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The Comprehension Horizon

Artificial intelligence sometimes seems remarkably clever. Still, we shouldn't forget what AI does at its core.

It doesn't understand the world the way humans do. It processes vast amounts of data and calculates from it which answers are most likely to fit. Put simply: AI doesn't search for truth, it searches for patterns. It calculates what the most probable answer is based on the available data.

Learning

To make AI better, more and more data is fed in and the models are optimized. The AI model keeps adjusting until its answers contain fewer and fewer errors.

In research, this relationship is often shown by plotting a model's errors against the computing power applied. The more computation, the smaller the error. You can see this in the graph above as well.

The dashed line represents a kind of AI scaling law. It describes how, with more computing power, AI makes fewer errors, yet the number of errors never drops below the dashed line.

Understanding

AI can acquire an enormous amount of knowledge. If you know all the data and can think logically, you shouldn't really make any mistakes. That's why, to me, this dashed line is more than just a technical trend line. I see it as the comprehension horizon.

Our Customers Are Not Average

Patent Cockpit's customers don't work at the average. They stand at the frontline of their technologies. Often the whole point is to do something that isn't yet obvious, something that departs from existing knowledge. That requires a genuine understanding of the situation. This is exactly where innovation arises.

AI can support this work. It can help to search faster, structure better, and decide on a more solid basis. But it doesn't replace actual progress.

Because progress doesn't come from the average. Progress happens where people and companies go beyond what can already be calculated.

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