MIT Generative AI Certification
Context:
This is an assignment I did for an MIT Professional Studies course I took with Nestor Gandara, Principal Partner of Gen AI Management at Amazon. The course gave us the opportunity to explore tools like LangChain, Chat GPT, and Amazon AI. I chose this early assignment for my portfolio because I think it demonstrates some of the most important skills a researcher can have: curiosity and the ability to distill complex ideas toward a meaningful outcome.
Hey Chat GPT… what’s a neural network?
I asked Chat GPT to explain neural networks to me. It explained that a neural network is like a “massive spreadsheet” with each value representing the weight of an input. Like a massive spreadsheet, the output of the neural network can be anything. Some of the examples given include:
-Computer vision
-Language
-Healthcare
-Finance
-Entertainment
Like the human brain, a neural network transforms a dataset into something usable.
A neural network is useful in an autonomous car that takes information from cameras, and lidar, to keep you from bumping into things on the way to work. It’s useful to create a work of art, aggregated from every existing works of art.
As an apprentice to a famous pop artist, I learned a famous Picasso quote, “that good artists copy, and great artists steal.”
Steve Jobs openly admitted he stole the idea for the Macintosh computer from Xerox Parc!
This was precisely the way the master goes about creating a painting. They transform inputs, in our case: drawers of news clippings and shelves of books, into new works of art. This is what we mean, when we say a neural network works just like an human brain.
Even when humans produce it, Art doesn’t come from the ether. There have been ethical breaches by human artists as well, notably Shepherd Fairey’s Obama portrait: Hope. Dutch masters, once believed to paint the world with an indescribable photorealism, turn out to have used elaborate projection techniques.
Vermeer used a camera obscura. Artists today use Chat GPT!
“Nick, I liked how you took a technical concept like neural networks and made it accessible by comparing it to a "massive spreadsheet" that transforms inputs into outputs that's exactly the kind of analogy that helps demystify AI. Your connection between how neural networks work and how human artists create was especially powerful, and bringing in your own experience as an apprentice to a pop artist made it feel personal and authentic. The Picasso quote and the Steve Jobs example were perfect illustrations of how transformation and "borrowing" have always been part of innovation and creativity. Excellent work!”
-Nestor Gandara