Oops, found the roundtable discussion appendix and missed Wendy Brown's actual Tanner lecture:
Politics and Knowledge in Nihilistic Times: Thinking with Max Weber - https://www.youtube.com/watch?v=nG52tEGghTA - “Politics” https://www.youtube.com/watch?v=qXm_0DxoS_k - “Knowledge” -- rec -- On Sun, Oct 8, 2023 at 1:27 PM Roger Critchlow <r...@elf.org> wrote: > The book sounds intriguing, but it's not in my lending library. > > Happily, there are lots of Tanner Lecture videos available online: > https://www.youtube.com/watch?v=yI-MCqeCILs Wendy Brown from 2019 > https://www.youtube.com/watch?v=NJprCvmrpoY Kim Stanley Robinson from > March 2023 > > -- rec -- > > > -- rec -- > > On Sun, Oct 8, 2023 at 11:56 AM David Eric Smith <desm...@santafe.edu> > wrote: > >> It’s a good point/counterpinet, Pieter. >> >> I don’t want to stand against using new tools to relieve a scarcity >> constraint, and surely education has been a severe one. >> >> I have what appears to be an enormous suspicion of a bait and switch, in >> which suddenly we find ourselves in a world where simultaneously: >> >> 1. Sal Khan and Daphne Koller own everything, and nobody else owns >> anything; and >> >> 2. People have no skills (say I, as I use the scary-good google translate >> to take enormous pressure, though less shame, off me for not learning a >> language I should have learned by now). >> >> Or, as a popular bumper sticker in Santa Fe used to say post-2016: Where >> are we going? And what am I doing in this handbasket? >> >> I should mention, on this point, that part of my cast of mind was shaped >> by an article I read some time ago in some education chronicle, about how >> the command-and-control interface to the computer was taking up more and >> more space in classrooms, and kids were starting to show severe systematic >> deficits in particular areas. They could command anything they wanted into >> existence on the computer, and failed to learn that the rest of the world >> of people doesn’t work that way. Negotiating skills were mentioned in the >> article. My description of a dystopian non-education was meant to suggest >> that for several students to have to hear exactly the same thing would >> require them to come to terms with the fact that it will fit them >> differently, and they should become used to handling that too. >> >> It is interesting that I could never use a chatbot as a first stage of >> writing something, as the optimistic chatbots suggest everybody will do, >> and which I can believe for some people will be a good fit. For me, I >> can’t even take looking at a page of my own writing when I am in a tangle, >> as a start to getting out of it. All that pre-formed text is in the way of >> whatever part of my brain tries to bring into focus what I should do next. >> I know that chatbots and writing is not your point about education, and >> don’t mean to derail those points; the chatbots-and-journalism theme was >> one of the things from the original thread that put me onto the education >> sidetrack. What (at least in my imagination) they have in common is that >> there are certain mental operations that I only do when I have “space”, and >> many of these tools seem designed to make sure nobody ever has to leave any >> “space” unfilled by some external stimulus, ever again. I worry about it >> as a development-weakening prosthetic, though I understand that the >> argument for that would need to be made case by case, versus the likely >> (and I believe you, in many cases demonstrated) economies and advantages of >> personalization. >> >> Fortunately, I am neither designing anything nor voting on anything just >> now, so there is no danger I will hold anybody else back who is trying to >> make something work. >> >> Eric >> >> >> On Oct 8, 2023, at 7:45 AM, Pieter Steenekamp <piet...@randcontrols.co.za> >> wrote: >> >> I'd like to reflect how LLM's and AI could disrupt education. >> >> My paradigm is not to think in terms of the current educational model, >> but to throw out all preconceived ideas and to design it from scratch. >> There are obviously zillions of ways to do it and a good model will need to >> evolve, but the following are merely two examples to trigger new and novel >> approaches, one from Sal Khan and one from my own experience. >> >> 1 Sal Khan's approach to use AI to personalize education is based on the >> idea that every student can benefit from a customized learning path that >> adapts to their needs and preferences. He argues that AI can help scale the >> benefits of one-to-one tutoring, which has been shown to improve students' >> performance significantly. He also believes that AI can enhance the role of >> teachers by providing them with useful feedback, insights, and assistance. >> He envisions a future where every student has access to an AI-powered >> personal tutor and every teacher has an AI teaching assistant. >> >> Sal Khan is the founder and CEO of Khan Academy, a nonprofit education >> platform that offers free online courses, videos, and exercises for >> learners of all ages. He has been a pioneer in using technology to >> democratize education and make it accessible to anyone, anywhere. He has >> also been exploring the potential of AI to transform education for the >> better. In his 2023 TED talk¹, he demonstrated Khanmigo, an AI-powered >> guide that can help students with various subjects, skills, and tasks. >> Khanmigo can detect students' mistakes and misconceptions, provide >> effective feedback and explanations, encourage Socratic dialogue and >> debate, and assist with writing and storytelling. Khanmigo also acts as a >> teaching assistant for teachers, helping them with lesson planning, >> grading, and progress reports. >> >> Sal Khan's approach to use AI to personalize education is based on his >> vision of creating a more humanistic and learner-centered education system. >> He believes that AI can empower students to learn at their own pace, >> explore their interests, and develop their creativity. He also believes >> that AI can support teachers to focus more on the social and emotional >> aspects of teaching, such as building relationships, fostering curiosity, >> and inspiring passion. He hopes that by using AI to personalize education, >> we can create a more equitable and inclusive learning environment for >> everyone.. >> >> Source: Conversation with Bing, 2023/10/08 >> (1) . https://bing.com/search?q=Sal+Khan+AI+education. >> (2) Sal Khan’s 2023 TED Talk: AI in the classroom can transform >> education. >> https://blog.khanacademy.org/sal-khans-2023-ted-talk-ai-in-the-classroom-can-transform-education/ >> . >> (3) Sal Khan: How AI could save (not destroy) education | TED Talk. >> https://www.ted.com/talks/sal_khan_how_ai_could_save_not_destroy_education/c >> . >> (4) The Future Of AI And Education: Insights From Sal Khan. >> https://www.openbusinesscouncil.org/the-future-of-ai-and-education-insights-from-sal-khan-in-conversation-with-bill-gates >> <https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fwww.openbusinesscouncil.org%2fthe-future-of-ai-and-education-insights-from-sal-khan-in-conversation-with-bill-gates&c=E,1,2zh-o7p-ZRG5J2pDpv8lLYBDKVFUgyvlCSvOCnrGzy0OEqHE_M-1ND6g52xVjiUgyBncevhmKdnOnnuuTkeZ66oyJXl1nY6Pan2Zr01pkGQWF2U,&typo=1> >> . >> (5) undefined. >> https://www.ted.com/podcasts/rethinking-with-adam-grant/khan-academy-founder-sal-khan-on-ai-and-the-future-of-education-transcript >> . >> (6) undefined. >> https://podcasts.apple.com/us/podcast/how-ai-could-save-not-destroy-education-sal-khan/id160904630?i=1000611325934 >> . >> (7) undefined. https://www.ted.com/contact%29. >> (8) en.wikipedia.org. https://en.wikipedia.org/wiki/Sal_Khan. >> >> 2 In South Africa, we are currently facing a significant education >> crisis. While there are some excellent private schools, they come with a >> high price tag. On the other hand, the state of public schools is a >> complete disaster. >> >> During the COVID-19 lockdowns, I had the opportunity to work with >> children ranging from 6 to 16 years old, and I decided to adopt a radically >> different educational approach. This approach was inspired by Sugata >> Mittra's belief that teachers may not be necessary if the learning >> environment is well-managed (as elaborated below). >> >> As part of our informal schooling setup, we incorporated a daily "speech" >> session at 11 am. This session was not limited to just speaking; the >> children were also required to submit handwritten copies of their speeches >> and present them to the group. Following each child's presentation, we >> engaged in a Q&A and discussion session. >> >> Even though we didn't have access to ChatGPT at that time, if I were to >> recreate this experience today, I would encourage the children to utilize >> resources like ChatGPT and other freely available AI tools on the internet. >> This approach aligns with preparing them for the demands of today's >> workplace. >> >> Children possess an innate desire to learn, seek challenges, and take >> pride in their accomplishments. Providing them with maximum freedom within >> defined boundaries is an excellent approach to help them flourish. >> >> Reference, info on Sugata Mitra from the internet >> The School in the Cloud is a concept developed by Sugata Mitra, an >> educational researcher and TED Prize winner. He proposes that children can >> learn anything by themselves, with the help of the Internet and their >> peers, without the need for formal teaching or supervision. He calls this >> method Self-Organized Learning Environments (SOLE)¹. >> >> Mitra conducted several experiments to test his idea, such as the "Hole >> in the Wall" project, where he installed computers in slums and villages in >> India and observed how children learned to use them without any guidance¹. >> He also created learning labs in different locations, where children could >> access online resources and mentors, called the "Granny Cloud", who >> supported their curiosity and exploration². >> >> Mitra's vision is to transform the way children learn, by giving them >> more autonomy, creativity and collaboration. He believes that this approach >> can prepare them for the future, where memorization of facts is less >> important than critical thinking and problem-solving. He also invites >> anyone, anywhere, to join his global experiment in self-organized learning, >> by creating their own SOLEs and sharing their discoveries². >> >> The School in the Cloud is also the subject of a documentary by Jerry >> Rothwell, which follows Mitra's three-year experiment and the impact of his >> work on children and educators around the world³. You can also read more >> about Mitra's ideas and experiences in his book "The School in the Cloud: >> The Emerging Future of Learning"⁴.. >> >> Source: Conversation with Bing, 2023/10/08 >> (1) Sugata Mitra: Build a School in the Cloud | TED Talk. >> https://www.ted.com/talks/sugata_mitra_build_a_school_in_the_cloud. >> (2) Sugata Mitra creates a School in the Cloud | Prize-winning wishes | >> TED .... >> https://www.ted.com/participate/ted-prize/prize-winning-wishes/school-in-the-cloud >> . >> (3) The School in the Cloud - United Nations Western Europe. >> https://unric.org/en/the-school-in-the-cloud/ >> <https://linkprotect.cudasvc.com/url?a=https%3a%2f%2funric.org%2fen%2fthe-school-in-the-cloud%2f&c=E,1,P04gf7AkTCBw5Pu_pIZ15Sa4DD1-gfP_8k-B2baFWOI2jWFHYyPbbaBsn0OsnINICl6TI9QThLvR2A5qOglBMS7zz_Tmtt90LZBHRFp-&typo=1> >> . >> (4) The School in the Cloud by Sugata Mitra (ebook) - eBooks.com >> <https://linkprotect.cudasvc.com/url?a=https%3a%2f%2feBooks.com&c=E,1,wsixh_9R4QKLkD8DtVqVcLh8kGp_7BfjsaQ5St9_onGfLCa4Ou6JZjv0T2UFtSbIYPqSp0o5p5t2ZJssBHfXMnLUgHb4gPP2_oEKNle93g,,&typo=1&ancr_add=1> >> https://www.ebooks.com/en-us/book/209765777/the-school-in-the-cloud/sugata-mitra/ >> <https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fwww.ebooks.com%2fen-us%2fbook%2f209765777%2fthe-school-in-the-cloud%2fsugata-mitra%2f&c=E,1,ALPLtj1Pd8Kx3SVvle5l5lE2km7dGj6PWIWblhALEROHD-5OllWa3vIAV_dpaEw1Tt9GJyLnLfyIb5iufGiV8vo3uAWeoE-zwANhJFQ5BQ,,&typo=1> >> . >> (5) undefined. https://www.ted.com/contact%29. >> (6) en.wikipedia.org. https://en.wikipedia.org/wiki/Sugata_Mitra. >> >> On Sun, 8 Oct 2023 at 11:20, David Eric Smith <desm...@santafe.edu> >> wrote: >> >>> In reading about the role of LLMs in personalization, I just realized >>> how to further destroy education. As in many of these things, one starts >>> with an insight that is basically good, and then hands it to a SV company >>> to be turned into something profoundly nihilistic. >>> >>> The lecturer sits at “the front” of wherever this happens. The body of >>> students sit in something that makes them manifestly a group. But what the >>> lecturer says isn’t what they hear. The lecturer speaks into a computer, >>> and the students all wear headsets (probably full VR immersions). An >>> intervening LLM, which has been trained on exchanges with each student and >>> with the lecturer, replaces whatever the lecturer says with a >>> “personalized” version of the “content” which is then fed to each student. >>> >>> No two people will have heard quite the same version of anything. I >>> guess, if they ever wanted to discuss the material with each other, another >>> LLM could be recruited to stand between them to convert what either of them >>> said into a different stream for the other to hear. That can be an >>> additional service for being “in the class”, which one can purchase for a >>> fee, like the fee to get on an airplane earlier in the line than some other >>> passenger who paid a lower fee. >>> >>> The only thing I find weird is that I haven’t already head this >>> suggested 1000 times even in the popular press. It seems like the first >>> idea that would occur to any SV engineer, or (though probably requiring a >>> cognitive exoskeleton) any university administrator. >>> >>> Eric >>> >>> Oh yeah, p.s.: The insight that wasn’t evil is that this is the >>> difference between lectures and books or other broadcast media. In a real >>> lecture, in the old world where people spent time with each other, the >>> teacher gets to know the students enough to learn what they can use, and >>> renders the material with empathy for that. I’ll leave the reader to put >>> together which parts of the resulting exchange get left out of my LLM >>> implementation. >>> >>> p.p.s. I should mention, has any of you read this book? >>> [image: 9780674279384-lg.jpg] >>> >>> Nihilistic Times — Wendy Brown >>> <https://www.hup.harvard.edu/catalog.php?isbn=9780674279384> >>> hup.harvard.edu >>> <https://www.hup.harvard.edu/catalog.php?isbn=9780674279384> >>> <https://www.hup.harvard.edu/catalog.php?isbn=9780674279384> >>> >>> I got to spend a little time in the orbit of this woman last year >>> (didn’t really “meet”, since I was just a quiet sitter-in in a group’s >>> weekly discussion), and she seems to me like just a fine mind. The book is >>> a chautauqua of sorts, not aspiring to a destination per se. But it is a >>> good combination of empathy, analytic clarity, and erudition, nicely >>> combined. Bears on how many things make up the machinery of nihilism, >>> extending well beyond relations I recognized as part of an integration, >>> though mentioning many things I rail against in daily life. >>> >>> >>> >>> >>> On Oct 7, 2023, at 8:36 PM, Steve Smith <sasm...@swcp.com> wrote: >>> >>> Tom - >>> >>> This is probably a little less relevant to the business of journalism >>> than you deserve but this is a pretty good (IMO) fleshing out of some of >>> the technical details of (L)LMs which might fill in some blanks: >>> >>> https://developers.google.com/machine-learning/resources/intro-llms >>> >>> There must be (by now) some (yet) more relevant resources for >>> Journalists (for example), not only to de-Jargonize a little but also to >>> make it (yet more) relevant to your domain. >>> >>> Here, straight from the *Horses' Mouth* (GPT 3.5) itself ( I leave it >>> to you to tell us how well these answers work for you?). It is probably >>> worth engaging with chatGPT yourself and asking more and more focused >>> questions... a good self-study in "prompt engineering"! >>> >>> http://chat.openai.com >>> <https://linkprotect.cudasvc.com/url?a=http%3a%2f%2fchat.openai.com&c=E,1,5AQR_YXXM2e5NRiZ2jwiMxV8_p-R8Bm41a-VJIvezvBxlpk5Dl9j1kvUr04X8zxM96dWITUcudcORIY8fwPup8paM-YALfjNmU7xfsuVh_3ViFZl3ak,&typo=1> >>> >>> *** >>> >>> *Introduction to Modern Language Models for Veteran Journalists* >>> >>> *In today's digital age, the field of journalism is undergoing a >>> significant transformation, largely driven by advancements in technology. >>> One key innovation that has had a profound impact on the industry is the >>> development of modern language models, often abbreviated as LLMs. While you >>> may not be a tech expert, understanding the basics of LLMs can be >>> invaluable for journalists. So, let's break it down in simple terms.* >>> >>> ***What Are Language Models?*** >>> >>> *At its core, a language model is like a super-smart digital writer. >>> It's a computer program trained to understand and generate human language. >>> Think of it as a tool that helps computers understand and use words, >>> sentences, and paragraphs just like humans do.* >>> >>> ***The Power of Large Language Models (LLMs)*** >>> >>> *Now, let's talk about Large Language Models (LLMs). These are the big >>> players in the world of language models. They're like language >>> supercomputers because they're trained on massive amounts of text from the >>> internet. This means they've learned a lot about how people write and talk.* >>> >>> ***How LLMs Help Journalists*** >>> >>> *1. **Content Generation**: LLMs can generate written content, from news >>> articles to summaries and even creative pieces. Journalists can use them to >>> draft stories faster and get ideas flowing.* >>> >>> *2. **Fact-Checking**: They're handy for fact-checking, helping you >>> quickly verify information by scanning a vast database of knowledge.* >>> >>> *3. **Summarization**: LLMs can take long, complex documents and create >>> concise summaries, saving you time on research.* >>> >>> *4. **Translation**: They can also translate text between languages, >>> which can be incredibly useful for international reporting.* >>> >>> *5. **Personalization**: Some news websites use LLMs to tailor content >>> to individual readers, providing a more personalized news experience.* >>> >>> *6. **Social Media Analysis**: LLMs can sift through social media data, >>> helping journalists understand public sentiment and trends.* >>> >>> ***Potential Concerns*** >>> >>> *While LLMs are incredibly powerful, there are some concerns to keep in >>> mind. They might unintentionally spread misinformation if not used >>> carefully, and they can't replace human judgment or critical thinking.* >>> >>> ***Conclusion*** >>> >>> *In a nutshell, modern language models (LLMs) are like digital writing >>> assistants that can help journalists write better, research faster, and >>> adapt to the changing landscape of digital journalism. While they're >>> powerful tools, it's important to use them responsibly, keeping in mind >>> their strengths and limitations, as well as the ethical considerations of >>> automated content creation in journalism.* >>> >>> Can you elaborate on some of the technical jargon? >>> >>> *Certainly! Here are some common technical jargon related to Large >>> Language Models (LLMs) explained in journalist-friendly terms:* >>> >>> *1. **Pretraining**: This is the initial phase where the LLM learns from >>> a massive amount of text data on the internet. Think of it as the model >>> absorbing a vast library of information to understand language better.* >>> >>> *2. **Fine-tuning**: After pretraining, LLMs undergo fine-tuning to >>> specialize them for specific tasks. It's like giving the model extra >>> training in a particular subject, like finance or healthcare, to make it >>> more useful for specialized reporting.* >>> >>> *3. **Token**: In LLMs, text is broken down into smaller units called >>> tokens. A token can be as short as one character or as long as one word. >>> Knowing the number of tokens is important because it affects how much text >>> the model can handle at once.* >>> >>> *4. **Inference**: This term refers to the process of using a trained >>> LLM to generate text or make predictions. Journalists use inference to >>> create content, answer questions, or analyze data.* >>> >>> *5. **Prompt**: A prompt is the input you provide to an LLM to get a >>> response. It's like giving the model a question or a starting point for it >>> to generate text. Journalists often craft prompts to get specific >>> information or insights.* >>> >>> *6. **Bias**: LLMs can sometimes produce biased or unfair content >>> because they've learned from biased internet data. Journalists should be >>> aware of this and critically evaluate the model's outputs for any biases.* >>> >>> *7. **Algorithm**: This is a fancy word for a set of rules or >>> instructions that an LLM follows to perform tasks. Algorithms guide how the >>> model generates text and makes decisions.* >>> >>> *8. **NLP (Natural Language Processing)**: NLP is the field of study >>> that focuses on teaching computers to understand and generate human >>> language. LLMs are a product of NLP research.* >>> >>> *9. **ML (Machine Learning)**: LLMs are a type of machine learning >>> model. Machine learning is a way to make computers learn from data and >>> improve their performance over time.* >>> >>> *10. **Training Data**: This is the text data used to teach an LLM. It's >>> like the model's textbooks, and the quality and diversity of this data >>> influence how well the LLM performs.* >>> >>> *11. **Bias Mitigation**: This is the process of reducing bias in LLMs. >>> It's important in journalism to ensure that the information provided by the >>> model is fair and unbiased.* >>> >>> *12. **Ethical AI**: This refers to the practice of using LLMs >>> responsibly and ethically. Journalists should consider the ethical >>> implications of using these tools, especially when it comes to issues like >>> privacy and misinformation.* >>> >>> *13. **API (Application Programming Interface)**: Some LLMs offer APIs >>> that allow journalists to interact with the model through code, enabling >>> custom applications and integrations.* >>> >>> *14. **Fine-Tuned Models**: These are LLMs that have been trained for >>> specific tasks, like summarization, translation, or question-answering. >>> They are more specialized and can be particularly useful for journalism.* >>> >>> *Understanding these terms can help journalists effectively leverage >>> LLMs in their work while also being mindful of their limitations and >>> ethical considerations.* >>> >>> >>> - Steve >>> >>> On 10/7/23 5:13 PM, Tom Johnson wrote: >>> >>> Thanks. Those are impressive numbers. >>> Tom >>> >>> On Sat, Oct 7, 2023 at 4:11 PM Marcus Daniels <mar...@snoutfarm.com> >>> wrote: >>> >>>> The “large” refers to the number of parameters used. A smaller large >>>> language model – a deep neural net -- start about 3 billion parameters, but >>>> larger ones like Claude 2 (the latest large language model of the company >>>> that wrote the paper Steve mentioned) have more than 130 billion >>>> parameters. Amazingly, it is possible using (rooms of) GPUs and other >>>> accelerators to optimize in this a space of this size. The billions of >>>> parameters come from the vocabulary size – the number of tokens that need >>>> to be discriminated, the many layers of transformers that are needed to >>>> capture the complexity of human and non-human languages (like DNA), and the >>>> context window size – how many paragraphs or pages the model is trained on >>>> at a time. A small language model might be suitable for understanding the >>>> geometries of chemicals, say. >>>> >>>> >>>> *From:* Friam <friam-boun...@redfish.com> *On Behalf Of *Tom Johnson >>>> *Sent:* Saturday, October 7, 2023 2:38 PM >>>> *To:* The Friday Morning Applied Complexity Coffee Group < >>>> friam@redfish.com> >>>> *Subject:* Re: [FRIAM] Language Model Understanding >>>> >>>> >>>> Thanks for passing this along, Steve. I wish, however, the authors of >>>> this short piece would have included a definition of, in their usage, >>>> "Large Language Models" and "Small Language Models." Perhaps I can find >>>> those in the larger paper. >>>> >>>> Tom >>>> >>>> >>>> On Sat, Oct 7, 2023 at 12:34 PM Steve Smith <sasm...@swcp.com> wrote: >>>> >>>> This popular-press article came through my Google News feed recently >>>> which I thought might be useful to the Journalists/English-Majors on the >>>> list to help understand how LLMs work, etc. When I read it in detail >>>> (forwarded from my TS (TinyScreenPhone) on my LS (Large Screen Laptop)) I >>>> found it a bit more detailed and technical than I'd expected, but >>>> nevertheless rewarding and possibly offering some traction to >>>> Journalism/English majors as well as those with a larger investment in the >>>> CS/Math implied. >>>> >>>> Decomposing Language Models into Understandable Components >>>> >>>> <https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fwww.anthropic.com%2findex%2fdecomposing-language-models-into-understandable-components&c=E,1,m6E2NyQiQqZTmLRighr8jjGwfjDVwi00TYuM_4iskHnmAw78zWd55VlGTXwTdzWWkVGzInmkQvZFTQYuycBPX1Ii3Lxo1Bb5DZUFcSW0rUdv4Ma-WSM,&typo=1> >>>> >>>> and the (more) technical paper behind the article >>>> >>>> https://transformer-circuits.pub/2023/monosemantic-features/index.html >>>> >>>> <https://linkprotect.cudasvc.com/url?a=https%3a%2f%2ftransformer-circuits.pub%2f2023%2fmonosemantic-features%2findex.html&c=E,1,PIXQOjp_g2tr-D-_MpOt_B6uVdfil6N3FViwvJ78HkMFtSu7LpKOXlQSpqz_GQuJyD31X5eqiYtu2d2_VgXFqA4pekVbchFYvvf9GwiQ1zIgLfEt&typo=1> >>>> >>>> Despite having sent a few dogs into vaguely similar scuffles in my >>>> careen(r): >>>> >>>> Faceted Ontologies for Pre Incident Indicator Analysis >>>> <https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fapps.dtic.mil%2fsti%2ftr%2fpdf%2fADA588086.pdf&c=E,1,nPyDgDuU0nMwlV3W24mUTteOTIfbrs9SipIKre1b1_XIxOIWJ1ok_IKz181AKiB6geR5Mb1z6-DrUslqOaBkYUxiG5O8Zhc2mG3ALmDJQjCULUXzR9v8IUhidw,,&typo=1> >>>> SpindleViz >>>> <https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fwww.ehu.eus%2fccwintco%2fuploads%2fc%2fc6%2fHAIS2010_925.pdf&c=E,1,YwucoE_ffMQO_zO0A6WWAg8Y0J7wyHAGiJfcntyFBphchxgl4Tx6INQAtF7qA9XB07R52Jwnqfs4YO9s2MHP3Lnh-nUkpbULJfatlSIig_XB5ixy7yxF&typo=1> >>>> ... >>>> >>>> ... I admit to finding this both intriguing and well over my head on >>>> casual inspection... the (metaphorical?) keywords that drew me in most >>>> strongly included *Superposition* and *Thought Vectors*, though they >>>> are (nod to Glen) probably riddled (heaped, overflowing, bursting, bloated >>>> ... ) with excess meaning. >>>> >>>> https://gabgoh.github.io/ThoughtVectors/ >>>> <https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fgabgoh.github.io%2fThoughtVectors%2f&c=E,1,WnnKNla0iVte02BV2Imnk1J5revdzixjz7Z3w4XFowr2Ti3fkKSk8kKj8BQdnL11w3MtGPIKl2FP5Y-6zSsJ5O9A0luCjDPRrFpM_kDhF0jacJbhFA,,&typo=1> >>>> >>>> This leads me (surprise!) to an open ended discursive series of >>>> thoughts probably better left for a separate posting (probably rendered in >>>> a semasiographic language like Heptapod B >>>> <https://en.wikipedia.org/wiki/Heptapod_languages#Orthography>). >>>> >>>> <must... stop... now... > >>>> >>>> - Steve >>>> >>>> -. --- - / ...- .- .-.. .. -.. / -- --- .-. ... . / -.-. --- -.. . >>>> FRIAM Applied Complexity Group listserv >>>> Fridays 9a-12p Friday St. Johns Cafe / Thursdays 9a-12p Zoom >>>> https://bit.ly/virtualfriam >>>> <https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fbit.ly%2fvirtualfriam&c=E,1,7Se1kU5K0qRIvWJRD4XXT6OVdefOkjmd8iBwB4_ScBm8nmwT9MUlDa2OlXu7gsTvtdy7EwO5VnLshsDYL-lYhTu-S1P_ak0_11QPeoudf_Pg&typo=1> >>>> to (un)subscribe http://redfish.com/mailman/listinfo/friam_redfish.com >>>> <https://linkprotect.cudasvc.com/url?a=http%3a%2f%2fredfish.com%2fmailman%2flistinfo%2ffriam_redfish.com&c=E,1,XgC24CHCqH-MiGAYACD7z6PtLS8L3PA6Ntnnm8-GFS-8K9DlJz1wbcz4YhFucq-Ucbr9oeSbxnsUcDSZ0XfT5aalKerL34Pq0R57j_mDeX4RrFvxbg,,&typo=1> >>>> FRIAM-COMIC http://friam-comic.blogspot.com/ >>>> <https://linkprotect.cudasvc.com/url?a=http%3a%2f%2ffriam-comic.blogspot.com%2f&c=E,1,1GkLbYQODhOcaZjv5c91-iHu4986bkpXTFuaNhmX9fFK-EzJOVs6x1AKJrFBa7SMS9GHwxtjJZQ_CrzTmsDpTJ-KHGBzYStX4zSsywCdFT2GG8q4MO_gHwI,&typo=1> >>>> archives: 5/2017 thru present >>>> https://redfish.com/pipermail/friam_redfish.com/ >>>> <https://linkprotect.cudasvc.com/url?a=https%3a%2f%2fredfish.com%2fpipermail%2ffriam_redfish.com%2f&c=E,1,pPB6Gx8uMJadpxScEftegu18poh3jvMC3dByqfb7-kH5q9a1uN-Hx18Hpf2mWKYR1aATb5b9IUgqwfoulMiH2oh8K03lnbespQNIBfFm-D_etq1aSira&typo=1> >>>> 1/2003 thru 6/2021 http://friam.383.s1.nabble.com/ >>>> >>>> -. --- - 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