A team of scientists has revealed they successfully built a quantum computer that can generate a superposition of all possible futures. It’s something like in the 2018 Avengers: Infinity War Movie, when Dr. Strange looks at 14 million possible futures searching for one where the superheroes are victorious against Thanos.
“When we think about the future, we are confronted by a vast array of possibilities,” explains Mile Gu, Assistant Professor of NTU Singapore, who led the creation of the quantum algorithm that underpins the prototype.
“These possibilities grow exponentially as we go deeper into the future. For instance, even if we have only two possibilities to choose from each minute, in less than half an hour there are 14 million possible futures. In less than a day, the number exceeds the number of atoms in the universe.”
The new study, published in the journal Nature Communications explains how the new quantum device could help future AI (Artificial Intelligence) to obtain knowledge much faster than it does today. It also indicates that quantum computers could finally become practical tools we can use.
The quantum device, built by Griffith University and Nanyang Technological University scientists reportedly can hold two superpositions of 16 different possibilities.
Furthermore, scientists say that it also uses less memory than a classical computer would, which in turn means it could eventually outperform classical systems in a number of tasks.
Speaking about the recent achievement in a press release, Griffith University scientist Geoff Pryde said, “It is very much reminiscent of classical computers in the 1960s.
“Just as few could imagine the many uses of classical computers in the 1960s, we are still very much in the dark about what quantum computers can do,” he added.
Helping AI Learn
Right now, artificial intelligence learns new things after analyzing various examples and then looking for specific patterns. This is sort of a slow process. But scientists behind the new researchers believe that their quantum superpositions could greatly improve the process of AI learning.
“By interfering these superpositions with each other, we can completely avoid looking at each possible future individually,” Griffith researcher Farzad Ghafari explained in the press release.
“The functioning of this device is inspired by the Nobel Laureate Richard Feynman,” says Dr. Jayne Thompson, a member of the Singapore team.
“When Feynman started studying quantum physics, he realized that when a particle travels from point A to point B, it does not necessarily follow a single path. Instead, it simultaneously transverses all possible paths connecting the points. Our work extends this phenomenon and harnesses it for modeling statistical futures.”