I've said previously that we are in the age of the last mover. What this means is that:

Any result that can be produced by an algorithm will become:

• Free to produce

• Instantaneous to produce

• Geographically independent, i.e. you will be able to produce the result anywhere

This is obviously not the case yet. There is still a lot of paid software out there. But it's starting to happen. I believe the most advanced piece of software known to man is ChatGPT. ChatGPT is free to use. Another Large Language Model (LLM), GPT4All goes ever further. It is a free-to-use privately hosted LLM. You can download, use, and own your own model for life.

During our entire school careers, we are reinventing the wheel. We are repeating things that other people have figured out. A miniscule subset of what we do entails novelty. Essays and the art we make in kindergarten fall into this small category.

This is also true for our undergraduate education. When we learn and apply Newton's laws, we are repeating something discovered 300 years ago.

When we start working, however, we are told not to reinvent the wheel.

The opening scene of the movie "The Hobbit" is an excellent metaphor for what its like having kids. Initially, Bilbo Baggins is living a very comfortable life, with "all the comforts of home". Then, suddenly, seven dwarfs invite themselves into his home, and his life is never the same again. I believe whether his life is better or worse depends on how you respond to infinite experiences.

Georg Cantor, a 19th century mathematician, was driven insane by contemplating the mathematical theory of infinity. It seems we find it excruciating to fit infinity into our finite minds.

I sometimes feel a tinge of insanity when contemplating open-source business models.

Yesterday, as I made my way home after a highly productive day at work, I found myself waiting impatiently at a traffic light. I was impatient because I knew something awkward and unpleasant was about to happen.

We all enjoy winning.

In the good old days, you wanted to beat your nearest competitor. Today, I get the same kick from beating a robot.

On most mornings I drop my kids off at kindergarten on my way to the office. While securing my rapidly maturing one-year-old into his recently acquired car seat, I was looking forward to starting the work week with a bang. I didn't have any urgent admin to do. I could give myself over to creative work I enjoyed. It was a blissful start to the morning.

Suppose we became masterfully proficient at producing robots. One day, after years of development, we finally create a robot that can replicate itself. It can create all the required microchips. It can fashion steel members from garbage, and it can write the required software. This is the point where robots cease to be something we're willing to pay for. We'll only pay for things that can't be produced at zero cost, like food.

When considering which kinds of results can be produced by algorithms, we first need to think about which kinds of results there are. The most obvious place to start is often the best:

1) Non-Physical results. Text, images, sound recordings, risk mitigation, love, hate, belonging, excitement, dignity

2) Physical results. Cars, food, spaceships, watches, computers

Adding an untrue detail to a story seems dishonest. We certainly don't tolerate politicians or newspapers when they are caught doing this. But have you ever been in a conversation where the other party recounts an exciting and interesting event from the past and, at the end, both parties find the story disappointing. The disclosing party sighs and says: "Actually, you had to be there".

The second law of thermodynamics states that entropy, another term for chaos, gradually increases in a closed system. The most compelling proof of this is observed when you unleash bored kids into a tidy room.

At the risk of sounding like a heretic, please let me explain.

The scientific method demands a meticulous approach, where one must declare your assumptions, collect impartial evidence, and consciously endeavor to eliminate your prejudices from the inquiry. If your theory holds up throughout this rigorous process, then you can draw conclusions.