Is AI Really Thinking Or Just Guessing? Apple’s New Study May Surprise You
Artificial Intelligence sounds powerful. Ask a question and it gives you an answer, fast. But have you ever wondered if these tools actually think things through? Or are they just copying patterns?
Apple's research team did something big. They ran a profound study to figure out if AI models like Claude and DeepSeek really solve problems, or just make it look like they do. And what they found is important for every business owner using AI tools today.
Step-By-Step Thinking: Real Or Pretend?
Most modern AI tools are trained to act like they’re thinking step by step. These are called Large Reasoning Models, or LRMs. They don’t just spit out answers. They walk you through their “thought process” first. Sounds smart, right?
But here’s the catch: until now, no one checked if those steps made any sense. If the final answer looked good, people assumed the AI had reasoned it out.
Apple wasn’t satisfied with that. They wanted proof. So, they built a series of tricky puzzles that required clear logic. The kind of puzzles that show if a model is really solving a problem, or just guessing based on past examples.
The Tests That Made AI Sweat
Apple used four puzzle types:
Tower of Hanoi
This is a brain puzzle where you have to move a stack of discs from one peg to another. You can only move one disc at a time, and you can’t put a big disc on top of a smaller one. The more discs you add, the harder it gets. With just 3 discs, it’s pretty simple. With 10 discs, you need over 1,000 perfect moves.
Checkers Jumping
This is like playing checkers, but only focusing on jumping over pieces to reach the other side. The puzzle adds more pieces each time, which makes it harder to plan every move. The rule is simple: jump, jump, jump, but in the right order. The number of jumps needed grows fast as you add more checkers.
River Crossing
This puzzle starts with a small group of people and a tiny boat. The goal is to get everyone across the river safely. But there are rules, like only two people can fit in the boat at once, or some people can’t be left alone together. More people and a bigger boat complicate the puzzle. The steps stay logical, but the options multiply.
Blocks World
This puzzle uses toy blocks. The goal is to move them from one layout to another by following a set of instructions. For example, “Put Block A on Block B” or “Clear Block C before moving Block D.” At first, it’s easy. But as you add more blocks, the number of steps grows fast. One wrong move can mess up the whole puzzle.
Each puzzle starts simple. But with each added piece, the challenge gets much harder. These puzzles are perfect for testing step-by-step logic. To keep things fair, Apple used two versions of the same AI models:
One with reasoning steps turned on
One without
They also ran each puzzle 25 times to remove random luck. That’s how serious they were.
The Shocking Results
Here’s what Apple found:
Easy puzzles: The non-thinking models won. They gave fast answers without wasting time.
Medium puzzles: The reasoning models did better. But they needed more memory (called tokens) to work.
Hard puzzles: Everything broke. None of the models, even the “smart” ones, could finish the task. Not even with over 1,000 steps laid out for them.
Even worse? The harder the puzzle got, the less thinking the models did. They gave up before they started, even when they had enough memory to keep going.
This wasn’t just a one-time thing. It happened in puzzle after puzzle. In some tests, even when the model was handed the correct step-by-step answer, it still failed.
What Does This Mean For Your Business?
If you use AI to write emails, answer questions, or plan tasks, this study matters. It tells us that AI tools are great at repeating things they’ve seen before, but when asked to do something totally new or very complex, they struggle, and they might pretend to think, but really they’re just stitching together patterns from past data.
This doesn’t mean AI is useless. Far from it. It means you need to understand where AI is strong and where it’s not.
Apple’s Other Reveal: Real-Time AI Tools
While this profound study was going on, Apple also rolled out some new AI features at their developer event. Here are the two most useful ones:
Live Phone Call Translation: You can now talk to someone in another language and your phone will translate the call in real time. No internet needed.
Screenshot Summaries: Take a screenshot and send it to ChatGPT inside your phone’s photo app. It will summarize it for you instantly.
These tools are designed for everyday use, and they work well. But the super-smart assistant that can read your email and plan your day? That one is still in progress.
So... Is AI Really Smart?
It depends on what you ask it to do. AI tools are excellent at helping with tasks they’ve seen before, like writing marketing emails, answering FAQs, or summarizing documents. But when it comes to long puzzles, big math problems, or tasks that require hundreds of steps? They fall apart fast.
Some researchers say we can fix this with better training and more memory. Others say we’ve hit a wall and need a brand-new type of AI. Either way, this is your wake-up call. If you’re using AI in your business, treat it like a powerful helper, not a full decision-maker.
Final Thoughts
Apple’s study pulled back the curtain on how AI works. And the truth is: a lot of it is guesswork. So if you’re a business owner using AI to save time and money, great. Just know its limits. Don’t expect it to think like a human. At least, not yet.
