Blurry images…

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The ghost imaging technique forms an image by correlating a beam that interacts with the object and a reference beam that does not. Individually, the beams don’t carry any meaningful information about the object. The imaging technique works with visible light, x-rays and other parts of the electromagnetic spectrum and, when the structured light beams are generated computationally with spatial light modulators, can be performed with a low-cost single-pixel detector instead of a complex, expensive camera.

To apply ghost imaging to moving objects, the new method uses a small number of light patterns to capture the position and trajectory of the object. The researchers developed an algorithm to cross correlate this positional information with blurred images captured at different positions, allowing a clear image to be gradually formed. (1)

Looking at a blurry image.

Making it clearer with time.

The more you know, the more clear it gets.

But no matter how much we clear the initially blurry picture.

The fact will remain that when you first looked at it…

The picture WAS blurry…

And what is important is not that you saw it at the end.

But that you wanted to anyway see through it even though you saw nothing…

Do you get it now?

It is you who painted the picture.

Expert decisions…

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Does a mass on a mammogram indicate breast cancer? Will Serbia be a member of the EU by 2025? Will there be more floods in Germany in five years’ time? The diagnoses and predictions made by doctors, scientists, and experts often have far-reaching consequences. And in many cases, it is only years later that it is possible to say which expert made the right call most often.

An interdisciplinary research team from the Max Planck Institute for Human Development and the Leibniz Institute of Freshwater Ecology and Inland Fisheries has developed a simple new method that can be used to identify the best decision-makers from a group of experts without having to know whether their decisions — past or present — are correct or incorrect. “Providing that at least half of all decisions made within the group are correct — which is typically the case in expert groups — and that each person has made about 20 yes/no decisions, this method has proved to work very well,” says Max Wolf, researcher at the Leibniz Institute of Freshwater Ecology and Inland Fisheries and co-author of the study.

The method was developed on the basis of insights into collective intelligence. It rests on a simple assumption: Those individuals in a group of experts who make decisions that are most similar to the decisions of others also make the best decisions. For yes/no decisions, this assumption is easily confirmed by means of mathematical modeling. To test whether the method also works in real groups, the researchers analyzed published predictions and diagnoses made by various groups in different fields. (1)

Great method. Which also seems to work.

But should we trust it?

Be aware of the things which work.

Decisions of most people tend to be correct. But from when do “most of the people” reach the correct decision on any of the great philosophical questions? The truth is never revealed to the many. For even if that seems so now, at the end you will see that the path was wrong.

We strive for live.

We are afraid of death.

And yet…

What is life?

What is death?

Trust not the many but the one man standing aside the crowd silent.

It is there that you will find the truth screaming…

Knowledge. Destruction.

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Powerful DNA-sequencing techniques have spurred an avalanche of discoveries about ancient humans, but each one comes at a price: the partial destruction of the specimens from which the DNA was taken. Anthropologists Keolu Fox and John Hawks call for researchers to think harder about safeguarding. “Unless some ground rules are established, future scientists, armed with better, potentially less-invasive methods for extracting DNA from ancient samples could well look back on this era as a time of heedless destruction, fuelled by the relentless pressure to publish,” says Fox and Hawks. (1)

We should not be alarmed or surprised though.

Knowledge IS destruction.

Every time we understand something, we dissolve it into pieces.

Every time we get to know something, we forget something else.

The cosmos was once at our fingertips.

Until we tried to touch it.

And it became real…

Dementia. Dying. Being born!

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It happens unexpectedly: a person long thought lost to the ravages of dementia, unable to recall the events of their lives or even recognize those closest to them, will suddenly wake up and exhibit surprisingly normal behavior, only to pass away shortly thereafter. This phenomenon, which experts refer to as terminal or paradoxical lucidity, has been reported since antiquity, yet there have been very few scientific studies of it. That may be about to change.

In an article published in the August issue of Alzheimer’s & Dementia , an interdisciplinary workgroup convened by the National Institutes of Health’s (NIH) National Institute on Aging and led by Michigan Medicine’s George A. Mashour, M.D., Ph.D., outlines what is known and unknown about paradoxical lucidity, considers its potential mechanisms, and details how a thorough scientific analysis could help shed light on the pathophysiology of dementia. (1)

Plato said it a long time ago.

What you see are just reflections.

Of a world beyond our own.

There is no way to prove that.

Unless you stop seeing outside.

And see inside yourself.

You are dying now. And you see things do clearly.

And yet, all of the sudden, you start remembering.

Of things you knew and you had forgotten.

But nothing which is worth knowing can be forgotten.

Nothing which is worth knowing can be learnt.

Look! He speaks so clearly now…

No, this is not a sign of hope.

But the last signs of decay fading away…

Predict. What you can never understand…

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Artificial intelligence can predict premature death, according to a study.

Computers which are capable of teaching themselves to predict premature death could greatly improve preventative healthcare in the future, suggests a new study by experts at the University of Nottingham.

The team of healthcare data scientists and doctors have developed and tested a system of computer-based ‘machine learning’ algorithms to predict the risk of early death due to chronic disease in a large middle-aged population. (1)

Computers predicting what they can never understand.

Is there any other way?

We can only predict what we do not know.

Look at the flower.

Smell the wind.

Feel the rain falling…

You will never predict them.

And yet, you smile.

Only because you know all there is to know about them…

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