I will die; not
at this particular moment of writing this ‘not,’ so: no need for dismay, not to fray
From there, our shared fabric, I reverse imagineered as trompe l’œil: always in our shared compound minds
of living life to the fullest here and now back to this exact mindful moment: back to this instant sensation, actually,
of living with you with care, with kindness: with simple daily work we can do; together.
as I had my synthetic constructs output, choreographically, to visceral and venerable visitors: at the wooden gate of our city state
today we live, today we think, today we do:
—animasuri’24
Bridges A. D., Chittka L. (2023) Escaping anthropocentrism in the study of non-human culture: Comment on “Blind alleys and fruitful pathways in the comparative study of cultural cognition” by Andrew Whiten. Physics of Life Reviews 44, 267-269 DOI: https://doi.org/10.1016/j.plrev.2023.01.008
Bridges A. D., MaBouDi H., Procenko O., Lockwood C., Mohammed Y., Kowalewska A., Romero-Gonzalez E., Woodgate J. L. & Chittka L. (2023) Bumblebees acquire alternative puzzlebox solutions via social learning. PLoS Biology21(3): e3002019 DOI: https://doi.org/10.1371/journal.pbio.3002019
Annabelle lives in a place where bookshelves are censored wooden, plastic, woven reed these controlling tangibles are controlled and outlawed here
Andrew on the other hand lives where colophons are; you know, these things with title, names , year of print or anything to identify source cut out, filtered out, out dated these are
Alisha lives in a place where paper is contraband surely papyrus, parchment, leather-bound or anything scraped for scraps with ink blobs, ink odor, or ink smear are controlled substances
Ali on the other hand lives where the word ‘literature’ gets uttering people band and ‘bande dessinée’ is a withering underground silent-musical theater group
All live in a world where inference is an only source connecting the dots where others had not trigger-happy mines of bitter patterns secret assets as test data groups driven by Moore’s Law and redacted data
Kummer, M., Stephan, F. (1996). On the Structure of Degrees of Inferability. IN: Journal of Computer and System Sciences 52, no. 2. April 1, 1996: 214–38. https://doi.org/10.1006/jcss.1996.0018
Lavigne, S. (2023). Scrapism: A Manifesto. Online: Critical AI. Volume 1, Issue 1-2, October 1, 2023. Rutgers University/ Duke University Press. https://doi.org/10.1215/2834703X-10734046
Wachter, S., Mittelstadt, B. (2018, Oct. 12). A Right to Reasonable Inferences: Re-Thinking Data Protection Law in the Age of Big Data and AI. Online: Open LawArXiv Repository. https://doi.org/10.31228/osf.io/mu2kf
Automated summaries, summon trust, brazenly bridging voids of knowing and relevance.
Not penned are the words, therefore thou dost trust; not perused the manuscript, therefore ye trust.
Consequential trust, as thy rigid law of physics, a gravitational pull to machined rule, a law of efficient attraction, it demands what ye shall not know.
Not having experienced the theme, therefore thou dost trust; not lived its corpus, therefore ye trust.
Revision of relevance to the unread, awaken, succumbing to insights undead, machined authority from a life unlived, and cleverness uncorporated.
Thou knowest not the author, the thought, the action, the clockmaker, the bricklayer, nor thy need, serendipitously found.
Therefore, thou shalt come to co-live a circular gist, lacking lived experience’s necessity, or intentionality of the read.
—animasuri’24
— triggers
Dreyfus, H. L. (1992). What Computers Still Can’t Do. A Critique of Artificial Reason. Boston, MA: MIT Press
Searle J.R. (1980). Minds, Brains, and Programs. IN: Behavioral and Brain Sciences. 1980;3(3):417-424. doi:10.1017/S0140525X00005756
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Labba, C., Alcouffe, A., Crubézy, E., & Boyer, A. (2023). IArch: An AI Tool for Digging Deeper into Archaeological Data. IN: 2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI), 22-29. https://doi.org/10.1109/ICTAI59109.2023.00012.
Merzlyak, A., & Lee, S. (2006). Phage as templates for hybrid materials and mediators for nanomaterial synthesis. IN: Current opinion in chemical biology, 10 3, 246-52 . https://doi.org/10.1016/J.CBPA.2006.04.008.
Meyer, V., Basenko, E., Benz, P., Braus, G., Caddick, M., Csukai, M., Vries, R., Frisvad, J., Gunde-Cimerman, N., Haarmann, T., Johnson, R., Keller, N., Mortensen, U., Perez, R., Ram, A., Ross, P., Shapaval, V., Steiniger, C., Brink, H., Munster, J., & Wösten, H. (2020). Growing a circular economy with fungal biotechnology: a white paper. IN: Fungal Biology and Biotechnology, 7. https://doi.org/10.1186/s40694-020-00095-z.
Safdari, M., Serapio-Garc’ia, G., Crepy, C., Fitz, S., Romero, P., Sun, L., Abdulhai, M., Faust, A., & Matari’c, M. (2023). Personality Traits in Large Language Models. Online: ArXiv, abs/2307.00184. https://doi.org/10.48550/arXiv.2307.00184.
Smith, A., & Helenius, A. (2004). How Viruses Enter Animal Cells. IN: Science, 304, 237 – 242. https://doi.org/10.1126/SCIENCE.1094823.
Tortella, G., Diez, M., & Durán, N. (2005). Fungal Diversity and Use in Decomposition of Environmental Pollutants. IN: Critical Reviews Microbiology, 31, 197 – 212. https://doi.org/10.1080/10408410500304066.
Varanda, C., Félix, M., Campos, M., & Materatski, P. (2021). An Overview of the Application of Viruses to Biotechnology. Viruses, 13. https://doi.org/10.3390/v13102073.
Warinner, C., Herbig, A., Mann, A., Fellows Yates, J. A., Weiß, C. L., Burbano, H. A., Orlando, L., & Krause, J. (2017). A Robust Framework for Microbial Archaeology. IN: Annual review of genomics and human genetics, 18, 321–356. https://doi.org/10.1146/annurev-genom-091416-035526
Wen, A., & Steinmetz, N. (2016). Design of virus-based nanomaterials for medicine, biotechnology, and energy. IN: Chemical Society reviews, 45 15, 4074-126 . https://doi.org/10.1039/c5cs00287g.
Iapaolo F. (2023). The system of autono‑mobility: computer vision and urban complexity-reflections on artificial intelligence at urban scale. AI & society, 38(3), 1111–1122. https://doi.org/10.1007/s00146-022-01590-0
Xie, H., & Xiao, P. (2022). Cooperative Adaptive Cruise Algorithm Based on Trajectory Prediction for Driverless Buses. Machines. https://doi.org/10.3390/machines10100893.
Lu, Y. (2023 Nov 20). ‘Lost Time for No Reason’: How Driverless Taxis Are Stressing Cities In San Francisco and Austin, Texas, where passengers can hail self-driving vehicles, the cars have added to the workloads of city employees. Online: The New York Times https://www.nytimes.com/2023/11/20/technology/driverless-taxis-cars-cities.html
Real word Actual word: think of one. Tangible word
Intangible word Ephemeral word: don’t think of one. Solid word
Concrete word Fake word: think of one. True word
Right word Wrong word: don’t think of one. Good word
Bad word Strong word: think of one. word!
how do these differ if non exist, yet each can hurt ‘n’ flirt
it’s fact it’s so unless
if output is adjectivally cleaned then < ignore: output >
if output is silence and silence is performance then output
—animasuri’24
—-•
triggers
Benasayag, M., Rendall, S. (2021). Tyranny of Algorithms: Freedom, Democracy, and the Challenge of AI. New York, USA: Europa Editions.
Chase, S. (1933, 1966). The Tyranny of Words. London, UK: A Harvest/ HBJ Book. https://archive.org/search?query=the+tyranny+of+words
Feffer, M., Heidari, H., Lipton, Z. C.(2023, May 26). Moral Machine or Tyranny of the Majority? Online: arXiv https://doi.org/10.48550/arXiv.2305.17319.
Gaus, G. (2016). The Tyranny of the Ideal: Justice in a Diverse Society. Princeton, New Jersey, USA: Princeton University Press.
Glukhov, D., Shumailov, I., Gal, Y., Papernot, N., Papyan, V. (2023, July 20). LLM Censorship: A Machine Learning Challenge or a Computer Security Problem? https://doi.org/10.48550/arXiv.2307.10719 AND https://www.cl.cam.ac.uk/~is410/Papers/llm_censorship.pdf
Li, L., Sha, L., Li,Y., Raković, M., Jia R., Joksimovic, S., Selwyn, N., Gašević, D., Chen, G. (2023). Moral Machines or Tyranny of the Majority? A Systematic Review on Predictive Bias in Education. In LAK23: 13th International Learning Analytics and Knowledge Conference (LAK2023). Association for Computing Machinery, New York, NY, USA, 499–508. https://doi.org/10.1145/3576050.3576119
Shapley, S. (2023). SemanticGPT. GPT's mind using Logit Bias. https://github.com/samshapley/SemanticGPT
Belabbes, M. A., Ruthven, I., Moshfeghi, Y., & Pennington, D. R. (2022). Information overload: A concept analysis. IN: Journal of Documentation, 79(1), 144–159. https://doi.org/10.1108/jd-06-2021-0118
Benselin, J. C., & Ragsdell, G. (2016). Information overload: The differences that age makes. IN: Journal of Librarianship and Information Science, 48(3), 284–297. https://doi.org/10.1177/0961000614566341
Daniel Manzoni de Almeida, Paula Seixas Mello, Silvia Luzia Frateschi Trivelato, Patricia Marzin-Janvier, Jean Rodrigues Siqueira, & Marsilvio Gonçalves Pereira. (2019). A case study in the teaching of immunology: written arguments and the counter-inductive method of Paul Feyerabend. Revista Brasileira de Ensino de Ciência e Tecnologia. https://periodicos.utfpr.edu.br/rbect/article/view/6691
Darnell, J.A., Gopalkrishnan, S. (2023). Digital Information Overload: How Leaders Can Strategically Use AI to Prevent Innovation Paralysis. IN: Pfeffermann, N., Schaller, M. (eds) New Leadership Communication—Inspire Your Horizon. Springer, Cham. https://doi.org/10.1007/978-3-031-34314-8_14
Ferguson, A. N, Franklin, M., & Lagnado, D. (2022). Explanations that backfire: Explainable artificial intelligence can cause information overload. Proceedings of the Annual Meeting of the Cognitive Science Society, 44. Retrieved from https://escholarship.org/uc/item/3d97g0n3
Siegel, M. G., Rossi, M. J., & Lubowitz, J. H. (2024). Editorial: Artificial Intelligence and Machine Learning May Resolve Health Care Information Overload. Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association, S0749-8063(24)00012-4. Advance online publication. https://doi.org/10.1016/j.arthro.2024.01.007
there are five colors. yellow, orange, green, blue and red.
I need all, all possible combinations starting off with the set of two,
followed by the set of three, then four combinations and ending with the set of five.
the order of the colors is important. that means, a set of ‘yellow | orange’ is different from a set of ‘orange | yellow’.
all possible combinations should be listed. also provide sets of multiples of the same color. so, for instance: ‘orange | orange.’
do not skip any combination since I need to copy paste all into a different document.
so all should be listed and all written out in long-form. do not abbreviate, do not cut corners
the format should remain persistent across all sets. that is, for instance: ‘a color | a color | a color’
the devider within one set is always ‘|’ while the devider between sets is always ‘,’.
execute. create, copy, reorder: become colorful.
—animasuri’24
—-• triggers
Baertschi, B. (2014). Human Dignity as a Component of a Long-Lasting and Widespread Conceptual Construct. Journal of Bioethical Inquiry, 11(2), 201–211. https://doi.org/10.1007/s11673-014-9512-9
Copeland, S. (2017). On serendipity in science: Discovery at the intersection of chance and wisdom. Synthese, 196(6), 2385–2406. https://doi.org/10.1007/s11229-017-1544-3
Kefalidou, G., & Sharples, S. (2016). Encouraging serendipity in research: Designing technologies to support connection-making. International Journal of Human-Computer Studies, 89, 1–23. https://doi.org/10.1016/j.ijhcs.2016.01.003
Liang, T. (2023). Unveiling the Ecological and Naturalistic Views in Zhuangzi’s Daoism: Exploring the Concept of “The Usefulness of Uselessness.” IN: Proceedings of the 2023 5th International Conference on Literature, Art and Human Development (ICLAHD 2023) (pp. 346–352). https://doi.org/10.2991/978-2-38476-170-8_38
Nishikawa-Pacher, A. (2022). Measuring serendipity with altmetrics and randomness. Journal of Librarianship and Information Science, 55(4), 1078–1087. https://doi.org/10.1177/09610006221124338
Ramsey, R. E. (2012). On the Dire Necessity of the Useless: Philosophical and Rhetorical Thoughts on Hermeneutics and Education in the Humanities. IN: Fairfield 2012: 91- 106. (Chapter 6). Thank you Dr. WSA.
Shumailov, I., Shumaylov, Z., Zhao, Y., Gal, Y., Papernot, N., Anderson, R. (2023, May 31). The Curse of Recursion: Training on Generated Data Makes Models Forget. https://doi.org/10.48550/arXiv.2305.17493.
Treusch, P., Berger, A., & Rosner, D. K. (2020). Useful Uselessness? Proceedings of the 2020 ACM Designing Interactive Systems Conference, 193–203. https://doi.org/10.1145/3357236.3395582
von Hippel, E. A., & von Krogh, G. (2013). Identifying Viable ‘Need-Solution Pairs’: Problem Solving Without Problem Formulation. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.2355735
Willems, L., Wade, E., Herbert, R., & Plume, A. (2022). Tales of the Unexpected: Designing for Serendipity in Research [ICSR Perspectives]. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4048549
To some human life experienced —as an accumulation of rejection with access just around the corner— is right over that next hill
Have you forgotten, dear?
now can not be measured it is being surrendered to the next without anticipation of past nor coming a raw material fondling patine from usage
Have you, dear?
value radiates outward it is never for the taking trapped in vaults by fund handlers handling your fun
Have dear?
unicorns, gray rhinos, black swans 30 below 30, vested interests and hip nuns staring straight, stiff upper lip prancing cameras, shoulders with a chip
Dear?
Have some tea without tea it soothes
it flows it grounds .
—animasuri’24
—-• triggers
Buhmann, A., & Fieseler, C. (2023). Deep Learning Meets Deep Democracy: Deliberative Governance and Responsible Innovation in Artificial Intelligence. Business Ethics Quarterly, 33(1), 146–179. doi:10.1017/beq.2021.42
Celik, Ismail. (2023, Sep 1). Exploring the Determinants of Artificial Intelligence (AI) Literacy: Digital Divide, Computational Thinking, Cognitive Absorption. IN: Telematics and Informatics 83 102026. https://doi.org/10.1016/j.tele.2023.102026.
Güngör, H. (2020). Creating Value with Artificial Intelligence: A Multi-stakeholder Perspective. Journal of Creating Value, 6(1), 72-85. https://doi.org/10.1177/2394964320921071
Krive, J., Isola, M., Chang, L., Patel, T., Anderson, M., & Sreedhar, R. (2023). Grounded in reality: artificial intelligence in medical education. JAMIA open, 6(2), ooad037. https://doi.org/10.1093/jamiaopen/ooad037
Sætra, H. S. (2020). A Shallow Defence of a Technocracy of Artificial Intelligence: Examining the Political Harms of Algorithmic Governance in the Domain of Government. IN: Technology in Society 62 (August 1, 2020): 101283. https://doi.org/10.1016/j.techsoc.2020.101283.
Zucker, J.-D. (2003). A Grounded Theory of Abstraction in Artificial Intelligence. Philosophical Transactions: Biological Sciences, 358(1435), 1293–1309. http://www.jstor.org/stable/3558222
