When I first started studying artificial intelligence in the early 2000s, my professors in natural language processing told us something very simple: one day, we’d be able to talk to our computers.

They estimated we’d start having basic interactions by 2015 and that, by 2025, we’d hold fluid, natural conversations. At the time, this felt distant. But in hindsight, the prediction was remarkably accurate: Google Assistant and Siri emerged around 2015, and ChatGPT completely shifted our relationship with machines in 2023.

This wasn’t magic. It wasn’t science fiction either. It was simply the logical result of looking at the right metric: computational power—more specifically, raw computing power viewed through the lens of cognitive science. By comparing the computational capacity of machines to that of living beings, it becomes possible to predict, with surprising accuracy, what kinds of cognitive tasks machines will be able to perform—and when.

As of 2025, the most powerful computers on Earth are roughly equivalent to a dog’s brain in terms of processing capacity. By 2030, they’ll be approaching primate level—and by 2035, they’ll reach the human brain. That doesn’t mean they’ll “think” like us. The programs they run are fundamentally different. But they’ll have the same raw capacity for processing, reasoning, and generation—and that changes everything.

Understanding this timeline helps explain why AI seems to be everywhere all of a sudden. These technologies aren’t just trendy. They’re the natural result of a long-term curve that’s now hitting a critical slope. When you adopt this cognitive and temporal perspective, everything starts to make sense.

Cognitive Thresholds: Why Progress Feels Sudden

What all of these breakthroughs have in common is the notion of cognitive thresholds. A technology can seem useless, clumsy, or experimental for years—until one day, it suddenly works brilliantly. That’s not a fluke. It’s a structural pattern. Once a system crosses a certain threshold of computing power or adopts a more efficient architecture, it flips from ineffective to impressive.

This is exactly what happened with ChatGPT, or with MidJourney in the creative space. One day, the model wasn’t usable. The next day, it was revolutionary. It’s not because something changed overnight, but because everything that had been slowly building up—data, models, hardware—finally had enough momentum to deliver.

And this pattern is accelerating. The higher the cognitive power, the faster the next leap comes. These inflection points—where a tool goes from irrelevant to indispensable—are going to happen more often, across more industries.

Tools That Will Reshape Everything

Today’s AI tools can already generate, analyze, optimize, and adapt with speed and precision beyond human reach. But this is just the beginning. With each leap in power, the tools become more transformative. They will not merely support human workflows—they will reshape them.

MidJourney disrupted the concept art profession almost overnight. Other breakthroughs are coming—in narrative design, gameplay balancing, automated coding, systems design, and beyond. And they won’t just be improvements. They’ll be ruptures in how we work, create, and think.

Putting the Timeline in Perspective

To put this into perspective: let’s take 2030 as a benchmark. That’s just enough time to ship:

  • 1 AAA production,
  • 2 AA games,
  • or 3 to 4 indie projects.

That’s all. A single production cycle—and by then, we’ll be at primate-level machine cognition. And five years later, at human-level capacity. These are not abstract milestones. They’re imminent. And they will redefine how we build, produce, and create.