Explaining Quantum Computing

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One of my favorite tech podcasts is Hard Fork. Hosts Kevin Roose of the NYT and Casey Newton often try to understand new and emerging technologies. To do so, they bring on expert guests and pepper them with questions.

Last Friday, they discussed Google's announcement of a new "quantum chip" called Willow that seemed to have amazing power. To help understand this news, they brought on Julian Kelly, Director of Hardware at Google Quantum AI. Julian and the hosts did a good job of trying to explain one of the hardest concepts in tech.

Listen to the Episode

To me, the explanation problem lies in the nature of quantum mechanics, which operates at such a small scale that it appears to break the rules of what we expect. It's counter-intuitive. We don't have familiar concepts to say, "It's like that thing you learned in school." Even the scientists working on it don't claim to understand exactly what's happening, even though they can measure it precisely.

In preparation for the interview, Kevin Roose asked a chatbot to "explain quantum computing to an idiot". What he got back was an interesting analogy that uses a comparison to a normal computer:

In a regular computer, it's like flipping a coin that must land either heads or tails. Every "bit" that goes through a processor must be either one or zero. And this produces a sort of very clear and definite state. In a quantum computer is more like a coin that is spinning on a table, and while spinning, it's both heads and tails at once. These things are called qubits, and they can exist in multiple states simultaneously until you measure them.

This state of being both heads and tails at once is called superposition and it's one of the fundamental ideas.

Kelly points out that a quantum computer can solve new, different kinds of problems because it's a fundamentally different kind of computing:

Normal computers are ubiquitous in everything that we do, but they all operate the same way. So like an abacus, or a vacuum tube, or a transistor computer, the principles are the same. They're basic in classical computation, and that just fundamentally has limits. And so quantum computers will unlock the opportunity to solve problems that no other technology can solve.

Part of the problem with quantum computing is that the qubits are fragile. Google's new chip is an improvement because it makes the qubits less fragile, allowing them to scale more easily. This is called "error correction"

Once again, the hosts asked AI how to think about this idea:

It said, think of quantum computers like trying to conduct an orchestra where all the musicians are extremely caffeinated and jittery. The more musicians (or qubits) you add, the more chaos you typically get. Before Willow, adding more qubits was like adding more caffeinated musicians. It just made things messier. What Google did was figure out how to make the orchestra play better when you add more musicians.

Kelly added another analogy that relates to the threshold that quantum computing has to reach in order to improve versus becoming more chaotic:

Suppose you want to make a rocket and you wanna explore the universe, right? If you wanna do that, you have to go faster than what's known as "escape velocity" of the earth, right? Otherwise, if you don't, you're gonna come right back into the planet. But if you can achieve escape velocity, you actually can get out of the clutches of Earth's gravity and go explore wherever you want. And so it's another example of one of these thresholds you have to cross.

It's important to know that quantum computing is a field of research that will likely take years to produce products or solutions for everyday life.

The Lesson

Yes, quantum computing is exciting and confusing. But the lesson I learned from this interview is that most ideas can be learned by asking an AI chatbot to explain a subject "to an idiot." I do this all the time, and it's incredibly helpful. I say this as someone whose career is based on explanations.

Listen to the Episode