My Path to Learning Artificial Intelligence

By Cesar Zaldivar

Introduction to Artificial Intelligence

Carl Sagan once warned that when almost no one understands science and technology, we create “a combustible mixture of ignorance and power” — a prescription for disaster. That warning feels more urgent than ever in the age of artificial intelligence.

— Sagan, Carl. The Demon-Haunted World. Random House, 1995.

Artificial intelligence is no longer a distant concept from science fiction — it is the technology shaping how we work, create, and make decisions every day. This portfolio documents my month-long journey studying the history, theory, and practical applications of AI’s history and platforms at Houston Community College, tracing its roots from a single summer workshop at Dartmouth in 1956 to the large-scale models and real-time systems that define the field today.

Each page, feature, and module represents a different lens: historical context, hands-on experimentation, critical analysis, and creative application. Whether you are a fellow student, a curious visitor, or a future employer, I invite you to explore the work and the thinking behind it.

Cesar Zaldivar  |  ITAI 1370 — AI History, Theory & Platforms  |  Professor Maryam Esmali  |  May 2026

Portfolio Modules

Module 1: Trinity of AI

The three pillars that power every AI breakthrough: Data, Algorithms, and Compute.

View Page

Module 2: The Dartmouth Proposal

Where it all began — the 1956 summer workshop that gave AI its name.

View Project

Module 3: AlphaGo Zero

How a machine taught itself to play Go better than any human — with no human input.

View Project

Module 4: Raytracing & QR Codes

How light becomes art, and how a grid of squares changed the way we share information.

View Analysis

Module 5: GPT-3 & Visual Authenticity

175 billion parameters, few-shot learning, and the blurring line between real and generated.

Read Essay

Module 6: Exploring T5

One model. Every NLP task. Text in, text out.

View Project

Module 7: Neural Networks & Deep Traffic

Do ascending or descending neuron layers train better? The results were surprising.

View Analysis

Module 8: Are My Stories Real or Fake?

A speculative essay on the future directions of AI research and its potential impact on society.

Read Essay

Module 9: Computer Vision Classifier

Dogs labeled as faces, electrical parts as not — and a 100% accuracy score that taught a bigger lesson.

View Case Study

Module 10: IBM Watson Assistant

A powerful AI platform, a broken demo, and a lesson in why user experience matters.

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Module 11: Comparing AI Assistants

Siri searched. Rufus tried. Google Assistant had opinions.

View Exploration

Module 12: Understanding Predictive AI

AI isn't reading your mind — it's reading your patterns.

View Analysis

Reflections & Conclusion

From Dartmouth in 1956 to neural networks in 2026 — what a semester of AI history taught me.

View Summary

About Me

A brief introduction to who I am, my background, and my interests in AI and technology.

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