Evolution allows life to explore almost limitless diversity and complexity. Scientists hope to recreate such open-endedness in the laboratory or in computer simulations, but even sophisticated computational techniques like machine learning and artificial intelligence can’t provide the open-ended tinkering associated with evolution. Here, common barriers to open-endedness in computation and biology were compared, to see how the two realms might inform each other, and ultimately enable machine learning to design and create open-ended evolvable systems. (1)

Looking for an end.

By accepting that there is none.

How could there be one?

The end is defined by the beginning.

And this definition is also the end.

One can never pass through the walls he raised.

Achilles will never reach the turtle.

Mathematicians will never prove everything.

Humans will never find the meaning of life.

Unless they stop looking for meaning.

Unless mathematicians stop trying to prove things.

Unless Achilles stops trying to pass the turtle and just runs.

No, there is no end. There are just beginnings…

Be careful with that first step…

No, it is not just a first step.

It is also your last…