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Yearly Archives: 2023
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Privacy, Copyright, and Intellectual Property
In our discussions, we went down a rabbit hole about the “commodification of inspiration,” that “worthless” (no commercial value) human-written fan fiction is okay, but published/sold (high commercial value) LLM-created content from copyrighted training data is not okay. While theoretically, it could be possible to track this transference of value – if you can quantify […]
Bias and Toxicity In Large Language Models (LLMs) and Machine Learning
WK 3 – 9/18: Bias and Toxicity The discussion on bias and toxicity (and setting safety rules by either human agency or secondary machine monitoring/constitutional AI) made me want to raise my p(doom) value based on three possibilities: 1.) Unintended human errors (programming mistakes in setting up rules).2.) Intended human errors (bad actors ignoring ethics […]
Labs for DATA 78000: Large Language Models and Chat GPT
Mondays 6:30p, Room 5417, CUNY Graduate Center, New York, NYInstructor: Michelle McSweeney, michelleamcsweeney.com Course Site: https://github.com/michellejm/LLMs-fall-23 Link to this post: https://tinyurl.com/46ykcr68 Prompt Engineering Lab – Stanton for 78000https://colab.research.google.com/drive/1qWsqeooxflEDoIw5kaTOu3iv7A2aC9zd Ngrams Lab – Stantonhttps://colab.research.google.com/drive/1HebbqSpe5WXT45j9Oh1y7vOfHk6RO_nw Word Vectors Lab – Stantonhttps://colab.research.google.com/drive/1B2Qy5AzfZEp_wF34yW4Z8S82lF6LtFbT Tokeninzation Lab – Stanton for 78000https://colab.research.google.com/drive/1YXfrKuSNtG1HuWTiQ_-Qh87ru276Bwuu BERT Sentiment Via Huggingface – Stanton for 78000https://colab.research.google.com/drive/1OXrTaE6Ot5CCdpjjIKnl5jE4Rp5CD9W5 Fine Tune LLaMa – […]
PROJECT III: WHITE PAPER
DOWNLOAD PDF VERSION: http://chimaboo.com/coursework/DATA73000/STANTON-WHITEPAPERDATA73000.pdf “FROM ATOP TABLEAU, I CAN ALMOST SEE WHERE Y’ALL FROM” FINAL PROJECT WHITE PAPER FOR DATA 73000: INTRODUCTION TO DATA VISUALIZATION WRITER: Matthew Stanton ([email protected]), May 2023 SUMMARY “So… Where Ya From? How New Yorkers Identify Their Roots” was inspired by previous work on measuring the educational cost of NYC’s “stop-and-frisk” […]
PROJECT III: Welcome to New York City… SO, WHERE YA FROM?
View on Tableau Public
PROJECT III: Welcome to New York City… So, Where Ya From? (Pin-up Draft)
New York is the “crossroads of the world,” but among today’s residents, where did everyone come from? Or rather, how do they identify their roots when asked about their “ancestry,” either as newly arrived immigrants, first gen natives, or Gotham’s Old Guard of past generations? And, whether from far-off lands or just over the bridge-and-tunnel […]
PROJECT II: Just How Much Dungeons & Dragons Have I Run In 40 Years?
For more than four decades, I have organized games of Dungeons & Dragons, the famous fantasy role-playing game invented in 1974 near my southeastern Wisconsin birthplace. I began as a 12-year-old “Dungeon Master” for my neighborhood friends, and just two years later, I was writing and running adventures at Gen Con, the biggest D&D convention […]
PROJECT II: Initial Draft Concept
For more than four decades, I have played and organized games of Dungeons & Dragons, the famous fantasy role-playing game invented in 1974 near my southeastern Wisconsin birthplace. I began as a 12-year-old “Dungeon Master” for my neighborhood friends, and just two years later, I was writing and running adventures at Gen Con, the biggest […]
PROJECT II: Qualified Self-Visualization and Blog Post (Proposal)
Proposal sketch in response to https://introductiontodatavisualization.commons.gc.cuny.edu/blogpost-2-guidelines/ Research question: What is the most popular mix of Dungeons & Dragons characters should I have available when I host public pick-up games in bars across New York City? For years I used to organize open games of D&D at venues across Manhattan and Brooklyn – game stores, bars, […]
Lab 5: Population Visualizations
Sample data per the exercise… View this Tableau embed here. Another way to look at the sample data… View this Tableau embed here. Something not in the exercise, just seeing what it looks like… View this Tableau embed here.
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