Last night, I accidentally offended one of the top minds in quantum computing.

I had scanned a few photos of his life's work (some very sophisticated quantum computing chips) and ran them through my MuseKat audio lens to simplify the concepts for an 8-year-old audience.

On the right, you'll see what Miko the Meerkat had to say about their quantum computing chip.

I shared this readout with one of the co-founders and lead technologists on the project and was immediately informed: "This is complete trash."

Nice.

I mean, obviously not the ideal response I was looking for. But one thing I like about super negative and direct feedback like that is that it's a great door opener. Because what I got to ask next was:

"Well, how might you explain the work that you do to an 8-year-old?"

What ensued was a 20-minute intense discussion full of deep tech language, lingo, and frameworks (many of which I've never been exposed to in a serious way before). I learned about three new terms that I've never really tried to understand on my own: superposition, entanglement, and interference.

I learned that the temperature that you store quantum chips matters a lot more than the temperature that you store classical chips, and I learned about some of what it takes to create a new chip, and the types of real-world, practical use cases that might make something like this a total game-changer.

In other words: The deliberately juvenile content remix was the perfect door-opener to ground my own learning.

When I learn something new, I'm finding are three things that are important for me to internalize in order to fully grok the new thing and commit it to memory. Those are:

Coming into this conversation about quantum computing, let's be perfectly real: I was batting zero on all three.

Since the subject matter was just about the furthest thing from my core competency areas (read: I haven't taken a math or science class since high school), I had no prior conceptual understanding of quantum mechanics. This made the learning curve hard from the start.

Furthermore, despite working in tech for 15 years, I don't get a lot of opportunities to interview serious deep tech scientists and researchers. As a result, I have little to no context about the practical applications and broader implications for this work.

Finally (largely due to my lack of conceptual and contextual knowledge), my brain just is not "fine tuned" with the terminology of how to ask the right questions to extract meaningful and relatable information.

This is why I’ve started thinking in terms of “learning lenses” – tiny frameworks that give me something to grab onto when the subject matter is flying way over my head.

What happened when I threw out the instant, 8-year-old description of quantum computing (by Miko the Meerkat) was that I completely disarmed the scientist in real time with a highly unusual entry point to a conversation.

The result (yes, after a healthy amount of judgment and annoyance on his part) was that his brain had to work harder to explain concepts in a new way to someone like me, and my brain had to work harder to try to find relatable things to keep the conversation going.

Let's be clear: This is what it feels like to push through any new hard thing and do get past that initial learning curve. But it's often not enough.

A really helpful thing that happened about 8 minutes into this discussion was that a friend of mine joined the discussion. She carries a background that comes from a much more specialized deep tech lens of viewing the world. I got a brief reprieve in my own interrogation by listening to her make real connections, in real time, asking both about practical applications and short clarifications to summarize her own understanding.

This bystander effect of learning is immensely helpful, both because I was able to observe how a more near-peer could relate to someone operating at a totally different level, and also benefit from her clarifications (and the future knowledge that she could "translate" her understanding back down to me over drinks later).

Typically, if you can't find a relatable anchor point with someone who operates at a completely different level of understanding and viewing the world, then you can't connect enough to draw out meaningful conversation.

For us, that anchor ended up being Schrödinger’s cat. When we were trying to unpack those three core ideas in quantum computing (superposition, entanglement, and interference), we kept coming back to this image of the cat in the box. Not because it solves anything, but because it holds something important: the idea that we can sit in a state of “both/and,” or even just “I don’t know yet.”

At one point, I decided to throw out a flier:

"Okay, so last year, my cat jumped off the roof, and I spent a whole night not knowing if she was alive or dead."

He looked at me like I was crazy. I continued.

"I didn't know if she was alive or dead but in that state of unknowing, I looked for other signals to help me infer and cross off some possibilities. For instance, I walked around the block for 'cat splats' on the sidewalk. But I didn't see any."

That's when he latched on a bit.

He acknowledged: "Well in that case there probably aren't an infinite amount of possibilities about what could have happened to your cat, but you can imagine quite a few."

"Right," I said. "She could have gone through a window. Gone to a neighbor's apartment. Gotten picked up by a hawk... So what you're saying is, that weird third space, with all the adjacent possibilities, that’s where the power lives? That’s what your chips are tapping into?”

"Something like that," he finally relented.

I decided to walk away from that conversation without telling him how things turned out for my cat.

No, I'm (still) not a quantum computing scientist. I never will be.

And yet.

After that single conversation (which, I'll admit, was layered with a lot more personal and professional discomfort than most people would likely tolerate), I replayed the conversation with my friend over drinks to help myself catch some of the important nuances that I'd missed.

Then I ran those three new terms into a new context window on ChatGPT this morning. My AI counterpart was able to help me talk through these at a more relatable level, on my own terms. This is something I would not have known how to do if I hadn't been thrown into the deep end of a highly complex technical conversation. Finally, I wrote this blog post, as a further way of processing my own learning and grounding my understanding.

All this thanks to my meerkat's so-called "trash" 8-year-old explanation of quantum computing. Miko may have missed the mark on the science, but she nailed her job as a learning spark. Sometimes, all you need a meerkat to break the ice with a quantum physicist.