I had spent a large chunk of a Saturday evening trying to shape the letters G, Y, A, L, P, O and N into as many words as possible. But three hours, 141 points and 37 words — including “nonapology”, “lagoon” and “analogy” — later, I had hit a wall.
“It’s purely statistical,” Noah Giansiracusa, a professor of mathematical and data science at Bentley University told me. “It’s really about extracting patterns from data and then pushing out new data that largely fits those patterns.” The success of an AI model also depends on the data it’s trained on. This is why AI companies are feverishly striking deals with news publishers right now — the fresher the training data, the better the responses. Generative AI, for instance,better at the task than solving word puzzles. Giansiracusa points out that the glut of chess games available on the internet almost certainly are included in the training data for existing AI models.
My repeated attempts to get GPT-4o and Llama 3 to crack the Spelling Bee failed spectacularly. When I told ChatGPT thatinstead. When I mistyped the world “sure” as “sur” in my response to Meta AI’s offer to come up with more words, the chatbot told me that “sur” was, indeed, another word that can be formed with the letters G, Y, A, L, P, O and N.