The Thinking Game: Because You Believe, You Begin to See

This piece comes from a conversation I recorded after watching the documentary The Thinking Game. It isn’t a technical analysis, nor an industry forecast. It’s simply what remained with me after being genuinely shaken by something — and taking the time to articulate those feelings carefully.

And if you’re not in the technology world, that’s completely fine. This isn’t written only for people who “understand AI.” It’s written for anyone who still takes the idea of belief seriously.

Before talking about the film itself, I feel it’s necessary to offer a bit of context. If you’re not closely following developments in artificial intelligence, it’s easy to underestimate what DeepMind represents — and what Demis Hassabis represents.

DeepMind was founded in 2010 by Demis Hassabis. From the very beginning, its goal was unusually clear. It wasn’t built to develop a specific application, nor to create a short-term profitable product. It was aimed directly at a question that, at the time, sounded almost audacious: is it possible to build artificial general intelligence?

Many of the milestones in AI that we casually reference today trace back to DeepMind. In 2016, AlphaGo defeated Lee Sedol, bringing the company into public consciousness. But AlphaGo itself was never the endpoint. What followed — AlphaGo Zero and AlphaZero — marked a methodological shift. These systems no longer relied on human game records. They learned from scratch, through self-play and self-improvement. That transition was profound.

Later, the same approach was extended into far more complex environments, such as StarCraft II, testing machine learning in uncertain, multi-variable, long-horizon decision systems. And then came AlphaFold. AlphaFold addressed a problem that had challenged biology for decades: protein structure prediction. For this work, Demis Hassabis and the AlphaFold team were awarded the Nobel Prize in Chemistry in 2024. For the first time, an AI-centered method directly advanced fundamental science at that level.

Seen together, DeepMind was never simply “building products.” It was following a coherent path — from games, to complex systems, to scientific discovery — toward a form of intelligence that could ultimately reshape the trajectory of civilization.

Demis himself carries a certain narrative weight. A child chess prodigy. An early programmer at a game company. A founder who achieved financial success at a young age. There’s a detail often mentioned: before founding DeepMind, he turned down a million-dollar salary offer. Not because he didn’t need money, but because it wasn’t what he truly wanted to pursue. What he wanted to work on was something that, if not attempted now, might never be attempted at all.

In 2014, DeepMind was acquired by Google. Later, Google Brain and DeepMind merged into what is now Google DeepMind — a research organization of nearly 6,000 people. The name Gemini, meaning “twins,” reflects that convergence: Google’s engineering strength combined with DeepMind’s research depth.

Understanding this background changes how you watch The Thinking Game. The film isn’t about a “successful company,” nor about a “genius founder.” It’s about choosing a very long time horizon — and holding onto it.

When I finished the documentary, I felt one thing very strongly: awe.

Of course, it tells the story of DeepMind and Demis Hassabis. But more than that, it captures a group of people who, very early on, decided to take seriously the possibility of building general artificial intelligence. They didn’t pivot toward it because it became fashionable. They began there.

Watching it, a sentence came back to me: because you believe, you begin to see.

DeepMind believed in something long before there was consensus, long before there were clear signals. They weren’t reacting to a trend. They were committing to a direction.

And that realization made me somewhat ashamed.

It reminded me of myself around 2016, after AlphaGo. I remember attending events where people began discussing artificial general intelligence. At that time, I honestly had no real understanding of what AGI meant. But what embarrasses me now isn’t that I didn’t understand. It’s that when I heard others discuss it, my instinct wasn’t curiosity. It was skepticism tinged with dismissal. I would think: what is this person trying to prove? Are they just showing off? Are they trying to sound sophisticated?

Looking back, that mindset feels uncomfortable. Ignorance itself isn’t the problem. Ignorance combined with arrogance is. That subtle contempt was simply a defense mechanism for not understanding. The documentary confronted me with that truth. Sometimes it isn’t that others are overreaching. It’s that I wasn’t standing high enough to see what they saw.

There was another moment in the film that gave new shape to an old phrase. Archimedes famously said, “Give me a place to stand, and I will move the earth.” We often hear that line as a metaphor for conviction. But watching DeepMind’s journey, it suddenly felt concrete.

Think about their path. Beginning with reinforcement learning in games, moving gradually toward more general forms of intelligence. If that trajectory truly succeeds, what changes isn’t just a product or an industry. It alters the way knowledge is generated. It shifts the foundation of scientific progress. In that sense, isn’t this precisely a lever? You apply force in a seemingly narrow domain, and the impact radiates outward in ways that are almost unimaginable.

For the first time, that ancient sentence had an image attached to it.

Another strong feeling I had while watching was this: under certain conditions, business can be beautiful.

What I saw in DeepMind was a group of extraordinarily intelligent people working with surprising simplicity of intention. There was little of the maneuvering and calculation we often associate with commerce. They were oriented toward a goal that felt both humble and vast at the same time. In fact, the goal itself wasn’t primarily commercial.

There’s a detail mentioned in the documentary: when DeepMind agreed to be acquired by Google, they requested that their technology not be used for military purposes. You can see it in their expressions — the sense that if a company is sufficiently aligned with its founding purpose, it can preserve something idealistic even as it scales.

It reminded me of the early days of Google — that youthful, almost idealistic image of what a company could be. Watching DeepMind today, integrated into Google’s broader system, yet still pursuing work that may influence the future of science and civilization, I felt that same echo.

All of us, I think, carry some version of a dream. It may be small — serving a community well. It may be larger — shaping an industry. Or larger still — nudging the arc of civilization in some direction. The scale matters less than the sincerity. If you can remain focused on what you genuinely believe in, without being distorted by excessive calculation, and if you can find joy in the act of creation itself, that is already meaningful.

That is why I strongly recommend watching The Thinking Game. Not for the technical detail, but for the quiet question it leaves behind.

Is there something you believe in — something you once took seriously — that you have not yet dared to treat as real?

Sometimes, you see because you believe.