Quantum Computers and the Evolution of AI | IPWatchdog Unleashed

This week on IPWatchdog Unleashed, we have a conversation that I’ve wanted to have for some time. The topic this week is quantum computers. It is quite a niche topic and finding people who actually know what they’re talking about is not particularly easy, but this is an enormously important topic that we should all know something about because for Artificial Intelligence (AI) to achieve all its full potential, we are going to need much better and much faster computers. And whether it is ultimately quantum computing or whatever comes next, quantum computers are going to be at minimum a bridge to go from where we are right now to where most in the public already think we are in terms of AI sophistication.

This conversation was recorded as part of our annual AI program, which was held April 21-23 at IPWatchdog Studios. I was joined on stage in front of a studio audience by Robert Plotkin, the founder of BlueShift IP. Robert has also written for us at IPWatchdog.com, and he is also an author. His first book was Genie in the Machine was published in 2009, and dealt with computer automated innovation. Most recently his new book AI Armor which deals with securing intellectual property protection for AI innovations, was published in 2024. Also joining the conversation was Sarah Schlotter, who is an attorney with Wolf Greenfield in Boston. Sarah is a member of the firm’s Electrical & Computer Technologies practice group, and she holds a PhD in applied physics from Harvard University.  Both Robert and Sarah regularly represent clients with respect to AI innovations, and particularly with respect to quantum hardware and quantum software inventions.

What are Quantum Computers?

We begin our conversation with me asking Sarah if she could explain quantum computing to set a baseline for the audience to understand. Sarah explained:

You think of classical computing as being a discrete type of computing. You’re storing information in a bit, a zero or a one. And as you store more information, you linearly need more bits, and those bits don’t really talk to each other. You write them to a hard drive, they sit there, you’re done. A qubit or a quantum bit can have a continuous value between zero and one essentially, but you’re mapping to basically a vector state, so you can encode into a broader, a larger state and define your state that way. And instead of being a discrete value, it’s beholden to statistical quantum physics. And the interesting thing about qubits is that they don’t live in a vacuum. Well, they physically can be made in a vacuum hardware-wise, but they talk to each other. They can be entangled through quantum entanglement. And so, as you want to store more data, instead of scaling linearly, they scale exponentially. So, three qubits give you a lot more power than three just bits. And so, it’s really controlling how these qubits talk to each other that is the big trick of quantum computing.

To take the next step in our understanding of quantum comping, Robert chimed in to explain:

I would say a quantum computer is one that leverages the quantum properties of the qubits. Because you could say, well, a classical computer contains quantum properties within its electrons, but a classical computer doesn’t leverage those properties to perform computations. The software isn’t written to take advantage of the quantum properties, whereas in a quantum computer, the computer is designed to take advantage of entanglement and superposition. And the software is written based on the assumption that those properties are leveraged or exposed.

“A lot of what I work on is when you entangle states in these qubits, they’re not next to each other,” Sarah explained. “They’re in totally separate parts of the quantum computer but they’re talking to each other; their states depend on each other. And so it’s very sci-fi.”

What Sarah and Robert are beginning to explain at this point is one of the core mysteries of quantum mechanics, which says that a particle can exist in multiple states simultaneously and also be in multiple locations at once. This concept explains how two or more particles can be linked in such a way that they share the same condition or state regardless of distance, a phenomenon known as quantum entanglement, which Einstein referred to as “spooky action at a distance”, which is indeed very sci-fi.

Why are Quantum Computers Necessary for AI?

After this foundation was laid, we dial it back a little bit and talk about why is it that quantum computers are necessary for the evolution of AI. Why can’t ordinary computers do what we need to have done? What is the particular advantage of quantum computing versus classical computing power?

“A quantum computer, if it were big enough, could contain and process exponentially larger amounts of information with a given set of bits than a classical computer,” Robert explained. “So, the hope or the hypothesis is that we could get to a point where you could have a quantum computer that is large enough to process the same amount of information in exponentially a shorter amount of time or conversely exponentially larger amount of information. And from what you all know about where AI is heading, it’s all based on training models, based on massive amounts of information, often simulating large amounts of possible outcomes, performing optimization processes which involve just massive amounts of computation… So, the hope is that we get to a point where we could make use of these quantum properties to tackle those problems. But it is unknown, one, whether we will be able to do that and whether just existing supercomputers will be able to get good enough to do that perhaps at some point, perhaps with some combination of better algorithms.”

“Quantum combined with AI is still very much an open research question,” Sarah said. “And so, it’s what do you mean by better, right? Is it a quantum speedup? Is it using less power? Is it being able to solve a problem that a classical computer just physically cannot? In terms of speedup, I don’t think we’ve yet seen that. There’s some recent work that came out, I think from Honda Research, that they did image classifying with the same accuracy as a classical computer could do. I don’t know that if you’re going to do the same task that a classical computer can do that you need a quantum computer. So, it’s going to be finding the use cases that very specifically need quantum computers or where quantum computers can provide a really big, powerful speedup and save energy time. And I don’t know that the space has been sort of mapped fully.”

From here our conversation moves into specific use cases for quantum computers, and as we talk about specific use cases we pivot into obtaining patent protection for those use cases, how the United States Patent and Trademark Office is handling quantum computing related innovations, and whether patent examiners are issuing patent eligibility rejections for quantum software the same way that we have come to expect with classical software—spoiler alert, patent examiners are treating quantum software the same as classical software for eligibility purposes.

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