It’s the sort of thought you only have when you let your brain float—part curiosity, part absurdity—the kind of pondering Douglas Adams might have described as “perfectly normal behavior for a species that invented both the digital watch and Vogon poetry.”

Where We Are with LLMs

If you’ve used ChatGPT, Claude, or Gemini, you’ve encountered what’s called a large language model (LLM). Imagine a system that’s read more text than you and I could in ten lifetimes, and then uses that knowledge to predict the next word, sentence, or idea in a way that sounds remarkably human.

They don’t think like we do. But they’re very good at producing the appearance of thought. Ask them for a recipe, a joke, or a philosophical musing, and they’ll happily oblige.

What makes them powerful also makes them hungry: they require enormous amounts of computing power and electricity to train. We’re talking server farms the size of warehouses and energy bills that could run a small town.

Where We Are with Quantum

Quantum computers, on the other hand, are still more “prototype” than powerhouse. Instead of bits that are either 0 or 1, they use qubits—tiny systems that can be both 0 and 1 at once until observed.

That means a small number of qubits can represent staggering amounts of information. The problem is, they’re incredibly delicate. Qubits don’t like noise, heat, or even attention. They need environments colder than deep space to behave properly.

Right now, we have machines with a few hundred qubits, but only a fraction of those can be trusted after error correction. Think of them as promising but temperamental teenagers—not ready to run the world, but full of potential.

Where These Worlds Could Collide

Here’s where my hot tub daydream took me: what if we could combine these two?

LLMs are great, but they struggle with searching vast data sets, optimizing huge networks, and sampling from probability clouds that are too complex for traditional computers. Quantum algorithms might eventually help with exactly these tasks.

With only a few thousand reliable qubits, it’s possible to imagine an LLM that doesn’t just guess the next word—it reasons across probabilities in ways we can’t quite do today. Maybe it’s faster. Maybe it’s more efficient. Or maybe it’s just wonderfully strange.

The Big Picture

As I sat there with the trees above and the mountains in the distance, I realized:

• LLMs are the here and now—practical, noisy, sometimes brilliant, sometimes baffling.
• Quantum computers are the not yet—fascinating, fragile, and still trying to grow up.
• The idea of them working together is both exciting and absurd—exactly the kind of future Adams might have smiled about.

And perhaps, in true Hitchhiker’s Guide fashion, the best place to wonder about it all isn’t in a lab or a conference hall, but in a hot tub on a Saturday morning, pondering life, the universe, and everything.

Further Reading

If you’d like to dip into Douglas Adams’ own cosmic musings, here are a few of my favorite books:

• The Hitchhiker’s Guide to the Galaxy
• The Restaurant at the End of the Universe
• Life, the Universe and Everything
• So Long, and Thanks for All the Fish
• Mostly Harmless

(Affiliate disclosure: As an Amazon Associate I earn from qualifying purchases, at no extra cost to you.)

Some links in this post are affiliate links. If you buy through one, I may earn a small commission at no extra cost to you.