Monthly Archives: November 2024
Transfigurations on Musings
Hello, my friends. If you, like me, have ever gazed into the cosmos of thought and marveled at the boundless intersections of science, technology, and human understanding, then you’re in for a journey. Today, we embark on a thoughtful exploration inspired by the writings of Jennifer L. Adams—a thinker deeply entrenched in the realm of higher education, where technology and learning converge like celestial bodies in orbit. Her central question is both provocative and profound: Is artificial intelligence truly that different from how our own minds work?
Such a question beckons us to consider the intricate dance of memory, intelligence, and pattern recognition, and to marvel at their manifestations both natural and artificial. Adams begins her inquiry not in a laboratory or lecture hall, but in a bathtub—a setting both humble and evocative, echoing Archimedes himself. She watches whirlpools form and dissipate, contemplating the microscopic life swirling in these temporary eddies. Her curiosity takes her to a surprising discovery: slime mold.
Ah, slime mold—a single-celled organism seemingly so simple, yet capable of navigating mazes and anticipating environmental changes. Imagine: a creature with no brain, no nervous system, no neurons, yet it remembers. Its memory, Adams suggests, may be chemical, a fundamental organization of matter with purpose. It is here, in this primal intelligence, that we are invited to see echoes of artificial intelligence.
Adams draws a parallel to large language models (LLMs), like GPT-4. These models, too, operate without consciousness, yet they predict patterns and generate responses so human-like that they often blur the line between machine and mind. Consider this: when tasked with responding to a zoo worker’s query, the AI adapts, contextualizes, and personalizes its response. It mirrors the dynamic complexity of thought, much as the slime mold mirrors memory.
But Adams doesn’t stop at algorithms. She speculates on the broader implications of intelligence—animal, artificial, and human. She recounts the intricate songs of whales, passed down through generations, a kind of aquatic epic encoded in soundwaves. Could their communication represent an organic language model, evolved naturally and independently of human cognition? What might these songs tell us about their history, their emotions, their view of the universe?
This thought invites an even deeper question: if intelligence emerges in myriad forms—from the chemical traces of slime molds to the silicon networks of AI—what truly defines intelligence? Is it memory? Pattern recognition? Adaptability? Or something ineffable, like the capacity for wonder or the ability to ask questions about existence itself?
Adams provocatively ties this inquiry back to the classroom, to the very essence of learning. Imagine a world where AI personalizes education for every learner, a virtual tutor attuned to the unique pathways of each student’s mind. Yet here, she invokes a cautionary principle: the Prime Directive from Star Trek, a reminder that with great power comes great responsibility. How do we harness AI to amplify human potential without losing what makes learning an inherently human endeavor?
The bathtub becomes a metaphor for our role in this vast experiment. As Adams muses about pulling the plug, ending the microcosmic swirl of life, we are reminded of the fragility of discovery, the delicacy of choice. How we engage with AI, how we integrate it into education, and how we define its role in our society will shape not only our future but our very understanding of intelligence itself.
So, as we stare into the starry vastness of possibility, let us ponder: What if AI is not merely a tool, but a mirror? A mirror reflecting our own creativity, our capacity for connection, our endless curiosity? And in that reflection, perhaps we might better understand ourselves—not as isolated beings, but as part of a vast and intricate cosmos, forever learning, forever exploring.
Stay curious, my friends. The universe awaits.
Musings from the Bath
There is a bit of fiction within the Star Trek universe, that really made an impact of me. It is tied into the prime directive:
This is a directive that is often dismissed in the heat of an episode (particularly by Captain Kirk)… but in one movie, Star Trek II: The Wrath of Khan, it shows up as a crew of a science vessel is having a damn hard time finding a planet that has absolutely zero life on it. This concept, when we live in world view where people wonder if life exists anywhere else at all in the universe, was extremely captivating to me.
So I sat in the bath this morning, and watched as tiny and fleeting whirling vortexes formed when i lower my arms quickly into the water. I wondered if there was microscopic life in the water that has been doing it’s thing in this newly created body of water – maybe organizing, reproducing, eating – that had just been swirled into a chaotic storm. I wondered, if this microscopic stuff, might have thought something like “what the?” as everything was displaced around it. Which made me think of language.
I asked Alexa (yes I have an device in my bathroom – one with a nice speaker of course): What is the most primitive life form that we know has a memory. I asked this, because I thought that proving one has memory, proves some organization of thought – at least to me. I’ll accept arguments of course.
So the answer is slime mold; which to be honest is a much more primitive life form than I was expecting the answer to be. Turns out that these single-celled organisms can remember their way through mazes, and anticipate changes in temperature and light if they happen in a pattern. They do not have brains or even a nervous system. Other tiny primitive organisms that show memory include bacterias, ciliates and other more complicated, yet distinctly un “animal” like, plants and fungi.
So, AIs are using what is called a Large Language Model to appear intelligent. These break down vast amounts of training data to analyze what tiny bit of language is the most likely bit to come next. For example, if I write:
Hello, how are
Just as your phones some predictive text so you don’t have to text as many letter – you can see the most likely word could be
you?
If you are told that the person speaking is a 35 year old person who works at the zoo taking care of parrots and they are speaking to there coworker as they change shifts (changing the query) you might still guess
you?
or you might think
the parrots?
Of course, GPT 4o is a blabber mouth by default so when I ask it to finish the sentence
Hello, how are
It says
you doing today? I hope you’re having a great day! 😊
When I give it the query that I mentioned about, with the speaker being a parrot caregiver at the zoo, it responds:
you? I hope your shift went smoothly—any updates or things I should know about the parrots today?
Demonstrating its politeness and verbosity.
Anyway, back to my bath, I am scrubbing up, thinking about whether I think, therefore, I am – only because I have a runaway LLM running inside of my head. Blah blah blahing at me – and I have a chemical system that remembers things. I remember myself blabbing. I remember conclusions I have come to. I remember patterns. I remember grudges and fondnesses. (sometimes I can’t quite remember why I like or dislike someone – but I know I do. Similarly, I might not remember what happens in a book, but I can tell you if I really liked it. This will come in handy for retirement rereads.)
I remember me.
“If You Think You Can Hold a Grudge, Consider the Crow” New York Times Article.
[side note – did you know you can read the NYTimes as a person with an .edu email address?]
Do Animals who use sounds to communicate use a small or midsized language model? To be sure, a chemical one. As we as humans may be using a chemical LLM?
Did you hear about the whales yet?
I’m going somewhere with all of this.
I promise. But I won’t be finishing these thoughts in today’s blog.
Maybe my LLM can interact with your LLM and we can make some new ideas together?
Oh – and to tie things up a bit. If I had never drained my bath, would something eventually have crawled out of it, wondered about the planet and started a new civilization? We will never know, because similar to what Captain Kirk may have done, I pulled out the drain when I was finished.
Oh – and definitely check out the NotebookLM podcast generated based on this post.
“It’s like AI is making us look in the mirror”
More reason to think about how we use the internet
I was asking GPT about a trip to the Grand Canyon as a part of a demonstration today, and I didn’t read what it actually responded at the time. I was just closing open tabs in my browser, and I read a bit of it before closing the tab and after the usual travel tips like use flexible travel dates, consider alternative airports, take budget airlines… the last one really got my attention:
“Clear your cookies: Some airlines and flight comparison websites use cookies to track your browsing history and raise prices if they see that you’re interested in a particular route. Clearing your cookies can help you avoid this price hike.”
I knew that my interest in a particular destination was noted – as my browser will become crowded with ads about the place I was investigating, but it never occured to me that the would start offering me higher costs just because it knows I want to go there.
That is like knowing that a car that is approaching your gas station is runing on no gas, and raising the cost just before you coast into the station.
Quick GIT instructions (but I recommend using GIT Desktop – cause I like GUIs)
title image – mostly decorative
Mini Lecture: Using Git and GitHub in the Terminal for Windows, Linux, and macOS
1. Initial Setup
- Install Git: Ensure Git is installed.
- Windows: Download from git-scm.com and follow the installer.
- Linux: Run
sudo apt install git(Debian/Ubuntu) orsudo dnf install git(Fedora). - macOS: Use
brew install gitif Homebrew is installed or download directly from git-scm.com.
- Configure Git: Set your global username and email:
git config --global user.name "Your Name" git config --global user.email "your.email@example.com" - Set Up Authentication with SSH:
- Generate an SSH Key:
ssh-keygen -t rsa -b 4096 -C "your.email@example.com"Follow the prompts and press Enter to accept the default file location.
- Add the SSH Key to the SSH Agent:
eval $(ssh-agent -s) ssh-add ~/.ssh/id_rsa - Add Your SSH Key to GitHub:
- Copy the public key to your clipboard:
cat ~/.ssh/id_rsa.pub | pbcopy # Use 'xclip' or manual copy on Linux - Go to GitHub SSH settings and add a new SSH key.
- Copy the public key to your clipboard:
- Test the Connection:
ssh -T git@github.com
- Generate an SSH Key:
2. Cloning a Repository
To work on an existing project, clone the repository:
# Replace with your repository URL
git clone https://github.com/username/repository.gitOr, if using SSH:
git clone git@github.com:username/repository.gitNavigate into the project directory:
cd repository3. Basic Git Workflow
- Check the status of your repository:
git status - Stage changes (add files to the staging area):
git add . # Stages all modified files git add filename.ext # Stages a specific file - Commit changes with a message:
git commit -m "Your commit message" - Push changes to GitHub:
git push origin main # Replace 'main' with the appropriate branch name
4. Creating a New Repository
- Initialize a new repository:
git init - Connect to a remote GitHub repository:
git remote add origin https://github.com/username/new-repository.gitOr, if using SSH:
git remote add origin git@github.com:username/new-repository.git - Add and commit your initial project files:
git add . git commit -m "Initial commit" - Push to GitHub:
git branch -M main # Ensure the branch is named 'main' git push -u origin main
5. Branching and Merging
- Create a new branch:
git checkout -b new-branch - Switch between branches:
git checkout main - Merge a branch into your current branch:
git merge new-branch
6. Handling Merge Conflicts
If you encounter merge conflicts:
- Git will mark conflicts in your files. Open the files in a text editor and manually resolve the conflicts.
- Once resolved, stage the changes:
git add resolved-file.ext - Commit the merge:
git commit -m "Resolved merge conflict"
7. Pulling Updates
To keep your local repository up-to-date with the remote:
git pull origin main # Replace 'main' with your branch name8. Additional Useful Commands
- View commit history:
git log - Undo the last commit (without losing changes):
git reset --soft HEAD~1 - Remove files from the staging area:
git reset filename.ext
Summary
This mini lecture has outlined essential commands for using Git and GitHub across Windows, Linux, and macOS. Remember to commit often, write meaningful commit messages, and stay consistent with Git best practices.
concluding slide image – mostly decorative that restates text