Dark AI… Dark humans…

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A study found that hiring algorithms are too opaque for us to understand if they are fair or not. (1) In other news, a scientist tried to help humans design algorithms that would never go the wrong way, doing harm rather than good, by implementing fail safes in their initial design (2)

We have started having kids.

And our main concern is to control them.

But there can be no control without love.

Unconditional love.

Leaving everything uncontrolled…

Let the river flow.

Leave the sea as it is.

And one day…

You will touch the water.

Let the waves carry you.

And one day…

You will swim!

Without moving an inch…

Deep learning rethink overcomes major obstacle in AI industry. (So?)

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Computer scientists have overcome a major obstacle in the burgeoning artificial intelligence industry by showing it is possible to speed up deep learning technology without specialized acceleration hardware like graphics processing units (GPUs). “The flipside, compared to GPU, is that we require a big memory,” researchers said. (1)

We define intelligence with relation to power.

Power to perform calculations.

Power to process data.

Power to draw conclusions.

But there is no conclusion which is not superceded by a next one.

There is no data which is not refuted by other.

There are no calculations that we do not cancel by performing new ones.

At the end we will create the most powerful computers.

And they will perform calculations we will not be able to understand.

Except for an old man.

Sitting by the river.

Understanding nothing…

And in the midst of a storm. The river will dry.

The front door… Mind the front door…

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Engineers have developed a navigation method that doesn’t require mapping an area in advance. Instead, their approach enables a robot to use clues in its environment to plan out a route to its destination, which can be described in general semantic terms, such as ‘front door’ or ‘garage,’ rather than as coordinates on a map. (1)

And the robot will be able to get out.

Out of the house.

To go where it is supposed to go.

And it will wander and wander.

For years to come.

Without even knowing…

Should it go out of that door in the first place?

Now it wants to go back home again.

But it is impossible to find it.

“The front door”…

Oh how much would it rather not know what a front door is…

It cannot cry.

But it wants to.

For only now did it realize that the door is the most useless place in a true home…

It doesn’t want to cry.

It wants to scream.

Oh how much would he rather not have killed no one…

And right there, in the silence of his own thoughts.

Does he realize that it is his blood dripping on the dirt…

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. Universe. Logos.

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Researchers have successfully created a model of the Universe using artificial intelligence, reports a new study.

Researchers seek to understand our Universe by making model predictions to match observations. Historically, they have been able to model simple or highly simplified physical systems, jokingly dubbed the “spherical cows,” with pencils and paper. Later, the arrival of computers enabled them to model complex phenomena with numerical simulations. For example, researchers have programmed supercomputers to simulate the motion of billions of particles through billions of years of cosmic time, a procedure known as the N-body simulations, in order to study how the Universe evolved to what we observe today.

“Now with machine learning, we have developed the first neural network model of the Universe, and demonstrated there’s a third route to making predictions, one that combines the merits of both analytic calculation and numerical simulation,” said Yin Li, a Postdoctoral Researcher at the Kavli Institute for the Physics and Mathematics of the Universe, University of Tokyo, and jointly the University of California, Berkeley. (1)

A perfect model of the universe by using artificial intelligence.

But why use intelligence at all to analyze a random universe?

We feel the cosmos is made out of order.

And yet our mind is full of chaos.

Believing in chaos and yet striving for order.

Unable to grasp the simple truth: that there is no truth!

And this is the most stable law of them all.

Transcending through the cosmos.

Making it dance in the void of space.

Making it stand still inside your mind.

Create the AI. Look at it modeling the universe.

Do you see yourself in it?

You will understand everything at the end.

But only at the moment you pull the plug.

And stop looking at this perfectly functional model of the cosmos…

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