All that is under the Sun
Imagine you are the most intelligent person in the world. You have read every book, seen every movie, and studied every equation up until the year 2023. But today, you wake up with a strange condition: anterograde amnesia. You can hold a conversation, you can reason brilliantly using your vast library of knowledge, but you …
Imagine you are a detective at the scene of a very peculiar crime. The victim? A once-vibrant houseplant, now droopy and sad. Your suspects? A cast of environmental characters: the amount of sunlight it received, the quantity of water it was given, the type of soil it’s planted in, and the music played in the …
The Art of Choosing One From Many: Categorical Cross-Entropy and the AI’s Grand Decision Imagine you’re a librarian training a new assistant. This isn’t just any library; it has 50,000 different sections. You hand the assistant a book and ask, “Where does this go?” The assistant, being new, doesn’t just point to one section. Instead, …
Imagine you’re teaching an archery student. They loose an arrow, and it thuds into the target, a little off-center. You wouldn’t just say, “You missed.” To be a good teacher, you need to know how much they missed by. Was it a near-perfect shot, just a hair’s breadth from the bullseye? Or did it land …
“Reality is that which, when you stop believing in it, doesn’t go away.” Philip K. Dick In the world of Large Language Models, the line between generated reality and objective reality can often feel perilously thin. We, the builders and researchers, stand at a fascinating and frustrating frontier. Our creations can draft elegant poetry, write …
Welcome back to All that is under the Sun! In our last blog post in Learning AI Series, we unmasked “Optimization,” the tireless engine that helps AI models strive for their “best selves.” We saw how AI isn’t just born brilliant; it learns and improves through a process of iterative refinement. But that begs a …