Chaos. Numbers. Simulations.

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Digital computers use numbers based on flawed representations of real numbers, which may lead to inaccuracies when simulating the motion of molecules, weather systems and fluids, find scientists.

The study, published today in Advanced Theory and Simulations, shows that digital computers cannot reliably reproduce the behaviour of ‘chaotic systems’ which are widespread. This fundamental limitation could have implications for high performance computation (HPC) and for applications of machine learning to HPC.

Professor Peter Coveney, Director of the UCL Centre for Computational Science and study co-author, said: “Our work shows that the behaviour of the chaotic dynamical systems is richer than any digital computer can capture. Chaos is more commonplace than many people may realise and even for very simple chaotic systems, numbers used by digital computers can lead to errors that are not obvious but can have a big impact. Ultimately, computers can’t simulate everything.”

The team investigated the impact of using floating-point arithmetic — a method standardised by the IEEE and used since the 1950s to approximate real numbers on digital computers.

Digital computers use only rational numbers, ones that can be expressed as fractions. Moreover the denominator of these fractions must be a power of two, such as 2, 4, 8, 16, etc. There are infinitely more real numbers that cannot be expressed this way. (https://www.sciencedaily.com/releases/2019/09/190923213314.htm)

An irrational universe.

Full of irrational people.

Trying to analyze it rationally.

Under the illusion that number we have invented can draw a sketch of the cosmos. And yet, nothing we have invented is anywhere to be seen but on a piece of paper. Can you limit the birth of a star on a piece of paper? Can you contain the death of the universe on an equation?

We believe we can.

And sadly, we do.

And at the moment we do, the universe indeed dies…

And a small voice will whisper in our ear…

Congratulations. You have now understood it all.

How irrationally rational everything is!

And inside the darkest night you will dance.

Laughter.

And for a brief moment the forest will look at you.

Crying.

And for a brief moment the forest will see nothing…

But an empty broken CD. Full of data. Full of life…

AI. Quantitative. Quantitative. Tautologies.

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Artificial Intelligence engineers should enlist ideas and expertise from a broad range of social science disciplines, including those embracing qualitative methods, in order to reduce the potential harm of their creations and to better serve society as a whole, a pair of researchers has concluded. (1)

Life is not about measuring. Life is not about counting.

Life is not about thinking. Life is not even about sensing.

Life is not about the quantitative.

Life is not about the qualitative either.

Life is about… living!

It sounds as a tautology and it is. But only tautologies can convey the most essential meaning of existence! Without dependencies. Without pre-requisites. Without conditions. Pure existence can only be defined by itself. Any other attempt to describe it is by default erroneous since it has lost contact with the thing which describes! (again, a tautology!)

Good men. Evil men. Clever men.

Only because someone sees evil men…

Only because someone sees good people…

Only because someone sees stupid people…

Full cosmos.

Only because it is void!

Specks of importance in an indifferent cosmos.

Feeling important for seeing the stars at night.

But everyone can do that…

Life is about… living!

Through the veil of the cosmos.

Beyond the shroud of Being.

In the midst of the day…

Close your eyes.

Can you feel the night burning inside?

AI imagining… Humans living…

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AI passes theory of mind test by imagining itself in another’s shoes. (1)

This is great. For the computer.

But we should test ourself.

Imagine you are a computer. But you can’t imagine how that can be, can you?

See? Forget about what you can do.

Focus on what you cannot.

These are the things that define you…

N-problems… Understanding nothing…

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Physicists are proposing a new model that could demonstrate the supremacy of quantum computers over classical supercomputers in solving optimization problems. They demonstrate that just a few quantum particles would be sufficient to solve the mathematically difficult N-queens problem in chess even for large chess boards. (1)

Solving problems with less.

Reaching at the end without leaving the beginning.

Dying before ever living.

That is the essence of life.

That there is no essence.

Look into the void. Rendering any problem meaningless.

Including life. The biggest problem of them all.

For in this perfect world you should know.

That everything which cannot be understood, should not…

Open-ending algorithms… The end as the beginning…

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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…

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