The Insidious Truth Behind AI’s Illiteracy: They’re Not Stupid, They’re Just Not Designed to Understand
We’ve all seen the memes, we’ve all chuckled at the absurdity of AI systems like ChatGPT and Claude getting simple things wrong, like counting the number of "R"s in the word "strawberry". But behind the humor, a more sinister truth lies: these AI models are not stupid, they’re just not designed to understand the complexities of human language and cognition.
A Lack of Understanding, Not Intelligence
Transformer models, the basis for many language AI systems, operate on a different level of abstraction than human language. They’re not designed to process individual letters or syllables, but rather to identify patterns and relationships between abstract concepts. This is why they struggle to recognize words like "strawberry", which is a complex combination of phonemes and orthography.
And it’s not just language processing – image generators like Midjourney and DALL-E also suffer from a similar lack of understanding. They’re not designed to recognize individual fingers, let alone entire hands, but rather to identify patterns in pixels and colors. No wonder they produce images with fingers that look like they’re made of rubber.
The Problems Run Deep
The issue lies in the fundamental design of these AI models, which are built on the assumption that they can learn to recognize patterns and make predictions based on data. But this data is often incomplete, noisy, and biased, leading to incorrect conclusions and hilariously bad memes.
And don’t even get us started on the "tokenization" process, where words are broken down into abstract units that are then fed into the model. It’s like trying to understand human language by counting the number of individual neurons in the brain. Yeah, good luck with that.
The Future of AI: A Battle for Understanding
The debate is on: can AI systems be designed to understand the complexities of human language and cognition? Or will they forever be stuck in the realm of abstract patterns and relationships? The stakes are high, and the consequences are dire. If we continue to design AI systems that are incapable of understanding, we’ll be left with systems that are merely good at reproducing their own biases.
But if we can crack the code, if we can design AI systems that can truly understand the world, we’ll be opening up a whole new era of possibilities. Imagine AI systems that can reason, that can problem-solve, that can even create new ideas and concepts.
It’s a battle for understanding, and it’s one we can’t afford to lose.
