All that is under the Sun
Imagine you’re trying to teach a machine the difference between a cat and a dog. You show it a picture of a cat, and it says, with 90% confidence, “That’s a cat.” Great! Now you show it a dog, and it says, with 60% confidence, “That’s a cat.” Not so great. The second guess is …
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, your friendly guide through the fascinating, and sometimes bewildering, world of Artificial Intelligence. This month, we’re kicking off a brand-new series that gets to the very heart of how AI learns and improves. Think of it as the AI equivalent of a motivational seminar, a Marie …
“If probability is the language of uncertainty, a PMF is its grammar: crisp, discrete, and occasionally punch‑line worthy.” Picture this: You open your favorite generative‑AI app, type “Write me a haiku about mangoes,” and in less time than it takes to blink, a tiny digital poet complies. What sorcery decides which 17 syllables appear? Beneath …
We constantly hear about AI’s incredible feats: identifying cats in photos better than your cousin Kevin, translating languages on the fly, even spotting diseases on medical scans. AI models, especially those powered by Deep Learning, are phenomenal classifiers. They can look at data and yell “CAT!” or “SPAM!” or “POTENTIAL TUMOR!” with astonishing accuracy. But …