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But there is no conclusion which is not superceded by a next one.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

Limits of measurements… Limits of out self…

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The limits of classical measurements of mechanical motion have been pushed beyond expectations in recent years. But the sensitivity that we can achieve using purely conventional means is limited. For example, Heisenberg’s uncertainty principle in quantum mechanics implies the presence of “measurement backaction”: the exact knowledge of the location of a particle invariably destroys any knowledge of its momentum, and thus of predicting any of its future locations.

Backaction-evading techniques are designed specifically to ‘sidestep’ Heisenberg’s uncertainty principle by carefully controlling what information is gained and what isn’t in a measurement, e.g. by measuring only the amplitude of an oscillator and ignoring its phase. In principle, such methods have unlimited sensitivity but at the cost of learning half of the available information.

Now, in an effort to improve the sensitivity of such measurements, the lab of Tobias Kippenberg at EPFL, working with scientists at the University of Cambridge and IBM Research — Zurich, have discovered novel dynamics that place unexpected constraints on the achievable sensitivity. Published in Physical Review X, the work shows that tiny deviations in the optical frequency together with deviations in the mechanical frequency, can have grave results — even in the absence of extraneous effects — as the mechanical oscillations begin to amplify out of control, mimicking the physics of what is called a “degenerate parametric oscillator.” (1)

The problem of measurement. An unsolvable problem. And yet, within our mania to understand everything we have missed that every unsolvable problem points only to the obvious: that the problem itself is wrong!

Trying to measure things. In a cosmos which cannot be measured.

Trying to observe things. In a cosmos not meant to be observed.

Trying to understand. In a cosmos which was never meant to be understood.

Destroyers of the world.

Trying to push through a veil we ourselves have set up.

We are the cosmos.

There is no cosmos.

Trying to understand our self. Without accepting our self.

Can’t you see?

There is no need to learn how to swim.

You are already deep in the water…

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…

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…

Attributing art. Understanding art. Making art?!

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AI used to analyze and attribute art. (1)

Computers analyzing art.

Categorizing it. Attributing it.

Computers understanding art.

Computers destroying art.

Only because they understood it.

While it is not meant to be understood.

But can’t you see?

This means that they didn’t understand it after all!

Weird cosmos.

Full of people. Full of computers.

Humans creating art.

Computers understanding it!

How nonsensical.

How dull.

How awfully… artistic!

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