409 Matching Annotations
  1. Last 7 days
    1. The network of trails functions as a shared external memory for the ant colony.

      Just as a trail of pheromones serves the function of a shared external memory for an ant colony, annotations can create a set of associative trails which serve as an external memory for a broader human collective memory. Further songlines and other orality based memory methods form a shared, but individually stored internal collective memory for those who use and practice them.

      Vestiges of this human practice can be seen in modern society with the use and spread of cultural memes. People are incredibly good at seeing and recognizing memes and what they communicate and spreading them because they've evolved to function this way since the dawn of humanity.

    2. Stigmergy (/ˈstɪɡmərdʒi/ STIG-mər-jee) is a mechanism of indirect coordination, through the environment, between agents or actions.

      Example: ant pheromone paths

      Within ants, there can be a path left for others to follow, but what about natural paths in our environment that influence us to take them because of the idea of the "path of least resistence" or the effects of having paved cow paths.

      Similarly being lead by "the company that you keep".

      relathionship to research on hanging out with fat people tending to make one fatter.

  2. Aug 2022
    1. Huarte goes on to distinguish three levels of intelligence. The lowest of theseis the “docile wit,” which satisfies the maxim that he, along with Leibnitz andmany others, wrongly attributes to Aristotle, namely that there is nothing inthe mind that is not simply transmitted to it by the senses. The next higherlevel, normal human intelligence, goes well beyond the empiricist limitation:it is able to “engender within itself, by its own power, the principles on whichknowledge rests.”
    2. the writings of the Spanish physician JuanHuarte, who in the late sixteenth century published a widely translated studyon the nature of human intelligence. In the course of his investigations, Huartecame to wonder at the fact that the word for “intelligence,” ingenio, seems tohave the same Latin root as various words meaning “engender” or “generate.”
    3. I recall being told by a distinguishedanthropological linguist, in 1953, that he had no intention of working througha vast collection of materials that he had assembled because within a few yearsit would surely be possible to program a computer to construct a grammar froma large corpus of data by the use of techniques that were already fairly wellformalized.

      rose colored glasses...

  3. www.janeausten.pludhlab.org www.janeausten.pludhlab.org
    1. He is a clever man, a reading man

      He believes Louisa to be intellectually inferior to Captain Benwick, not a choice he would make for himself - like his sister and her husband he wants a marriage where they can meet as equals. Having said that...on this reading I've been questioning how smart the Admiral is

    1. https://web.archive.org/web/20220810205211/https://escapingflatland.substack.com/p/gpt-3

      Blogged a few first associations at https://www.zylstra.org/blog/2022/08/communicating-with-gpt-3/ . Prompt design for narrative research may be a useful experience here. 'Interviewing' GPT-3 a Luhmann-style conversation with a system? Can we ditch our notes for GPT-3? GPT-3 as interface to the internet. Fascinatiing essay, need to explore.

    1. For the sake of simplicity, go to Graph Analysis Settings and disable everything but Co-Citations, Jaccard, Adamic Adar, and Label Propogation. I won't spend my time explaining each because you can find those in the net, but these are essentially algorithms that find connections for you. Co-Citations, for example, uses second order links or links of links, which could generate ideas or help you create indexes. It essentially automates looking through the backlinks and local graphs as it generates possible relations for you.
  4. Jul 2022
    1. Erasmus learned Greek at the beginning of the 16th century, and from his study in Queens’ College, Cambridge, he spread the word of how important it was to read the Gospels and other foundational texts of Christianity in the language in which they were first written. His battle cry was ad fontes (“back to the sources”)

      i love this

    1. AI text generator, a boon for bloggers? A test report

      While I wanted to investigate AI text generators further, I ended up writing a testreport.. I was quite stunned because the AI ​​text generator turns out to be able to create a fully cohesive and to-the-point article in minutes. Here is the test report.

    1. A cognitiveagent is needed to perform this very action (that needs to be recurrent)—and another agent is neededto further build on that (again recurrently and irrespective to the particular agents involved).

      This appears to be setting up the conditions for an artificial cognitive agent to be able to play a role (ie Artificial Intelligence)

    2. In this paper, we propose and analyse a potential power triangle between three kinds of mutuallydependent, mutually threatening and co-evolving cognitive systems—the human being, the socialsystem and the emerging synthetic intelligence. The question we address is what configuration betweenthese powers would enable humans to start governing the global socio-econo-political system
      • Optimization problem - human beings, their social system and AI - what is optimal configuration?
    1. Superintelligence has long served as a source of inspiration for dystopian science fiction that showed humanity being overthrown, defeated, or imprisoned by machines.
    1. he distinguishes three dimensions of dependent origination and this is in his commentary on the guardian of malama jamaica carica called clear words he talks about causal dependence that is every phenomenon depends upon causes and 00:16:19 conditions and gives rise to further causes and conditions um myriological dependence that is every phenomenon every composite phenomenon depends upon the parts that uh that it 00:16:31 comprises and every phenomenon is also dependent upon the holes or the systems in which it figures parts depend on holes holes depend on parts and that reciprocal meteorological dependence 00:16:44 characterizes all of reality and third often overlooked but most important is dependence on conceptual imputation that is things depend in order to be represented as the kinds of 00:16:57 things they are on our conceptual resources our affective resources and as john dunn emphasized our purposes in life this third one really means this um 00:17:09 everything that shows up for us in the world the way we carve the world up the way we um the way we experience the world is dependent not just on how the world is but on the conceptual resources 00:17:22 as well as the perceptual resources through which we understand the world and it's worth recognizing that um when we think about this there are a bunch of um contemporary majamakers majamikas we 00:17:34 might point to as well and so paul fireauben who's up there on on the left well really an austrian but he spent much of his life in america um willard van norman kwine um up on the right wilford sellers and paul churchland

      This is a key statement: how we experience the world depends on the perceptual and cognitive lens used to filter the world through.

      Francis Heylighen proposes a nondual system based on causal dependency relationships to serve as the foundation for distributed cognition.(collective intelligence).


  5. Jun 2022
    1. We've yet to see note-taking platforms meaningfully add AI affordances into their systems, but there are hints at how they could in other platforms.

      A promising project is Paul Bricman's Conceptarium.

  6. www.audible.com www.audible.com
    1. animal intelligence or simply in learning more about dogs as our companions--or both

      or human intelligence

    1. https://www.youtube.com/watch?v=bWkwOefBPZY

      Some of the basic outline of this looks like OER (Open Educational Resources) and its "five Rs": Retain, Reuse, Revise, Remix and/or Redistribute content. (To which I've already suggested the sixth: Request update (or revision control).

      Some of this is similar to:

      The Read Write Web is no longer sufficient. I want the Read Fork Write Merge Web. #osb11 lunch table. #diso #indieweb [Tantek Çelik](http://tantek.com/2011/174/t1/read-fork-write-merge-web-osb110

      Idea of collections of learning as collections or "playlists" or "readlists". Similar to the old tool Readlist which bundled articles into books relatively easily. See also: https://boffosocko.com/2022/03/26/indieweb-readlists-tools-and-brainstorming/

      Use of Wiki version histories

      Some of this has the form of a Wiki but with smaller nuggets of information (sort of like Tiddlywiki perhaps, which also allows for creating custom orderings of things which had specific URLs for displaying and sharing them.) The Zettelkasten idea has some of this embedded into it. Shared zettelkasten could be an interesting thing.

      Data is the new soil. A way to reframe "data is the new oil" but as a part of the commons. This fits well into the gardens and streams metaphor.

      Jerry, have you seen Matt Ridley's work on Ideas Have Sex? https://www.ted.com/talks/matt_ridley_when_ideas_have_sex Of course you have: https://app.thebrain.com/brains/3d80058c-14d8-5361-0b61-a061f89baf87/thoughts/3e2c5c75-fc49-0688-f455-6de58e4487f1/attachments/8aab91d4-5fc8-93fe-7850-d6fa828c10a9

      I've heard Jerry mention the idea of "crystallization of knowledge" before. How can we concretely link this version with Cesar Hidalgo's work, esp. Why Information Grows.

      Cross reference Jerry's Brain: https://app.thebrain.com/brains/3d80058c-14d8-5361-0b61-a061f89baf87/thoughts/4bfe6526-9884-4b6d-9548-23659da7811e/notes

    1. Dall-E delivers ten images for each request, and when you see results that contain sensitive or biased content, you can flag them to OpenAI for review. The question then becomes whether OpenAI wants Dall-E's results to reflect society's approximate reality or some idealized version. If an occupation is majority male or female, for instance, and you ask Dall-E to illustrate someone doing that job, the results can either reflect the actual proportion in society, or some even split between genders. They can also account for race, weight, and other factors. So far, OpenAI is still researching how exactly to structure these results. But as it learns, it knows it has choices to make.

      Philosophical questions for AI-generated artwork

      As if we needed more technology to dissolve a shared, cohesive view of reality, we need to consider how it is possible to tune the AI parameters to reflect some version of what is versus some version of how we want it to be.

    1. Harness collective intelligence augmented by digital technology, and unlock exponential innovation. Beyond old hierarchical structures and archaic tools.


      The words "beyond", "hierarchical", and "archaic" are all designed to marginalize prior thought and tools which all work, and are likely upon which this broader idea is built. This is a potentially toxic means of creating "power over" this prior art rather than a more open spirit of "power with".

  7. May 2022
    1. Bret Victor shared this post to make the point that we shouldn't be worrying about sentient AI right now; that the melting ice caps are way more of a threat than AGI. He linked to this article, saying that corporations act like a non-human, intelligent entity, that has real impacts in the world today, that may be way more consequential than AI.

    1. Ben Williamson shared this post on Twitter, saying that it's a good idea to remove the words 'artificial intelligence' and 'AI' from policy statements, etc. as a way of talking about specific details of a technology. We can see loads of examples of companies using 'AI' to obfuscate what they are really going.

    1. The bulk of Vumacam’s subscribers have thus far been private security companies like AI Surveillance, which supply anything from armed guards to monitoring for a wide range of clients, including schools, businesses, and residential neighborhoods. This was always the plan: Vumacam CEO Croock started AI Surveillance with Nichol shortly after founding Vumacam and then stepped away to avoid conflicts with other Vumacam customers.

      AI-driven Surveillance-as-a-Service

      Vumacam provides the platform, AI-driven target selection, and human review. Others subscribe to that service and add their own layers of services to customers.

  8. Apr 2022
    1. Since most of our feeds rely on either machine algorithms or human curation, there is very little control over what we actually want to see.

      While algorithmic feeds and "artificial intelligences" might control large swaths of what we see in our passive acquisition modes, we can and certainly should spend more of our time in active search modes which don't employ these tools or methods.

      How might we better blend our passive and active modes of search and discovery while still having and maintaining the value of serendipity in our workflows?

      Consider the loss of library stacks in our research workflows? We've lost some of the serendipity of seeing the book titles on the shelf that are adjacent to the one we're looking for. What about the books just above and below it? How do we replicate that sort of serendipity into our digital world?

      How do we help prevent the shiny object syndrome? How can stay on task rather than move onto the next pretty thing or topic presented to us by an algorithmic feed so that we can accomplish the task we set out to do? Certainly bookmarking a thing or a topic for later follow up can be useful so we don't go too far afield, but what other methods might we use? How can we optimize our random walks through life and a sea of information to tie disparate parts of everything together? Do we need to only rely on doing it as a broader species? Can smaller subgroups accomplish this if carefully planned or is exploring the problem space only possible at mass scale? And even then we may be under shooting the goal by an order of magnitude (or ten)?

    1. ResearchRabbit, which fully launched in August 2021, describes itself as “Spotify for papers”.

      Research Rabbit is a search engine for academic research that was launched in August of 2021 and bills itself as "Spotify for papers." It uses artificial intelligence to recommend related papers to researchers and updates those recommendations based on the contents of one's growing corpus of interest.

    2. Connected Papers uses the publicly available corpus compiled by Semantic Scholar — a tool set up in 2015 by the Allen Institute for Artificial Intelligence in Seattle, Washington — amounting to around 200 million articles, including preprints.

      Semantic Scholar is a digital tool created by the Allen Institute for Artificial Intelligence in Seattle, Washington in 2015. It's corpus is publicly available for search and is used by other tools including Connected Papers.

    1. ReconfigBehSci [@SciBeh]. (2021, November 14). @STWorg @olbeun @lombardi_learn @kostas_exarhia @stefanmherzog @commscholar @johnfocook @Briony_Swire @Sander_vdLinden @DG_Rand @kendeou @dlholf @ProfSunitaSah @HendirkB @gordpennycook @andyguess @emmapsychology @ThomsonAngus @UMDCollegeofEd @gavaruzzi @katytapper @orspaca [Tweet]. Twitter. https://twitter.com/SciBeh/status/1459813535974842371

    1. ReconfigBehSci [@SciBeh]. (2021, November 14). Kai Spiekermann will speak the need for science communication and how it supports the pivotal role of knowledge in a functioning democracy. The panel will focus on what collective intelligence has to offer. 3/6 [Tweet]. Twitter. https://twitter.com/SciBeh/status/1459813528987217926

    1. He continues by comparing open works to Quantum mechanics, and he arrives at the conclusion that open works are more like Einstein's idea of the universe, which is governed by precise laws but seems random at first. The artist in those open works arranges the work carefully so it could be re-organized by another but still keep the original voice or intent of the artist.

      Is physics open or closed?

      Could a play, made in a zettelkasten-like structure, be performed in a way so as to keep a consistent authorial voice?

      What potential applications does the idea of opera aperta have for artificial intelligence? Can it be created in such a way as to give an artificial brain a consistent "authorial voice"?

    1. ReconfigBehSci. (2021, November 14). Join us this week at our 2021 SciBeh Workshop on the topic of ‘Science Communication as Collective Intelligence’! Nov. 18/19 with a schedule that allows any time zone to take part in at least some of the workshop. Includes: Keynotes, panels, and breakout manifesto writing 1/6 [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1459813525635973122

    1. Empathy – This is perhaps the most important element of emotional intelligence. Empathy is the ability to identify with and understand the wants, needs, and viewpoints of those around you. People with empathy are good at recognizing the feelings of others, even when those feelings may not be obvious. As a result, empathetic people are usually excellent at managing relationships , listening , and relating to others. They avoid stereotyping and judging too quickly, and they live their lives in a very open, honest way.

      Empathy – I value empathy as I consider it to be the most important element of emotional intelligence. Empathy means to be able to recognise and understand the wants, needs, and perspectives of others around us.

      Empathy allows you to be better at recognizing the feelings of others, even if those people aren't making it obvious to notice. Hence, empathetic people make excellent relationship managers, also making good listeners , and relating to others. This traits allows one to avoid stereotyping and judging others at face value.

  9. Mar 2022
    1. ReconfigBehSci. (2021, November 20). Thanks to everyone who took part in our Workshop on #SciComm as Collective Intelligence It was amazing! Materials will be uploaded to http://SciBeh.org website 1/2 @kakape @DrTomori @SpiekermannKai @GeoffreySupran @ArendJK @STWorg @dgurdasani1 @suneman @philipplenz6 [Tweet]. @SciBeh. https://twitter.com/SciBeh/status/1461978072924762117

    1. projet européen X5-GON (Global Open Education Network) qui collecte les informations sur les ressources éducatives libres et qui marche bien avec un gros apport d’intelligence artificielle pour analyser en profondeur les documents
    1. This generative model normally penalizes predicted toxicity and rewards predicted target activity. We simply proposed to invert this logic by using the same approach to design molecules de novo, but now guiding the model to reward both toxicity and bioactivity instead.

      By changing the parameters of the AI, the output of the AI changed dramatically.

    1. Of course, users are still the source of the insight that makes a complete document also a compelling document.

      Nice that he takes a more humanistic viewpoint here rather than indicating that it will all be artificial intelligence in the future.

  10. Feb 2022
    1. Stay at the forefront of educational innovation

      What about a standard of care for students?

      Bragging about students not knowing how the surveillance technology works is unethical.<br><br>Students using accessibility software or open educational resources shouldn't be punished for accidentally avoiding surveillance. pic.twitter.com/Uv7fiAm0a3

      — Ian Linkletter (@Linkletter) February 22, 2022
      <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>

      #annotation https://t.co/wVemEk2yao

      — Remi Kalir (@remikalir) February 23, 2022
      <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
    1. At the back of Dr Duncan's book on the topic, Index, A History Of The, he includes not one but two indexes, in order to make a point.

      Dennis Duncan includes two indices in his book Index, A History of The, one by a professional human indexer and the second generated by artificial intelligence. He indicates that the human version is far better.

    1. Der Hauptanwendungspartner für die hier beschriebenen Lösungen war und ist der Sie-mens-Konzern. Die Lösungen wurden durch das KI-Start-up Giance, eine deutsch-chinesi-sche Ausgründung des DFKI, für den chinesischen Markt angepasst und weiterentwickelt.

      KI-basierte Serviceplattform für Enterprise Intelli- gence

    2. Unsere Global Enterprise Intelligence (GEI) Platform eignet sich nicht nur zur Beobachtung von Zulieferern, sondern wird auch in ande-ren Bereichen eingesetzt, in denen Firmen beobachtet werden müssen wie z. B. Wettbewer-beranalyse, Partnerbetreuung, Key-Account-Management oder Portfolio- Management.


    3. Knowledge Graph Check & UpdateMithilfe der Neo4J-Graphdatenbanktechnologie werden für die Anwendungen Wis-sensgraphen aufgebaut und ständig um neue Relationen und Eigenschaften der beob-achteten Firmen ergänzt. Die Wissensgraphen dienen nicht nur der Visualisierung der Ergebnisse, sie werden auch zum Entity Linking und zur Erkennung von bereits be-kannter Information verwendet

      Neo4J-Graphdatenbanktechnologie werden für die Anwendungen Wissensgraphen aufgebaut und ständig um neue Relationen und Eigenschaften der beobachteten Firmen ergänzt.

      Die Wissensgraphen dienen nicht nur der Visualisierung der Ergebnisse, sie werden auch zum Entity Linking und zur Erkennung von bereits bekannter Information verwendet.

    1. integrierten IT-basierten Management- und Entscheidungsunterstützung (Business Intelligence)

      Business Intelligence



    1. We need to getour thoughts on paper first and improve them there, where we canlook at them. Especially complex ideas are difficult to turn into alinear text in the head alone. If we try to please the critical readerinstantly, our workflow would come to a standstill. We tend to callextremely slow writers, who always try to write as if for print,perfectionists. Even though it sounds like praise for extremeprofessionalism, it is not: A real professional would wait until it wastime for proofreading, so he or she can focus on one thing at a time.While proofreading requires more focused attention, finding the rightwords during writing requires much more floating attention.

      Proofreading while rewriting, structuring, or doing the thinking or creative parts of writing is a form of bikeshedding. It is easy to focus on the small and picayune fixes when writing, but this distracts from the more important parts of the work which really need one's attention to be successful.

      Get your ideas down on paper and only afterwards work on proofreading at the end. Switching contexts from thinking and creativity to spelling, small bits of grammar, and typography can be taxing from the perspective of trying to multi-task.

      Link: Draft #4 and using Webster's 1913 dictionary for choosing better words/verbiage as a discrete step within the rewrite.

      Linked to above: Are there other dictionaries, thesauruses, books of quotations, or individual commonplace books, waste books that can serve as resources for finding better words, phrases, or phrasing when writing? Imagine searching through Thoreau's commonplace book for finding interesting turns of phrase. Naturally searching through one's own commonplace book is a great place to start, if you're saving those sorts of things, especially from fiction.

      Link this to Robin Sloan's AI talk and using artificial intelligence and corpuses of literature to generate writing.

  11. Jan 2022
    1. https://vimeo.com/232545219

      from: Eyeo Conference 2017


      Robin Sloan at Eyeo 2017 | Writing with the Machine | Language models built with recurrent neural networks are advancing the state of the art on what feels like a weekly basis; off-the-shelf code is capable of astonishing mimicry and composition. What happens, though, when we take those models off the command line and put them into an interactive writing environment? In this talk Robin presents demos of several tools, including one presented here for the first time. He discusses motivations and process, shares some technical tips, proposes a course for the future — and along the way, write at least one short story together with the audience: all of us, and the machine.


      Robin created a corpus using If Magazine and Galaxy Magazine from the Internet Archive and used it as a writing tool. He talks about using a few other models for generating text.

      Some of the idea here is reminiscent of the way John McPhee used the 1913 Webster Dictionary for finding words (or le mot juste) for his work, as tangentially suggested in Draft #4 in The New Yorker (2013-04-22)

      Cross reference: https://hypothes.is/a/t2a9_pTQEeuNSDf16lq3qw and https://hypothes.is/a/vUG82pTOEeu6Z99lBsrRrg from https://jsomers.net/blog/dictionary

      Croatian acapella singing: klapa https://www.youtube.com/watch?v=sciwtWcfdH4

      Writing using the adjacent possible.

      Corpus building as an art [~37:00]

      Forgetting what one trained their model on and then seeing the unexpected come out of it. This is similar to Luhmann's use of the zettelkasten as a serendipitous writing partner.

      Open questions

      How might we use information theory to do this more easily?

      What does a person or machine's "hand" look like in the long term with these tools?

      Can we use corpus linguistics in reverse for this?

      What sources would you use to train your model?


      • Andrej Karpathy. 2015. "The Unreasonable Effectiveness of Recurrent Neural Networks"
      • Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al. "Generating sentences from a continuous space." 2015. arXiv: 1511.06349
      • Stanislau Semeniuta, Aliaksei Severyn, and Erhardt Barth. 2017. "A Hybrid Convolutional Variational Autoencoder for Text generation." arXiv:1702.02390
      • Soroush Mehri, et al. 2017. "SampleRNN: An Unconditional End-to-End Neural Audio Generation Model." arXiv:1612.07837 applies neural networks to sound and sound production
    1. Markoff, a long-time chronicler of computing, sees Engelbart as one pole in a decades-long competition "between artificial intelligence and intelligence augmentation -- A.I. versus I.A."

      There is an interesting difference between artificial intelligence and intelligence automation. Index cards were already doing the second by the early 1940s.

  12. Dec 2021
    1. There is the mammal way and there is the bird way." This is one scientist's pithy distinction between mammal brains and bird brains: two ways to make a highly intelligent mind.
    1. evolutionary theorists like Christopher berm whose book hierarchy in the forest he's a primatologist is quite explicit about 00:11:27 this and says well this is precisely what makes human politics different from the politics of say chimpanzees or bonobos or orangutangs is what he calls our actuarial intelligence which I 00:11:39 believe what he means by this is the fact that we can in fact imagine what another kind of society might be like

      Primatologist [[Christopher Boehm]] argues in his book Hierarchy in the Forest: The Evolution of Egalitarian Behavior that humans are different from our primate ancestors because homo sapiens possess actuarial intelligence, or the ability to imagine what other kinds of society might look like.

  13. Nov 2021
  14. Oct 2021
    1. Crowdpol is a pro-social platform, where changemakers from across the globe can work together to tackle the challenges of the century.

      Shared by Ferial Puren

    1. Annotate the web, with anyone, anywhere.

      Gyuri Lajos recommended Hypothesis to the Stop Reset Go team to simulate the experience of using the IndyWiki project that he is working on.

    1. Gyuri Lajos is a member of the Stop Reset Go team. He is working on IndyWiki as a Web3 Native platform for collective intelligence.

  15. Sep 2021
  16. Aug 2021
    1. Provide more opportunities for new talent. Because healthcare has been relatively solid and stagnant in what it does, we're losing out on some of the new talent that comes out — who are developing artificial intelligence, who are working at high-tech firms — and those firms can pay significantly higher than hospitals for those talents. We have to find a way to provide some opportunities for that and apply those technologies to make improvements in healthcare.

      Intestesing. Mr. Roach thinks healthcare is not doing enough to attract new types of talent (AI and emerging tech) into healthcare. We seem to be losing this talent to the technology sector.

      I would agree with this point. Why work for healthcare with all of its massive demands and HIPPA and lack of people knowing what you are even building. Instead, you can go into tech, have a better quality of life, get paid so much more, and have the possibility of exiting due to a buyout from the healthcare industry.

    1. Building on platforms' stores of user-generated content, competing middleware services could offer feeds curated according to alternate ranking, labeling, or content-moderation rules.

      Already I can see too many companies relying on artificial intelligence to sort and filter this material and it has the ability to cause even worse nth degree level problems.

      Allowing the end user to easily control the content curation and filtering will be absolutely necessary, and even then, customer desire to do this will likely loose out to the automaticity of AI. Customer laziness will likely win the day on this, so the design around it must be robust.

  17. Jul 2021
    1. Facebook AI. (2021, July 16). We’ve built and open-sourced BlenderBot 2.0, the first #chatbot that can store and access long-term memory, search the internet for timely information, and converse intelligently on nearly any topic. It’s a significant advancement in conversational AI. https://t.co/H17Dk6m1Vx https://t.co/0BC5oQMEck [Tweet]. @facebookai. https://twitter.com/facebookai/status/1416029884179271684

  18. Jun 2021
    1. intelligence collective réflexive

      Il ne s’agirait donc pas de simplement devenir collectivement «plus intelligent» (au sens d’efficace, dans un strict paradigme scientifique et technique pour accélérer le fonctionnement de l’économie), mais aussi réflexif: réfléchir aux conditions de cette société renouvelée, en proie à de nouvelles dynamiques de pouvoir extrêmement concentrées et asymétriques.

    1. t hadn’t learned sort of the concept of a paddle or the concept of a ball. It only learned about patterns of pixels.

      Cognition and perception are closely related in humans, as the theory of embodied cognition has shown. But until the concept of embodied cognition gained traction, we had developed a pretty intellectual concept of cognition: as something located in our brains, drained of emotions, utterly rational, deterministic, logical, and so on. This is still the concept of intelligence that rules research in AI.

    2. the original goal at least, was to have a machine that could be like a human, in that the machine could do many tasks and could learn something in one domain, like if I learned how to play checkers maybe that would help me learn better how to play chess or other similar games, or even that I could use things that I’d learned in chess in other areas of life, that we sort of have this ability to generalize the things that we know or the things that we’ve learned and apply it to many different kinds of situations. But this is something that’s eluded AI systems for its entire history.

      The truth is we do not need to have computers to excel in the things we do best, but to complement us. We shall bet on cognitive extension instead of trying to re-create human intelligence --which is a legitimate area of research, but computer scientists should leave this to cognitive science and neuroscience.

    1. Last year, Page told a convention of scientists that Google is “really trying to build artificial intelligence and to do it on a large scale.”

      What if they're not? What if they're building an advertising machine to manipulate us into giving them all our money?

      From an investor perspective, the artificial answer certainly seems sexy while using some clever legerdemain to keep the public from seeing what's really going on behind the curtain?

    2. It seeks to develop “the perfect search engine,” which it defines as something that “understands exactly what you mean and gives you back exactly what you want.”

      What if we want more serendipity? What if we don't know what we really want? Where is this in their system?

  19. May 2021
    1. Turing was an exceptional mathematician with a peculiar and fascinating personality and yet he remains largely unknown. In fact, he might be considered the father of the von Neumann architecture computer and the pioneer of Artificial Intelligence. And all thanks to his machines; both those that Church called “Turing machines” and the a-, c-, o-, unorganized- and p-machines, which gave rise to evolutionary computations and genetic programming as well as connectionism and learning. This paper looks at all of these and at why he is such an often overlooked and misunderstood figure.
  20. Mar 2021
    1. In this respect, we join Fitzpatrick (2011) in exploring “the extent to which the means of media production and distribution are undergoing a process of radical democratization in the Web 2.0 era, and a desire to test the limits of that democratization”

      Something about this is reminiscent of WordPress' mission to democratize publishing. We can also compare it to Facebook whose (stated) mission is to connect people, while it's actual mission is to make money by seemingly radicalizing people to the extremes of our political spectrum.

      This highlights the fact that while many may look at content moderation on platforms like Facebook as removing their voices or deplatforming them in the case of people like Donald J. Trump or Alex Jones as an anti-democratic move. In fact it is not. Because of Facebooks active move to accelerate extreme ideas by pushing them algorithmically, they are actively be un-democratic. Democratic behavior on Facebook would look like one voice, one account and reach only commensurate with that person's standing in real life. Instead, the algorithmic timeline gives far outsized influence and reach to some of the most extreme voices on the platform. This is patently un-democratic.

    1. Meanwhile, the algorithms that recommend this content still work to maximize engagement. This means every toxic post that escapes the content-moderation filters will continue to be pushed higher up the news feed and promoted to reach a larger audience.

      This and the prior note are also underpinned by the fact that only 10% of people are going to be responsible for the majority of posts, so if you can filter out the velocity that accrues to these people, you can effectively dampen down the crazy.

    2. In his New York Times profile, Schroepfer named these limitations of the company’s content-moderation strategy. “Every time Mr. Schroepfer and his more than 150 engineering specialists create A.I. solutions that flag and squelch noxious material, new and dubious posts that the A.I. systems have never seen before pop up—and are thus not caught,” wrote the Times. “It’s never going to go to zero,” Schroepfer told the publication.

      The one thing many of these types of noxious content WILL have in common are the people at the fringes who are regularly promoting it. Why not latch onto that as a means of filtering?

    3. But anything that reduced engagement, even for reasons such as not exacerbating someone’s depression, led to a lot of hemming and hawing among leadership. With their performance reviews and salaries tied to the successful completion of projects, employees quickly learned to drop those that received pushback and continue working on those dictated from the top down.

      If the company can't help regulate itself using some sort of moral compass, it's imperative that government or other outside regulators should.

    4. <small><cite class='h-cite via'> <span class='p-author h-card'>Joan Donovan, PhD</span> in "This is just some of the best back story I’ve ever read. Facebooks web of influence unravels when @_KarenHao pulls the wrong thread. Sike!! (Only the Boston folks will get that.)" / Twitter (<time class='dt-published'>03/14/2021 12:10:09</time>)</cite></small>

    1. System architects: equivalents to architecture and planning for a world of knowledge and data Both government and business need new skills to do this work well. At present the capabilities described in this paper are divided up. Parts sit within data teams; others in knowledge management, product development, research, policy analysis or strategy teams, or in the various professions dotted around government, from economists to statisticians. In governments, for example, the main emphasis of digital teams in recent years has been very much on service design and delivery, not intelligence. This may be one reason why some aspects of government intelligence appear to have declined in recent years – notably the organisation of memory.57 What we need is a skill set analogous to architects. Good architects learn to think in multiple ways – combining engineering, aesthetics, attention to place and politics. Their work necessitates linking awareness of building materials, planning contexts, psychology and design. Architecture sits alongside urban planning which was also created as an integrative discipline, combining awareness of physical design with finance, strategy and law. So we have two very well-developed integrative skills for the material world. But there is very little comparable for the intangibles of data, knowledge and intelligence. What’s needed now is a profession with skills straddling engineering, data and social science – who are adept at understanding, designing and improving intelligent systems that are transparent and self-aware58. Some should also specialise in processes that engage stakeholders in the task of systems mapping and design, and make the most of collective intelligence. As with architecture and urban planning supply and demand need to evolve in tandem, with governments and other funders seeking to recruit ‘systems architects’ or ‘intelligence architects’ while universities put in place new courses to develop them.
  21. Feb 2021
  22. Jan 2021
    1. As an opening move, I’d suggest that we could reconceptualize intelligence as NaQ (neuroacoustic quotient), or ‘the capacity to cleanly switch between different complex neuroacoustic profiles.’

      also seems more neutral and embracing the differences in [[neurodiversity]] / individual thinking vs relentless optimizing for a certain KPI (like for IQs) #[[to write]]

  23. Dec 2020
    1. création collective de sens qui est au cœur de l’intelligence humaine

      objectif de l'intelligence collective, des humanités numériques comme discipline en communauté