Quantum-computer-based AI is better at guessing than humans.

Statistics play a vital role in computer-based guessing. The system makes statistics about the probability of how often some cases are happening. And then, the system will use the statistics for making guesses. The reason why the computer wins over humans in guessing competition is that the computer has statistics about the most common cases. And then the computer must just answer by using the most common case.

The fact is that the regular, binary computer-based AI might also be better at guessing than humans. In those cases, the AI will not guess things like humans. The AI will use probability calculations and probability databases for making guesses.

"Scientists achieved a quantum speedup by effectively suppressing errors in a bitstring guessing game, managing strings up to 26 bits long. They showed that, with proper error control, quantum computers can execute full algorithms with better time-scaling than conventional computers, even in the current noisy era of quantum computing". (ScitechDaily.com/Quantum Speedup – Quantum Computers Are Better at Guessing)

If there is a known case. And all records about those cases are stored in databases like how many times the coin's heads and tails side is upward if we throw it the computer can use those kinds of databases to guess what is on upward heads or tails. There could be recorded the database about thousands of heads or tails cases, and then the computer can use that database for making probability-based guessing.

The probability-based guess is a simple thing. If the computer has a good database of the variables. The computer can collect that database by using things like traffic control cameras. And then it can calculate which way to turn is more popular to right or left. Statistics are the key element for mathematics-based guessing. The idea is that the computer finds the most common cases and then makes guesses by using statistics.

The AI is the ultimate tool. And AI-based systems can boost business architecture. The AI can collect databases about marketing courses or how people behave in certain situations. And that data is also suitable when the AI tries to predict: how people behave in risky situations.

If the AI can predict things. Like when the regular driver turns the car in a panic situation. That thing makes it possible to create more advanced and safer autopilots. The system can collect statistics which is the most common direction where a right-handed person turns the vehicle. The autopilot could help to predict the trajectory of the incoming vehicle and avoid destructive situations.

https://scitechdaily.com/quantum-speedup-quantum-computers-are-better-at-guessing/

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