I am a data scientist, fiddle player, and flute maker from Bala Cynwyd, Pennsylvania. My passion for interdisciplinary and practical studies has lead me from Artificial Intelligence research in 2002 at CU Boulder, to biology, to K-12 science and language teaching, and back to AI Data Science. I completed the Data Science program at The Bloom Institute of Technology in 2020.
I am interested in interdisciplinary projects that span best practice and organizational management, education and human development, economics and finance, health and healthcare, consciousness, law, visual arts, poetry, botany, economic-botany, linguistics, statistics, language comprehension, writing systems, international studies, mythology, history, traditional music, astronomy, cooking, baking, pickling, woodworking, mindfulness, Shakespeare, Lean Six Sigma, Philosophy of Science, literature, digital security, poetry, agile & scrum project management, asteroid mining, quantum information theory, folk dancing, astrobiology, etc. Practical applications of data abound.
March 2023: Object Relationship Space Framework For AI Design, Analysis, Performance, Architecture, and Operating Systems
January 2020: Medicine and Symptom Recommendation Machine Learning
March 2020: Center for Advanced Defense Studies Sanctions Explorer
April 2020: Emulator of LS8 CPU in Python
April 2020: Efficient Blind Traversal of Graph(Data Structure)
April 2020: Basic Blockchain Structure From Scratch in Python
August 2020: Minimal Text Adventure Game for Teaching Data Science
Sept 2020: Guide: Minimal Flask Endpoints for Data_Science
Dec 2019: Basic Perceptron Neural Network in Python from Scratch
December 2023: Image Analogies and Relationships: Word and Image
November 2023: Feedback on Language Meaning
November 2023: Technology, Biology, and AI Goals
November 2023: Ants vs AI
October 2023: Jellyfish Spider-Crab AI: Modular Architectural Learning
October 2023: Biology, Psychology, Math: AI broad or AI Narrow
Sept 2023: Calculating Tea for AI: Advocating for Architectural Learning
Sept 2023: Modeling Participant Architectural Learning in Five Trees Plus Mindstate
Sept 2023: The Vortex: Gender and AI’s Scylla and Charybdis
Sept 2023: AI ALU Corpus Callosum
Sept 2023: Architectural Learning, Developmental-Landscape Hypervolumes, & Empirical Task-Trees: Participation With AI
Sept 2023: Subroutine Stacking Measure: AI Learning & General Project Participation
August 2023: AI Rules: Falstaff, Computer Science, and Natural Law
August 2023: Modularizing Problem Space for AI: Following a Wedge by Sight
August 2023: Questions as Objects in AI Object Handling
August 2023: Interpreting Hofstadter’s Gap: AI, Music, Math, Language
August 2023: AI Bodies & Brains: Solving A Problem
August 2023: Language, Analysis, Society, Compassion: AI, Biology, & Types of Intelligence
June 2023: Integrating STEM and Ethics for AI Alignment / Goal Alignment
May 2023: Scientific Method and Data Science Models
May 2023: AI Generalization’s Types & Testability
April 2023: Our AI Ancestors: Dumbledore’s Portrait and Ray Kurzweil’s Father
April 2023: Human-AI Interactions Study: World Chess Championships
April 2023: AI In A General Learning Gauntlet
April 2023: AGI’s Culture Tools
April 2023: Better Tools To Plan AI
February 2020: Explaining Basic NLP for Recommendation Systems
October 2019: Less Is More: Explaining The Future - Using Only The Past
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