We are surprised when witnessing something move faster than our intuition expects. We are inherently wired to understand slow, compounding growth. We expect the long, grinding years of the plateau—the quiet periods where nothing seems to happen before a sudden breakthrough.
I was looking at a chart Patrick Collison shared this morning, and it challenged that very intuition. It’s a simple, stark visualization: AI model intelligence relative to the formation date of the lab that built it.
If you trace the lines for Google and OpenAI on the right side of the graph, you see the history we’ve all lived through. Thousands of days—more than a decade of quiet, methodical, often unglamorous research—before their trend lines finally bend and shoot upward. It is a geometry of patience. It’s the visual representation of laying bricks, one by one, year by year, until you have a foundation sturdy enough to support the weight of a revolution.
And then, on the far left of the chart, there is a red line. MSL. The team behind Meta’s new Muse Spark model, released today.
The red line doesn’t curve. It doesn’t slope. It simply strikes straight up, like a lightning bolt in reverse.
In roughly 200 days since formation, this new effort achieved a level of capability that took the early pioneers thousands of days to reach. Collison noted how much he loves seeing things done quickly, and it’s hard not to share that specific, visceral thrill of seeing the boundaries pushed so aggressively.
I find myself thinking about the architecture of speed and what it means for the rest of us.
We spend so much of our lives absorbing the lesson that “good things take time.” We are taught that the crucible of meaningful work requires a long, slow simmer. And mostly, that remains true. The compound interest of human experience is real, and wisdom is rarely rushed.
Yet, every once in a while, a new paradigm emerges that doesn’t just accelerate the timeline—it collapses it entirely.
The pioneers cut the agonizingly slow path through the jungle, taking the brunt of the time, the friction, and the missteps. The ones who follow—like xAI, Anthropic, and now MSL—don’t have to clear the brush from scratch. They can look at the map, pave the road, and simply drive.
What does it mean for our own mental models when the timeline from “formation” to “frontier” shrinks from five thousand days to a few hundred?
It is a jarring reminder that the past pace of performance is not a law of physics.
I think about my own assumptions—how often I assume a project, a habit, or a societal shift will take a while, simply because similar things took a while in the past. We anchor our expectations to old geometry.
Meta’s release of Muse Spark is a technical feat, certainly. But the chart itself holds a broader, more human lesson. It’s a visual prompt to constantly re-evaluate our assumptions about how long the impossible is supposed to take.
The future doesn’t always arrive on a comfortable, predictable schedule. Sometimes, it just shows up unannounced, demanding we adjust our stride to keep up.
