AI models like ChatGPT or Siri don’t actually understand your questions.
Instead, they’re trained to predict what words should come next — like supercharged autocomplete. They’ve read tons of data from books, websites, and conversations, and when you talk to them, they just guess what a smart answer should look like.
They’re not thinking. They’re guessing — very convincingly.
One of the most fascinating things about AI is how it can sound incredibly intelligent. It can explain complex topics, hold conversations, and even crack jokes.
But here’s the secret: it’s not doing any of that with real understanding.
It’s using something called a language model trained on enormous amounts of text. It finds patterns in words and phrases and uses those patterns to build answers that look smart.
There’s usually no awareness, no learning from experience, and no common sense. Just math and probability.
Apple’s researchers gave AI models a series of logic puzzles, word problems, and tricky questions.
Here’s what happened:
It’s like a student who memorized answers without learning the subject — impressive until you change the format.
Not exactly. Today’s AI is very good at mimicking intelligence.
It can sound brilliant, helpful, and confident, but there is a difference between sounding smart and actually being smart.
Real thinking means breaking down a problem, understanding it, and reasoning through it — something that AI still struggles with.
To put it simply: AI can talk like Einstein, but thinks like autocomplete.
This illusion can be dangerous.
If we assume AI understands everything it says, we risk placing too much trust in it — using it for medical advice, relying on it for legal decisions, or expecting it to solve issues beyond its capability.
That’s why Apple’s research is so important — it reminds us to tread carefully before handing over the responsibility of critical decisions to a machine that’s probably just guessing.
Imagine asking an AI:
What’s 27 × 19?
It might give you the right answer.
But ask it to explain how it got there — and it often can’t.
Worse, if you change the numbers slightly, it might totally fail.
This shows how it's not actually doing the math — it's just repeating what looks like a correct pattern from its training data.
A solid way to know if the AI is just doing guesswork is to see if:
Ask insightful follow-up questions like:
Until AI can handle these convincingly, we should treat it as a tool, not a genius.
Apple’s research isn’t saying AI is useless.
It’s definitely powerful, resourceful, and getting better with time.
But it’s crucial to be aware of its limits.
We’re not at the point where AI can truly reason, plan, or think like humans.
Right now, it’s more like an extremely helpful assistant with a good memory — not a deep thinker.
Understanding this helps us use AI better — and keeps us from over trusting it.
AI might sound smart, but don’t be fooled by the performance.
Just because it talks like a thinker doesn’t mean it’s doing any thinking.
Things will evolve and improve — but for now, it’s important to know the risks and limitations.
If you're curious about how AI works under the hood, here are some friendly starting points:
And keep reading!
AI is changing fast, and there’s always something new to discover.