Creative AI… Dull humans…

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In October 2018, a portrait of Edmond Belamy sold at Christie’s in New York for $432,500, nearly 45 times its maximum estimated price. Nothing that out of the ordinary, perhaps. Except Belamy didn’t exist. He was the fictitious product of the artist’smind – and the mind that created him wasn’t even human.

Signed in the corner by a formula that is part of the algorithm that created it, the portrait was the first artwork made by artificial intelligence brought to auction. There have been many similar seeming breakthroughs in AI creativity. In 2017, an AI wrote a continuation of the Harry Potter books by using machine learning to analyse the first seven volumes of J. K. Rowling’s output. The music for US singer Taryn Southern’s 2018 album I AM AI was bigged up as having been composed and produced entirely by machines. Back in 2016, SACEM, a French professional association in charge of artists’ rights, was the first to acknowledge an algorithm, the Artificial Intelligence Virtual Artist or AIVA, as a composer.

It fits into a common theme that anything we can do, AI can do – and probably better. But it is worth looking under the hood of all these creative outputs to understand how much the machines really are doing, and how much is just hype. Answering the question of whether AI can be creative isn’t easy – and raises fundamental questions about the nature and origins of human creativity. (1)

How exquisite.

At the end, computers will understand art.

At the end, AI will create genuine art.

And we will see it.

And we will understand it.

And only then will we understand that there is no art.

Without someone not understanding it…

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…

Μπορείς να με καταλάβεις;

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As two people speak, their brains begin to work simultaneously, synchronizing and establishing a unique bond. This is what in neuroscience is called brain synchronization.

New research by the Basque Center on Cognition, Brain and Language (BCBL) in San Sebastián and published in Cortex magazine confirms that this phenomenon depends on the language we use to communicate.

“When a conversation takes place in one’s native language, both interlocutors pay attention to it in a more global way, focusing on the sentences and the global content of the message,” stresses Jon Andoni Duñabeitia, co-author of the study. However, when done in a foreign language, attention resources focus primarily on other, more complex linguistic levels for non-native speakers, such as sounds and words.

“In the latter communicative context we need to reconfigure our attention strategies so that we can understand each other, and this may be directly related to the difference in the areas synchronised during the conversation,” suggests Duñabeitia. (1)

Language.

Portrayed as a facilitator of communication.

But it is actually a barrier we must overcome.

Only when this barrier is lifted can we actually speak to each other.

Because communication and understanding never stem from logos.

But Logos is the result of the understanding we already have.

Speak to me.

And I will understand you…

Only if I already do…

Note: “Μπορείς να με καταλάβεις;” = “Can you understand me?” in Greek…

The limits of AI…

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A team of mathematicians and AI researchers discovered that despite the seemingly boundless potential of machine learning, even the cleverest algorithms are nonetheless bound by the constraints of mathematics.

Research showed that a machine’s ability to actually learn – called learnability – can be constrained by mathematics that is unprovable. In other words, it’s basically giving an AI an undecidable problem, something that’s impossible for an algorithm to solve with a true-or-false response.

The team investigate a machine learning problem they call ‘estimating the maximum’ (EMX), in which a website seeks to display targeted advertising to the visitors that browse the site most frequently – although it isn’t known in advance which visitors will visit the site. This problem is similar to a mathematical paradox called the continuum hypothesis, another field of investigation for Gödel.

Like the incompleteness theorems, the continuum hypothesis is concerned with mathematics that cannot ever be proved to be true or untrue, and given the conditions of the EMX example, at least, machine learning could hypothetically run into the same perpetual stalemate. (1)

We believe in science.

But the only thing science has proved is that it cannot prove anything.

Gödel’s incompleteness theorem showed that whatever we do, we will never be able to prove everything in the context of our limited theories. No matter how many axioms you choose and how carefully you choose them, you will never be able to describe the cosmos in its totality in an objective way as proponents of scientism would like to believe.

Now we have built big computers.

With the hope that they will answer everything.

But they cannot answer anything.

Because there is nothing to answer in the first place.

In a limited world there is no reason to analyze the Monad.

In an immeasurable cosmos you cannot count beyond One.

The maximum is zero.

The minimum is infinite.

A computer struggling to make sense of the problem. A man standing beside the computer trying to make sense of the computer. A bird flying by. Poor man…

Reading emotions… Listen to the silence…

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Research shows for the first time that adults with autism can recognize complex emotions such as regret and relief in others as easily as those without the condition.

Psychologists at the University of Kent used eye-tracking technology to monitor participants as they read stories in which a character made a decision then experienced a positive or negative outcome. The lead author Professor Heather Ferguson, from the University’s School of Psychology, explained that the study highlights a previously overlooked strength in adults with ASD.

The researchers found that adults with autism spectrum disorder (ASD) were quickly able to think about how things might have turned out differently (either better or worse than reality), then judge whether the story character would feel regret or relief (known as counterfactual emotions).

The adults with ASD were found to be just as good at recognizing regret emotions in the character as adults without the condition, and even better at computing relief. (1)

We believe that reading emotions is important. But there is nothing to read. Because everything lies within our self. Let go and become a hole for the cosmos to fill. And you will understand everything.

People with ASD do not try to understand, explain or respond as we do. They simply receive. And their inability to express what they know makes us believe that they know nothing, even though the truth is exactly the opposite.

It is the silence which holds the knowledge we try to find.

It is the absence of understanding which holds the wisdom we seek.

Listen to the ones who speak not.

And in their absence of words.

You will hear everything…