https://hu.ma.ne/

The AI pin has just been listed o/a 2023-11-10.

—epilepticrabbit @epilepticrabbit@social.coop on Nov 09, 2023, 11:51 at https://mastodon.social/@epilepticrabbit@social.coop/111382329524902140

https://ailiteracy.fyi/

Doug Belshaw joint

https://poe.com/

https://questy.ai/

As an ex-Viv (w/ Siri team) eng, let me help ease everyone's future trauma as well with the Fundamentals of Assisted Intelligence.<br><br>Make no mistake, OpenAI is building a new kind of computer, beyond just an LLM for a middleware / frontend. Key parts they'll need to pull it off:… https://t.co/uIbMChqRF9

— Rob Phillips 🤖🦾 (@iwasrobbed) October 29, 2023

https://www.theguardian.com/media/2023/oct/31/microsoft-accused-of-damaging-guardians-reputation-with-ai-generated-poll

https://www.nytimes.com/2023/10/27/business/media/reviewed-usa-today-ai-writers.html

https://www.cnn.com/2023/08/30/tech/gannett-ai-experiment-paused/index.html

https://www.washingtonpost.com/pr/wp/2016/08/05/the-washington-post-experiments-with-automated-storytelling-to-help-power-2016-rio-olympics-coverage/

Wang et. al. "Scientific discovery in the age of artificial intelligence", Nature, 2023.

A paper about the current state of using AI/ML for scientific discovery, connected with the AI4Science workshops at major conferences.

(NOTE: since Springer/Nature don't allow public pdfs to be linked without a paywall, we can't use hypothesis directly on the pdf of the paper, this link is to the website version of it which is what we'll use to guide discussion during the reading group.)

Three AI Chatbots, Two Books, and One Weird Annotation Experiment by Remi Kalir on September 29, 2023 https://remikalir.com/blog/three-ai-chatbots-two-books-and-one-weird-annotation-experiment/

An interesting divergent take on writing in library books...

https://typeshare.co/go-go-golems/posts/nobody-likes-boring-ai-content-how-to-write-unique-marketing-copy-with-chatgpt

https://typeshare.co/go-go-golems/posts/under-the-hood-how-to-use-chatgpts-attention-mechanism-for-better-prompts

Are we stretching too far by saying that AI are currently emergent? Isn't this like saying that card indexes of the early 20th century are computers. In reality they were data storage and the "computing" took place when humans did the actual data processing/thinking to come up with new results.

Emergence would seem to actually be the point which comes about when the AI takes its own output and continues processing (successfully) on it.

https://aboard.com/

A card-based collaboration tool that leverages information visualization. Pinterest for collaborative teams with expandable data.

Looks interesting and I've got a beta invite, but not sure if it fits any of my needs, particularly with an eye toward note taking.

https://www.theguardian.com/technology/2023/sep/01/mushroom-pickers-urged-to-avoid-foraging-books-on-amazon-that-appear-to-be-written-by-ai

https://openai.com/blog/teaching-with-ai

https://shindig.com/login/event/agifuture

https://www.britannica.com/topic/RUR

This may be an interesting use case for artificial intelligence tools like ChatGPT which can provide the reader of complex material with simplified synopses to allow better penetration of the material (potentially by removing jargon, argot, etc.)

He then pushes a button and "plays back" the opinion whenever it seems appropriate to do so. He has performed acceptably without having had to think.

This seems to be a reasonable argument to make for those who ask, why read? why take notes? especially when we can use search and artificial intelligence to do the work for us. Can we really?

https://medium.com/intelliboosters/is-tiago-fortes-build-a-second-brain-still-relevant-in-the-age-of-chatgpt-b7a7c5e8637c

These articles kill me. They sit at surface level and don't delve any deeper for actual insight. And this is why these techniques are necessary. (BTW, these methods go back thousands of years... Tiago didn't invent them.)

https://a16z.simplecast.com/episodes/a-true-second-brain-xrODaBD2

Recommended by Michael Grossman

https://claude.ai/onboarding

Kalir, Remi H. “Playing with Claude.” Academic blog. Remi Kalir (blog), August 25, 2023. https://remikalir.com/blog/playing-with-claude/.

https://claude.ai/

https://chat.openai.com/auth/login

https://openai.com/

&list=PLdAbfZfaH_1I0vD3GsgbIdsLp6id6AOUb&index=9

https://www.youtube.com/playlist?list=PLdAbfZfaH_1I0vD3GsgbIdsLp6id6AOUb

https://myessayfeedback.ai/

Mills, Anna, Maha Bali, and Lance Eaton. “How Do We Respond to Generative AI in Education? Open Educational Practices Give Us a Framework for an Ongoing Process.” Journal of Applied Learning and Teaching 6, no. 1 (June 11, 2023): 16–30. https://doi.org/10.37074/jalt.2023.6.1.34.

Annotation url: urn:x-pdf:bb16e6f65a326e4089ed46b15987c1e7

Search: https://jonudell.info/h/facet/?user=chrisaldrich&max=100&exactTagSearch=true&expanded=true&addQuoteContext=true&url=urn%3Ax-pdf%3Abb16e6f65a326e4089ed46b15987c1e7

What does open education tell us about AI in academia?

This is one of the things that doesn't seem to be being explored enough presently, or at least I'm not seeing it outside of the SAG and WGA strikes where it seems to be a side issue rather than a primary issue.

https://textfx.withgoogle.com/

A Generative AI Primer on 2023-08-15 by Brian Basgen

ᔥGeoff Corb in LinkedIn update (accessed:: 2023-08-26 01:34:45)

Epstein, Ziv, Hertzmann, Aaron, Herman, Laura, Mahari, Robert, Frank, Morgan R., Groh, Matthew, Schroeder, Hope et al. "Art and the science of generative AI: A deeper dive." ArXiv, (2023). Accessed July 21, 2023. https://doi.org/10.1126/science.adh4451.

Abstract

A new class of tools, colloquially called generative AI, can produce high-quality artistic media for visual arts, concept art, music, fiction, literature, video, and animation. The generative capabilities of these tools are likely to fundamentally alter the creative processes by which creators formulate ideas and put them into production. As creativity is reimagined, so too may be many sectors of society. Understanding the impact of generative AI - and making policy decisions around it - requires new interdisciplinary scientific inquiry into culture, economics, law, algorithms, and the interaction of technology and creativity. We argue that generative AI is not the harbinger of art's demise, but rather is a new medium with its own distinct affordances. In this vein, we consider the impacts of this new medium on creators across four themes: aesthetics and culture, legal questions of ownership and credit, the future of creative work, and impacts on the contemporary media ecosystem. Across these themes, we highlight key research questions and directions to inform policy and beneficial uses of the technology.

reply to u/drogers8 at https://www.reddit.com/r/antinet/comments/14ot4na/inserting_a_maincards_with_lack_of_memory/

I would submit that your first sentence is wildly false.

What topic(s) cover your newly made cards? Look those up in your index and find where those potentially related cards are (whether you remember them or not). Go to that top level card listed in your index and see what's there or in the section of cards that come after it. Find the best card in that branch and file your new card(s) as appropriate. If necessary, cross-index them with sub-topics in your index to make them more findable in the future. If you don't find one or more of those topics in your index, then create a new branch and start an index entry for one or more of those terms. (You'll find yourself making lots of index entries to start, but it will eventually slow down—though it shouldn't stop—as your collection grows.)

Ideally, with regular use, you'll likely remember more and more, especially for active areas you're really interested in. However, take comfort that the system is designed to let you forget everything! This forgetting will actually help create future surprise as well as serendipity that will actually be beneficial for potentially generating new ideas as you use (and review) your notes.

And if you don't believe me, consider that Alberto Cevolini edited an entire book, broadly about these techniques—including an entire chapter on Luhmann—, which he aptly named Forgetting Machines!

AI has recently become such a big thing in our lives today. For a while I was seeing chatgpt and snapchat AI all over the media. I feel like people ask these sites stupid questions that they already know the answer too because they don't want to take a few minutes to think about the answer. I found a website stating how many people use AI and not surprisingly, it shows that 27% of Americans say they use it several times a day. I can't imagine how many people use it per year.

• limited (machine) intelligence

  • cannot help but exist
  • if the original (human) authors of the AI code are themselves limited in their intelligence

• comment

  • this limitation is essentially what will result in AI progress traps
  • Indeed,
    • progress and their shadow artefacts,
    • progress traps,
    • is the proper framework to analyze the existential dilemma posed by AI

OEG Live: Audiobook Versions of OER Textbooks (and AI Implications)

Host: Alan Levine<br /> Panelists: Brian Barrick (LA Harbor College), Delmar Larsen, Brenna, Jonathan, Amanda Grey (KPU), Steel Wagstaff (Pressbooks).

Find out more information and discuss this topic on OEG Connect: https://oeg.pub/439V1Bc

writeout.ai

Recommended by Steel Wagstaff at OEG Live 2023-06-02.

Project Tailwind by Steven Johnson

This sounds like the sort of personalized AI tool I've been wishing for since the early ChatGPT models if not from even earlier dreams that predate that....

[29] AI - Deep Learning

[28] AI - precedents...

[25] AI - Alignment

[24] AI - Bias in Training Materials

[21] AI - Skills Erosion

[21] AI Nuances

[20] AI - Alignment Goals

[19] AI - Legal Response

[18] AI - Increased sophistication

https://bard.google.com/

https://thoughtful.sandbox.google.com/about

https://hamlet.andromedayelton.com/

• Given a thesis, find out which other theses are most conceptually similar.

Tagging and linking with AI (Napkin.one) by Nicole van der Hoeven

https://www.youtube.com/watch?v=p2E3gRXiLYY

Nicole underlines the value of a good user interface for traversing one's notes. She'd had issues with tagging things in Obsidian using their #tag functionality, but never with their [[WikiLink]] functionality. Something about the autotagging done by Napkin's artificial intelligence makes the process easier for her. Some of this may be down to how their user interface makes it easier/more intuitive as well as how it changes and presents related notes in succession.

Most interesting however is the visual presentation of notes and tags in conjunction with an outliner for taking one's notes and composing a draft using drag and drop.

Napkin as a visual layer over tooling like Obsidian, Logseq, et. al. would be a much more compelling choice for me in terms of taking my pre-existing data and doing something useful with it rather than just creating yet another digital copy of all my things (and potentially needing sync to keep them up to date).

What is Napkin doing with all of their user's data?

Abstract

Recent innovations in artificial intelligence (AI) are raising new questions about how copyright law principles such as authorship, infringement, and fair use will apply to content created or used by AI. So-called “generative AI” computer programs—such as Open AI’s DALL-E 2 and ChatGPT programs, Stability AI’s Stable Diffusion program, and Midjourney’s self-titled program—are able to generate new images, texts, and other content (or “outputs”) in response to a user’s textual prompts (or “inputs”). These generative AI programs are “trained” to generate such works partly by exposing them to large quantities of existing works such as writings, photos, paintings, and other artworks. This Legal Sidebar explores questions that courts and the U.S. Copyright Office have begun to confront regarding whether the outputs of generative AI programs are entitled to copyright protection as well as how training and using these programs might infringe copyrights in other works.

This isn't true. The Stochastic Parrots paper outlines other avenues for reining in the harms of language models like GPT's.

Luhmann attributes (an independent) life to his zettelkasten. It is effectuated by internal branching, opportunities for links or connections, and a register as well as lack of pre-planned comprehensive order, lack of hierarchy, and lack of linear structure.

Which of these is necessary for other types of "life"? Can any be removed? Compare with other systems.

¿inteligencia artificial cuando quien programa la información es el hombre? Que la hace artificial?

Bender, Emily M., Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜” In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–23. FAccT ’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3442188.3445922.

Would the argument here for stochastic parrots also potentially apply to or could it be abstracted to Markov monkeys?

A.I. Is Mastering Language. Should We Trust What It Says?<br /> by Steven Johnson, art by Nikita Iziev

Johnson does a good job of looking at the basic state of artificial intelligence and the history of large language models and specifically ChatGPT and asks some interesting ethical questions, but in a way which may not prompt any actual change.

When we write about technology and the benefits and wealth it might bring, do we do too much ethics washing to help paper over the problems to help bring the bad things too easily to pass?

Is language acquisition a very complex method of pattern recognition?

This is certainly "a way", but history has shown, particularly in the United States, that government regulation is unlikely to get involved at all until it's far too late, if at all. Typically they're only regulating not only after maturity, but only when massive failure may cause issues for the wealthy and then the "regulation" is to bail them out.

Suggesting this here is so pie-in-the sky that it only creates a false hope (hope washing?) for the powerless. Is this sort of hope washing a recurring part of

Who get's to make decisions?

A similar set of questions might be asked of our political system. At present, the oligopolic nature of our electoral system is heavily biasing our direction as a country.

We're heavily underrepresented on a huge number of axes.

How would we change our voting and representation systems to better represent us?

What features would be design society towards? Stability? Freedom? Wealth? Tolerance?

How might long term evolution work for societies that maximized for tolerance given Popper's paradox of tolerance?

Impromptu: Amplifying Our Humanity Through AI by Reid Hoffman

via Friends of the Link

Primary care physician Gavin Francis reviews two books on the importance of forgetting, as part of a larger reflection on memory.

Leveraging Social Annotation in the Age of AI : Hypothesis

Slides for this presentation: https://docs.google.com/presentation/d/1wOmZiAKWsXru1Uv7_nH5S3KDCYHtdBiZYb1_ab58yeA/edit#slide=id.g15258ea6415_0_78

Video<br /> https://www.youtube.com/watch?v=f5fqPirbb64

Annotation and AI Starter Assignments<br /> by Jeremy Dean

• students as fact-checkers
• students as content experts
• students as editors

see also: https://web.hypothes.is/annotation-and-ai-starter-assignments/

Not Skynet, but social disruption

https://openai.com/blog/chatgpt

Sam Matla talks about the collector's fallacy in a negative light, and for many/most, he might be right. But for some, collecting examples and evidence of particular things is crucially important. The key is to have some idea of what you're collecting and why.

Historians collecting small facts over time may seem this way, but out of their collection can emerge patterns which otherwise would never have been seen.

cf: Keith Thomas article

concrete examples of this to show the opposite?

Relationship to the idea of AI coming up with black box solutions via their own method of diffuse thinking

Despite the affordances of recording, searching, tagging made by computerized note taking systems, the problem still remains what to search for or collect and how to relate the smaller parts to the whole.

customer relationship management vs. personal knowledge management (or perhaps more important knowledge relationship management, the relationship between individual facts to the overall whole) suggested by autocomplete on "knowl..."

Can zettelkasten be used for other than positivitistic methodologies?

Description of Joseph Weizenbaum's ELIZA program

When rule-based artificial intelligence was the state-of-the-art.

https://www.cyberneticforests.com/ai-images

Critical Topics: AI Images is an undergraduate class delivered for Bradley University in Spring 2023. It is meant to provide an overview of the context of AI art making tools and connects media studies, new media art, and data ethics with current events and debates in AI and generative art. Students will learn to think critically about these tools by using them: understand what they are by making work that reflects the context and histories of the tools.

Sloan, Robin. “Author’s Note.” Experimental fiction. Wordcraft Writers Workshop, November 2022. https://wordcraft-writers-workshop.appspot.com/stories/robin-sloan.

brilliant!

How fitting that the amanuensis in a short story written with the help of artificial intelligence has done the opposite of what the author intended!

Wordcraft Writers Workshop by Andy Coenen - PAIR, Daphne Ippolito - Brain Research Ann Yuan - PAIR, Sehmon Burnam - Magenta

cross reference: ChatGPT

When does using an artificial intelligence-based writing tool make the writer an editor of the computer's output rather than the writer themself?

If I were going to use an AI, I'd want to plugin and give massive priority to my commonplace book and personal notes followed by the materials I've read, watched, and listened to secondarily.

Wordcraft's hallucinations can create interesting and creatively surreal suggestions.

How might one dial up or down the ability to hallucinate or create surrealism within an artificial intelligence used for thinking, writing, etc.?

Because one may need to spend an inordinate amount of time filtering through potentially bad suggestions of artificial intelligence, the time and energy spent keeping a commonplace book or zettelkasten may pay off magnificently in the long run.

Examples of artificial intelligence pushing toward pre-existing biases based on training data sets.

How to improve on this state of the art?

Eugenia Triantafyllou is talking about crutches for creativity and inspiration, but seems to miss the value of collecting interesting tidbits along the road of life that one can use later. Instead, the emphasis here becomes one of relying on an artificial intelligence doing it for you at the "hit of a button". If this is the case, then why not just let the artificial intelligence do all the work for you?

This is the area where the cultural loss of mnemonics used in orality or even the simple commonplace book will make us easier prey for (over-)reliance on technology.

Is serendipity really serendipity if it's programmed for you?

Again note the reference to magic with respect to the artificial intelligence: "the ability to conjure ideas 'out of thin air'".

Just as using a text for writing generative annotations (having a conversation with a text) is a useful exercise for writers and thinkers, creative writers can stand to have similar textual creativity prompts.

Compare Wordcraft affordances with tools like Nabokov's card index (zettelkasten) method, Twyla Tharp's boxes, MadLibs, cadavre exquis, et al.

The key is to have some sort of creativity catalyst so that one isn't working in a vacuum or facing the dreaded blank page.

The engineers behind Wordcraft refer to it "as a 'magic text editor'". This is a cop-out for many versus a more concrete description of what is actually happening under the hood of the machine.

It's also similar, thought subtly different to the idea of the "magic of note taking" by which writers are taking about ideas of emergent creativity and combinatorial creativity which occur in that space.

Is LaMDA really able to "learn higher-level concepts" or is it just a large, straight-forward information theoretic-based prediction engine?

https://pair.withgoogle.com/

People + AI Research (PAIR) is a multidisciplinary team at Google that explores the human side of AI by doing fundamental research, building tools, creating design frameworks, and working with diverse communities.

Ippolito, Daphne, Ann Yuan, Andy Coenen, and Sehmon Burnam. “Creative Writing with an AI-Powered Writing Assistant: Perspectives from Professional Writers.” arXiv, November 9, 2022. https://doi.org/10.48550/arXiv.2211.05030.

See also: https://wordcraft-writers-workshop.appspot.com/learn

A Google project entering the public as ChatGPT was released and becoming popular.

For additional experiences, see: https://www.robinsloan.com/newsletters/authors-note/

Author's note by Robin Sloan<br /> November 2022

PolitiFact - People are using coded language to avoid social media moderation. Is it working?<br /> by Kayla Steinberg<br /> November 4, 2021

http://www.wisdomofchopra.com/...

A random generator using Deepak Chopra tweets.

Reminiscent of https://hypothes.is/a/bzlr9l06Ee23w7voPzbY5g

A Luhmann web article from 2001-06-30!

Berzbach, Frank. “Künstliche Intelligenz aus Holz.” Online magazine. Magazin für junge Forschung, June 30, 2001. https://sciencegarden.net/kunstliche-intelligenz-aus-holz/.

Interesting to see the stark contrast in zettelkasten method here in an article about Luhmann versus the discussions within the blogosphere, social media, and other online spaces circa 2018-2022.

ᔥ[[Daniel Lüdecke]] in Arbeiten mit (elektronischen) Zettelkästen at 2013-08-30 (accessed:: 2023-02-10 06:15:58)

https://docs.google.com/document/d/1E8b-aY6R-CUMgXe0UTCsdyHWHDatBa1DaQBvdcuA_Kk/edit

AI in Education Resource Directory

<small><cite class='h-cite via'>ᔥ <span class='p-author h-card'>Hypothesis</span> in Liquid Margins 38: The rise of ChatGPT and how to work with and around it : Hypothesis (<time class='dt-published'>02/09/2023 16:11:54</time>)</cite></small>

https://docs.google.com/document/d/1WpCeTyiWCPQ9MNCsFeKMDQLSTsg1oKfNIH6MzoSFXqQ/preview<br /> Policies related to ChatGPT and other AI Tools

<small><cite class='h-cite via'>ᔥ <span class='p-author h-card'>Hypothesis</span> in Liquid Margins 38: The rise of ChatGPT and how to work with and around it : Hypothesis (<time class='dt-published'>02/09/2023 16:11:54</time>)</cite></small>

Foundation Models in AI

Large language models, more generally, are “foundation models”. They got the large-language name because that is where they were first applied.