🧠 Just 10 Minutes With AI Can Make You Give Up More Easily

AI makes us faster.

But what happens when we suddenly have to think without it?

A newly peer-reviewed study involving 1,222 participants suggests something uncomfortable: after just 10–15 minutes of AI-assisted problem-solving, people performed worse on their own — and were more likely to give up.

Researchers conducted three randomized experiments involving mathematics and reading comprehension. Some participants solved problems independently, while others had access to ChatGPT. Initially, the AI-assisted group performed better. But when researchers unexpectedly removed the chatbot, the advantage disappeared. In the first experiment, participants who had used AI correctly solved just 57% of subsequent problems, compared with 73% among those who had worked independently. They also skipped nearly twice as many questions: 20% versus 11%.

The researchers identified an especially interesting pattern. Participants who used AI primarily to obtain complete answers struggled more afterward than those who used it for hints or explanations. That comparison was observational, not a separate randomized experiment, but it suggests an important distinction: AI that helps you think may be very different from AI that thinks for you.

The possible explanation is a psychological shift. When answers arrive instantly, independent effort begins to feel unnecessarily difficult. Researchers call attention to the loss of productive struggle — the mental work through which we develop skills and persistence.

Important caveat: The experiments measured immediate effects during short online tasks. They do not establish permanent cognitive damage or show that regular AI use necessarily makes people less intelligent. Whether these effects persist over weeks or months remains unknown.

But the implication is fascinating.

We may be building machines that make us extraordinarily productive while quietly changing how willing we are to solve problems ourselves.

Perhaps the smartest AI assistant isn’t the one that always gives you the answer.

It’s the one that sometimes makes you figure it out.

Would you prefer an AI that solves everything instantly — or one that occasionally forces you to think?

#AI #ChatGPT #Psychology #Neuroscience #CognitiveScience #ArtificialIntelligence #Science

https://arxiv.org/abs/2604.04721

⚛️ Google Just Reduced a Critical Quantum Computing Error by 40 TIMES
Quantum computers have a fundamental problem.
They can potentially perform calculations beyond the reach of classical machines, but the quantum states they rely on are incredibly fragile.
Even tiny disturbances can introduce errors, making large-scale quantum calculations extremely difficult.
Now, researchers at Google Quantum AI have demonstrated a breakthrough that could help overcome one of the biggest obstacles.
They reduced errors in a critical quantum computing resource by approximately 40 times.
In a new study published in Science, researchers used Google's Willow quantum processor to demonstrate a technique called magic state cultivation.
Despite the name, there's nothing supernatural about it.
Magic states are specially prepared quantum states that enable certain operations essential for universal quantum computing.
Producing them reliably has been one of the field's biggest technical challenges.
The researchers developed a method to create these states, detect errors and discard unsuccessful attempts.
The result: quantum states with approximately 99.99% fidelity.
That means the prepared states matched their intended quantum states with extraordinarily high accuracy.
But the breakthrough goes beyond simply reducing errors.
The team also demonstrated that these refined states could be transferred between two different quantum error-correction systems — an important step toward integrating them into larger quantum computers.
And here's why this matters.
Some estimates suggest that producing reliable magic states could consume the overwhelming majority of a future fault-tolerant quantum computer's hardware resources.
Making their production more efficient could dramatically change the economics and engineering requirements of quantum computing.
Important caveat: The 40-fold improvement applies to the error rate of these particular quantum states, not the overall error rate or computing speed of Willow. Only about 8% of preparation attempts passed the researchers' strict checks. This is a hardware proof of principle, not a demonstration of a large-scale, fault-tolerant quantum computer.
Nevertheless, the implications are enormous.
Future quantum computers could help simulate complex molecules, discover new materials and investigate physical systems that conventional supercomputers struggle to model.
For decades, scientists have been trying to make quantum computers powerful enough to perform useful calculations.
Now they're getting better at making quantum information reliable enough to trust.
And that may prove just as important.
Could the biggest breakthrough in quantum computing turn out to be not more qubits — but fewer errors?
#Science #QuantumComputing #Physics #Google #QuantumPhysics #Technology #Innovation
https://doi.org/10.1126/science.aee7961