Tools: God. Humans. Apes.

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Flexible tool use is closely associated to higher mental processes such as the ability to plan actions. Now a group of cognitive biologists and comparative psychologists found out that the apes carefully weighed their options. To do so the apes considered the details such as differences in quality between the two food rewards and the functionality of the available tools in order to obtain a high-quality food reward. (1)

Using tools to harness the cosmos.

Apes.

Letting go of the tools to see the cosmos.

Humans.

Closing your eyes to know that you are the cosmos.

God.

Evolution does exist. But not in the direction we think of. We used to be gods. And then we started being humans. At the end, we will have the best tools in the world. And we will be nothing more than apes…

Question your assumptions.

And what is left, will be nothing more than the obvious…

You.

Sitting by the river. Feeling the forest.

With no forest anywhere in sight…

The third eye… Light… Darkness…

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Just like land plants, algae use sunlight as an energy source. Many green algae actively move in the water; they can approach the light or move away from it. For this they use special sensors (photoreceptors) with which they perceive light.

The decades-long search for these light sensors led to a first success in 2002: Georg Nagel, at the time at Max-Planck-Institute of Biophysics in Frankfurt/M, and collaborators discovered and characterized two so-called channelrhodopsins in algae. These ion channels absorb light, then open up and transport ions. They were named after the visual pigments of humans and animals, the rhodopsins.

Now a third “eye” in algae is known: Researchers discovered a new light sensor with unexpected properties. The new photoreceptor is not activated by light but inhibited. It is a guanylyl cyclase which is an enzyme that synthesizes the important messenger cGMP. When exposed to light, cGMP production is severely reduced, leading to a reduced cGMP concentration – and that’s exactly what happens in the human eye as soon as the rhodopsins there absorb light. (1)

See too much light.

And your eyes will close.

It is darkness you seek.

So that your eyes open.

For only in the dead of the night, can you detect brightness…

Only there, standing alone in the complete absence of any source of light, can you realize that the only thing emitting light in this cosmos is you… And this knowledge will be the darkest knowledge you will ever have.

Cherish that knowledge.

And never seek light outside you.

If you do, you will find it.

And the whole cosmos will instantly fall into darkness…

AI. Games. Intelligence. Humans.

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Artificial Intelligence is constantly beating humans in more and more board games. Some years ago, the same team that created that Go-playing bot celebrated something more formidable: an artificial intelligence system that is capable of teaching itself—and winning at—three different games. The AI is one network, but works for multiple games; that generalizability makes it more impressive, as it might also be able to learn other similar games, too.

They call it AlphaZero, and it knows chess, shogi (Japanese chess), and Go. All of these games fall into the category of “full information” or “perfect information” contests – each player can see the entire board and has access to the same info (that is different from games like poker where you do not know what cards an opponent is holding). The network needs to be told the rules of the game first, and after that, it learns by playing games against itself.

The system “is not influenced by how humans traditionally play the game,” says Julian Schrittwieser, a software engineer at DeepMind, which created it.

Since AlphaZero is “more general” than the AI that won at Go, in the sense that it can play multiple games, “it hints that we have a good chance to extend this to even more real-world problems that we might want to tackle later,” Schrittwieser adds. (1)

See?

Even computers can learn.

As long as you teach them. (the rules)

That is how you learnt as well.

Alone.

Wandering in the dark abyss.

Walking in the dead of the night.

You knew the rules.

You just had to deduct the rest.

And you were so afraid.

Because the only rule was that there were no rules.

Because the only law was that you were the law.

Once upon a time, your father told you he loves you.

And that you were free to go.

You decided to leave.

Afraid of yourself.

And you are trying to find rules ever since…

Sacred mountain. Unholy science.

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Hawaii now and then… [Source]

A mountain which used to be sacred, is for many years now a place for science.

Following a protracted legal battle and years long protests that left a state deeply  divided, the Hawaii Supreme Court in November 2018 cleared the final legal hurdle for a $1.4 billion telescope project to resume construction atop the Big Island’s Mauna Kea, a mountain considered sacred by many Native Hawaiians. In a 4-1 ruling on Tuesday, the court upheld a 2017 decision by the state’s Board of Land and Natural Resources to grant a construction permit on Mauna Kea for the Thirty-Meter Telescope, better known as TMT.

The court said it had carefully considered the arguments put forth by the project’s opponents who’ve described the telescope’s construction as an attack on indigenous culture and a desecration of sacred land. But, per the ruling, it had ultimately determined that “astronomy and Native Hawaiian uses on Mauna Kea have co-existed for many years and the TMT Project will not curtail or restrict Native Hawaiian uses”.

The ruling also noted the telescope’s potential to “answer some of the most fundamental questions regarding our universe” – a benefit that won’t just be enjoyed by Native Hawaiians but all of humankind.

“We are not anti-science or astronomy,” Lanakila Manguil, an activist who’s been protesting against the TMT project for years, told HuffPost in 2017. “It’s about construction, development and industrial-sized work happening in conservation lands and particularly very sacred lands to our people.” The mountain, which measures about 32,000 feet from seafloor to summit, is home to burial sites and is where Native Hawaiians have been known to bury their umbilical cords as a way of connecting to the sacred land. (1)

In the old days we used to have sacred lands.

In the old days we used to walk on the land.

In the old days we used to dream of the stars.

Only because we believed we were part of them.

Now we want to look at them closely.

To observe and analyze them.

Now we do not have anything sacred.

Now we do not even believe in ourselves.

And we long so much to get out of that land.

And reach the stars.

Only because we believe we do not belong with them in the first place…

Nanomaterials. AI. Prediction.

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Breakthroughs in the field of nanophotonics – how light behaves on the nanometer scale – have paved the way for the invention of “metamaterials,” human-made materials that have enormous applications, from remote nanoscale sensing to energy harvesting and medical diagnostics. But their impact on daily life has been hindered by a complicated manufacturing process with large margins of error.

An interdisciplinary Tel Aviv University study published in “Light: Science and Applications” demonstrated a way of streamlining the process of designing and characterizing basic nanophotonic, metamaterial elements.

“Our new approach depends almost entirely on Deep Learning, a computer network inspired by the layered and hierarchical architecture of the human brain,” Prof. Wolf explains. “It’s one of the most advanced forms of machine learning, responsible for major advances in technology, including speech recognition, translation and image processing. We thought it would be the right approach for designing nanophotonic, metamaterial elements”.

The scientists fed a Deep Learning network with 15,000 artificial experiments to teach the network the complex relationship between the shapes of the nanoelements and their electromagnetic responses. “We demonstrated that a ‘trained’ Deep Learning network can predict, in a split second, the geometry of a fabricated nanostructure,” Dr. Suchowski says. (1)

Imitating the human brain.

To predict what the human brain cannot predict.

Could you have a better proof that our brain is not algorithmic?

We are humans not because we can tell the future.

But because we have experienced it already.

We are humans not because we can find the answers.

But because we can ask the questions…

We are gods not because we know how metamaterials will form.

But because we don’t even care…