If robots are ever going to start learning, thinking, and creating on their own, they're going to have to go quantum. And, well, in theory at least, quantum robots are being designed to become the worker of tomorrow.
Movies like Her and AI imagine a future where artificial intelligence is good enough for us to feel empathy for robots but, actually, the technology hasn't progressed at the same rate as, say, computing power.
Robots are still mostly designed to complete specific tasks and aren't learning from their past mistakes. But the coming quantum computing revolution will change everything, according to researchers from Madrid's Universidad Complutense.
"The unceasing setbacks in the general AI problem caused research to shift emphasis to the production of useful technology, a direction now called applied AI … and reduced from the holistic task of designing an autonomous and intelligent agent," Miguel Martin-Delgado and Giuseppe Paparo wrote in a recent study published in Physical Review X.
The increasing need for a labor workforce in technological manufacturing necessitates the design of true artificial intelligence
Quantum computing, they say, will change all of that, perhaps in as soon as a decade, and it'll lead to real artificial intelligence and smart, creative robots.
"We believe that a good figure of merit to expect the quantum technological revolution to take place is 10 years," Martin-Delgado told me in an email.
The team used quantum physics theory and modeling to suggest that, once they are readily available, quantum computers can be used to allow robots to remember situations they've encountered before in "classical environment"—that is, the real world, where things are constantly changing. The robots will then be able to react.
Under this scenario, robots will learn at a quadratic rate (that is, very fast, perhaps in real time) and be able to recall memories at that same speed.
"We employ the theory of a quantum random walk to show how an agent can explore its episodic memory in superposition to dramatically speed up its active learning time," Martin-Delgado said. "Utilizing quantum physics to promote artificial intelligence learning has the ability to provide a quadratic increase in speed in active learning, critical when the environment changes on timescales of the 'thinking' time of the robot."
In other words, your robot dog will be able to notice when your voice changes inflection or your eyebrows get all mean and remember that you hit it last time you did that (why are you an abusive robot dog owner?).
The quantum robot dog will run away, or bite you, or something, rather than just sitting there like this little guy:
That's a very, very rudimentary example of what the tech will be capable of, of course.
Martin-Delgado told me that at this point, it's "purely theoretical work," but says that it's based on the evolution of quantum computing itself, and on the evolution of artificial intelligence. Quantum computing, he said, wasn't really even a field of study until 1985, until physicist David Deutsch suggested such a thing could exist.
Similarly, Martin-Delgado thinks that his paper can help physicists and manufacturers define what, exactly, a quantum robot will do.
"[Deutsch's paper] was a great theoretical breakthrough that clarified many not-well-understood questions about what a quantum computer should be like," he said.
"This opened the way to discovering new quantum algorithms that outperform classical analogues and eventually, to the realization of small-scale experimental quantum computers with ion-traps, superconducting qubits, etc," he added. "Our work provides the structure of the architecture needed for a quantum robot."
Oh, and, by the way, these quantum robots are surely being designed to take your job. Martin-Delgado says it's looking like it might take only a decade for this sort of computing breakthrough, and he suggests that the technology is being driven by a need for cheap labor.
"The increasing need for a labor workforce in technological manufacturing necessitates the design of artificial intelligence that is capable of quickly responding to, and learning from, a variety of complex environmental stimuli," he said.