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A team of scientists says they've built a quantum computer that generates a superposition of several possible futures the computer could experience.
The research, published Tuesday in Nature Communications, describes how this quantum system could help futuristic artificial intelligence learn much faster than it can today - and it could mean quantum computers are finally becoming practical tools.
Right now, artificial intelligence learns by analyzing example after example and looking for patterns. The scientists behind this research argue that their quantum superpositions could vastly improve the process.
"By interfering these superpositions with each other, we can completely avoid looking at each possible future individually," Griffith researcher Farzad Ghafari said in the press release.
"In fact, many current artificial intelligence algorithms learn by seeing how small changes in their behaviour can lead to different future outcomes, so our techniques may enable quantum enhanced AIs to learn the effect of their actions much more efficiently."
Simulations of stochastic processes play an important role in the quantitative sciences, enabling the characterisation of complex systems. Recent work has established a quantum advantage in stochastic simulation, leading to quantum devices that execute a simulation using less memory than possible by classical means. To realise this advantage it is essential that the memory register remains coherent, and coherently interacts with the processor, allowing the simulator to operate over many time steps. Here we report a multi-time-step experimental simulation of a stochastic process using less memory than the classical limit. A key feature of the photonic quantum information processor is that it creates a quantum superposition of all possible future trajectories that the system can evolve into. This superposition allows us to introduce, and demonstrate, the idea of comparing statistical futures of two classical processes via quantum interference. We demonstrate interference of two 16-dimensional quantum states, representing statistical futures of our process, with a visibility of 0.96 ± 0.02.
Our multi-step photonic implementation of a stochastic simulation has verified the memory advantage available with quantum resources. We have demonstrated that it is possible to maintain this advantage at all stages of the simulation by preserving quantum coherence, as opposed to previous experiments8,36. Further, we have shown that superpositions of process outcomes can be interfered. These techniques have the potential to reduce memory requirements in simulations of stochastic processes and to provide tools for advances in quantum machine learning and communication complexity.
The comparison of future statistics has direct relation to other protocols, such as quantum fingerprinting and state comparison in communication complexity. Fingerprinting involves estimating the distance between two vectors, where the resource to be minimised is the amount of communication. For the comparison of two vectors, quantum mechanics can reduce the amount of communication required beyond classical limits. In the quantum protocol, Alice and Bob perform a SWAP test—a quantum information primitive, which compares two arbitrary states. Two-photon interference is known to be equivalent to a SWAP test. Our comparison of futures can be cast as a similar problem. In this case, the task would be for Alice and Bob, who each have their future statistics from potentially different processes, to compare the two statistical futures34. In principle, for very high-dimensional Hilbert spaces, a comparison of statistical futures via two-photon interference can achieve a quantum advantage in communication complexity. The comparison of two vectors is also an important component of many machine learning tasks, and thus a similar advantage could extend to more general settings like speech recognition.
originally posted by: neoholographic
a reply to: bobs_uruncle
You can't say quantum this or that and get published in Nature Communications. You can't be serious. Of course Scientist will mention Quantum Mechanics, it's one of the most powerful scientific theories we have.
It makes no sense to hear a Scientist talking about Quantum Mechanics in a paper published in Nature Communications and call it crap without reading it because you see the word quantum. That's just asinine
originally posted by: BrianFlanders
This actually doesn't sound like a big deal because even if a computer can emulate human thought and then amplify that, it is still based on something that had the end goal of emulating a flawed mind. Humans are often wrong about what's going to happen in the next few seconds. So let's say that a computer can do the same thing for the next 10 years that a human can do for the next ten seconds, it would probably still be wrong most of the time unless the probable outcome was so obvious that you shouldn't even need a computer to guess anyway.
The new AI tool has been developed to offer doctors a better guide to how best treat a specific patient. The machine learning algorithm was trained on 10 years' worth of CT scan and tissue sample data from 364 women. Four tumor characteristics were evaluated retrospectively by the system: structure, shape, size and genetic makeup. The system was then able to give each patient a disease severity rating called a Radiomic Prognostic Vector (RPV).