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Thursday, March 21, 2013

In the beginning was the code



Dear Friends,
Be Well.
David


In the beginning was the code
A transcript of Jürgen Schmidhuber’s TEDx talk in Belgium
universe_cube
March 15, 2013 by Jürgen Schmidhuber

A supercomputer simulation of the evolution of the universe (credit: Andrey Kravtsov/University of Chicago)
There is a fastest, optimal, most efficient way of computing all logically possible universes, including ours — if ours is computable (no evidence against this). Any God-like “Great Programmer” with any self-respect should use this optimal method to create and master all logically possible universes.

At any given time, most of the universes computed so far that contain yourself will be due to one of the shortest and fastest programs computing you. This insight allows for making non-trivial predictions about the future. We also obtain formal, mathematical answers to age-old questions of philosophy and theology.

Transcript of Jürgen Schmidhuber’s TEDx talk at UHasselt, Belgium, Nov. 10, 2012


I will talk about the simplest explanation of the universe. The universe is following strange rules. Einstein’s relativity. Planck’s quantum physics. But the universe may be even stranger than you think. And even simpler than you think
.
Is the universe being created by a computer program?

Konrad Zuse

Many scientists are now taking seriously the possibility that the entire universe is being computed by a computer program, as first suggested in 1967 by the legendary Konrad Zuse, who also built the world’s first working general computer between 1935 and 1941. [1]

Zuse’s 1969 book Calculating Space discusses how a particular computer, a cellular automaton, might compute all elementary particle interactions, and thus the entire universe.

The idea is that every electron behaves the same, because all electrons re-use the same subprogram over and over again.

First consider the virtual universe of a video game with a realistic 3D simulation. In your computer, the game is encoded as a program, a sequence of ones and zeroes. Looking at the program, you don’t see what it does. You have to run it to experience it.

Reality has still higher resolution than video games. But soon you won’t see a difference any more, since every decade, simulations are becoming 100–1000 times better, because computing power per Swiss Franc is growing by a factor of 100–1000 per decade.

A few decades imply a factor of a billion. Soon, we’ll be able to simulate very convincing heavens and hells. It will seem quite plausible that the real world itself also is just a simulation.

To a man with a hammer, everything looks like a nail. To a man with a computer, everything looks like a computation.

Skeptics might say: What about quantum physics, and Heisenberg’s uncertainty principle, and Bell’s inequality? Don’t they imply that the universe cannot be produced by a deterministic program? Not at all. Bell himself knew well that deterministic universes including deterministically computable observers are fully compatible with all available physical observations.

The universe as the sum of all mathematics

“Calculating space,” a painting by Konrad Zuse

When my brother Christof was a teenager in the early 1980s in Munich, he told me and others: the universe, or quantum multiverse, is the sum of all mathematics. I believe he is the reason why such ideas emerged in Munich.

He was younger than me. He still is. He also was smarter than me. He went on to become a physicist at Munich, Caltech, Princeton, and CERN, and he lived in Berne next door to where Einstein lived.

It took me a while to understand what my brother meant. In 1996, I formalized his idea through a computation. I generalized Everett’s many worlds theory, pointing out that there is a very short and fast program that not only computes our own universe, or multiverse, but also all other logically possible universes, even those with different physical laws. For example, universes with anti-gravity.

In fact, there is a fastest, optimal, most efficient way of computing all logically possible universes, including ours — if ours is computable (no evidence against this).

(Credit: TEDx)

The optimal method can be programmed with only ten lines of code. I wrote it down for you — here it is! [Holds up a piece of paper.] [2]

Any God-like “Great Programmer” with some self-respect should use this optimal method to create and master all logically possible universes.

Suppose he runs it for a while. At some point, many of the executed programs will have computed universes that containyou! You, as you are sitting here and staring at me with incredulous eyes.

You could even become a “Great Programmer” yourself, using the optimal method [holds note up again] to simulate all possible universes in nested fashion. (But this would not necessarily help to figure out the future faster than by waiting for it to happen. The computer on which to run this program would have to be built within our universe, and as a small part of the latter would be unable to run as fast as the universe itself.)

Anyway, now it’s easy to see that due to the nature of the optimal method, at any given time, most of the universes computed so far that do contain yourself will be due to one of the shortest and fastest programs computing: YOU.

Predictions

This insight allows for making non-trivial predictions about the future. There are many possible futures of your past so far. Which one is going to happen? Answer: given the probability distribution induced by the optimal method, most likely one of the few regular, non-random futures with a fast and short program.[3] (Because the weird futures where suddenly the rules change and everything dissolves into randomness are fundamentally harder to compute, even by the optimal method. Random stuff by definition does not have a short program.)
This implies that the decay of neutrons, widely believed to be random, most likely is not random, but pseudo-random, like the decimal expansion of PI, which looks random, but isn’t, because it is computable by a short and fast program.

Why quantum computing may never scale

The optimal method also implies that quantum computation will never work well, essentially because it is consuming so many basic computational resources. I first made this prediction a dozen years ago. Since then there has not been any progress in practical quantum computation, despite lots of efforts. (The biggest number factored into its prime factors by any existing quantum computer is still 15.) Quantum computation is sexy, but dead.

What about free will? Free will is overrated. In my group at the Swiss AI Lab IDSIA, we often program simulated worlds including simulated observers with simulated artificial brains. Through pseudo-random trial and error they even learn from experience to become smarter over time, acting as if they had free will. They have no idea that every thought in their artificial neural networks is computed by a deterministic program. (In a way, they do have free will — it’s just deterministically computed free will.)

Computational theology

Nevertheless, computer science is now giving us formal, mathematical answers to old questions of philosophy and theology. One of the results of my Computational Theology is this: your own life must be very important in the grand scheme of things.

You may think that your life is insignificant, because you are so small, and the universe is so big. But given the Great Programmer’s optimal way of computing all universes, it is probably very hard to edit your life (or mine) out of our particular universe: Any program that produces a universe like ours, but without you, is probably much longer and slower (and thus less likely) than the original program that includes you.

So with high probability, your life essentially has to be this way, with all of its ups and downs. Your life is notinsignificant. It seems to be an indispensable part of the grand scheme of things.[4]

This is compatible with religions claiming that “all is one,” “everything is connected to everything.” May this thought lift you up in times of frustration.

Footnotes:

(Credit: iStockphoto)

1. A recent KurzweilAI news article mentioned somewhat related ideas by Max Tegmark (1997/1998). How does Schmidhuber’s approach differ?

“My paper on all computable universes called ‘A computer scientist’s view of life, the universe, and everything’ got submitted/published in 1996/1997,” Schmidhuber told KurzweilAI.

“Back then, Max also was based in Munich (at LMU). He put forth this somewhat vague and not really formally well-defined notion of a mathematics-based ensemble of universes.

“He assumed a uniform prior distribution on this ensemble, which unfortunately cannot even exist, as there is no uniform distribution on countably infinite things. Over the years, Max and I had quite a few little chats about this :-) . I think a mathematical analysis of this type really must focus on the formally well-defined, limit-computable mathematical structures/universes.

“Max also completely ignores computation time, while the talk above is all about computation time, which makes a big difference between easy-to-compute and hard-to-compute universes, and greatly affects their probabilities, and thus the most likely futures of observers inhabiting them. I also addressed such differences in an additional 2000 paper on all formally describable universes (and also in the 2012 survey paper for H. Zenil’s book, A Computable Universe).

“I also wrote that I suspect my brother Christof Schmidhuber is the real reason why such ideas emerged in Munich. At the age of 17 he declared that the universe is the sum of all math, inhabited by observers who are mathematical substructures (private communication, Munich, 1981).

“As he went on to become a theoretical physicist at LMU Munich, Caltech, Princeton, and CERN, discussions with him about the relation between superstrings and bitstrings became a source of inspiration for writing both the first paper  and later ones based on computational complexity theory, which seems to provide the natural setting for his more math-oriented ideas (private communication, Munich 1981-86; Caltech 1987-93; Princeton 1994-96; Berne/Geneva 1997–; compare his notion of “mathscape”).”

2. The preprint of a recent overview paper by Schmidhuber includes pseudocode (a simplified generic version) for the ten lines of code mentioned in the talk (see also slides):

FAST Algorithm
for i := 1, 2, . . . do

Run each program p with l(p) ≤ i for at most 2i−l(p) steps and reset storage modified by p
end for

[here l(p) denotes the length of program p, a bitstring]

Schmidhuber explains: “This is essentially a variant of Leonid Levin’s universal search (1973), but without the search aspect. The code systematically lists and runs all possible programs in interleaving fashion. It can be shown that it computes each particular universe as quickly as this universe’s (typically unknown) fastest program, save for a constant factor that does not depend on the universe size.

From this asymptotically optimal method, we can derive an a priori probability distribution on possible universes called the Speed Prior. It reflects the fastest way of describing objects, not necessarily the shortest. (BTW, note that any general search in program space for the solution to a sufficiently complex problem will create many inhabited universes as byproducts.)”

3. Assume you are running computations for all universes in parallel, says Schmidhuber. Some contain you at a given time. So among those universes computed so far that contain you, which are the most likely ones, that is, what’s your most likely future? In a Bayesian framework, “Speed Prior” permits non-trivial answers to questions of this type.
4. “Because most likely the universe to which you owe your current existence has a high a priori probability,” explains Schmidhuber. “Other possible variants of your life are less likely because they are harder to compute, even by the optimal method.”

The insights mentioned in this talk were first published between 1996 and 2000, and further popularized in the new millennium. Detailed mathematical papers as well as popular high-level summaries can be downloaded from Schmidhuber’s overview site on all computable universes.

For information on a Master’s Degree in Artificial Intelligence through courses taught by Schmidhuber and colleagues, visit this site: Master’s Degree in Informatics with a Major in Intelligent Systems

For new jobs for postdocs and PhD students in Schmidhuber’s research group, visit this site: http://www.idsia.ch/~juergen/eu2013.html


Dr. Juergen Schmidhuber is Director of the Swiss Artificial Intelligence Lab, Professor of Artificial Intelligence at the University of Lugano, Switzerland, and Professor at The University of Applied Sciences and Arts of Southern Switzerland

Wednesday, March 20, 2013

2013 - There is no end.


karstenramser.net
2013
There is no end. There is R-Evolution. The R-Evolution of consciousness. Life is r-evolving.
Out of the old arise the new. The known steps into the unknown. Only you can make the turn around.
The Change is inevitable. The world we know will come to an end. You are the change.
Awakening is your purpose. All is good, don´t be afraid.
The path to a new world passes through the winter of egoism, only when we have left behind the identification with the I, a new world will arise.
It is the hardest and most difficult way. It looks impossible, but you walk.
The dangers are real.Your fears are also real.
There is nothing left. Only the light who you are. Integrate the shadow of the ego.
Walk until you can´t walk anymore. Surrender. Leave the ego behind.
And you do not die, the unexpected happens. You awake up from the dream of the separate I.
The awakening is inside, there you will find the way to the new world.
The end is just the beginning of something new, so there is no end.
Only R-Evolution and Transformation.
All spiritual texts, all prophecies, all the good intentions, the highest ideals, the goodwill and the dream of a new world, everything will be in vain if we do not leave behind the identification with the I.
All is good, the Self knows. The Self is the only reality that exists. Trust.
When we recognize ourselves in the Self, now in this ever present moment, the new world will arise.
If you want to be the change, there is only one way, you must be the change.
We are not on the way, we are the way.
We are not creating the new world, we are the new world.
We can not fail, consciousness has already won, life exists.
We are life, immortal and eternal.
We are consciousness.
LIFE IS R-EVOLVING

Where we can go?‏



Dear Friends,


   Be Well.
   David



Where we can go?
We are here.
In the ever present moment.
There is no place where we can run to.
There is only the here and now.
Past and future are just thoughts.
Your identity is just a way to think.
Stop running
Stop hiding
Stop the wishful thinking
Awake up, to the only real thing in life
There will be never ever more then the here and now.
Stop searching
The next moment will never come.
be present now.
Is your attention in the now?
To be conscious now is our responsibility
It is our choice to be conscious now
It is our decision where we want to live,
we want to live in our imagination of what could and should be
or
We want to be real, seeing the miracle of life.
The thing we have to do,
is to give the idea of a separate identity.
Open your eyes and mind, see the miracle of existence.
You are in this moment the miracle.
Be your self,
do what ever you have to do,
most of all be conscious,
remember you can go nowhere,
you are here and now,
let life be the unfolding process.
Let it happen.

Like Robot, Like Human


Dear Friends,


Be Well.
David



Written on MARCH 15, 2013 AT 7:51 AM by JTOZER



Filed under FEATUREDROBOTS{NO COMMENTS}

I think it goes without saying that humans are flawed.
<pause for dramatic effect>
I know.  It’s a shocker.

So when we think of the things humans are capable of doing, there’s always a margin of error, isn’t there?  There’s always some bell curve that factors in because we know that we’ve got our short comings.  We’re not perfect.

Which is weird, since we are constantly asking the machines we build to be.  Especially the ones that awe and fascinate us the most.

Yeah, I’m talking about robots.

Up until now, the concept of a perfectly constructed robot was just that; a concept.  
Such a KIND face... (Cyberman, Copyright BBC)

Such a KIND face… (Cyberman, Copyright BBC)

Our movies and video games tend to depict robots as these inhuman goofy types, or seething, wrathful, intrinsically flawed things that either take on far too many human traits (Cylons) or not NEARLY enough (Cybermen).  In any case, our creative little minds tend to presume that robots are going to lean to the extremes.

But that’s just fun fiction.
However…

What if I told you that there was a process being developed that allowed scientists to implant a very human like thinking process into a very non-human robot brain?  Would you panic?  Because if so, I’d stop reading now.  And maybe seek out some calming tea.  Or professional help, depending on the severity.

Because it’s really happening, folks, and it’s going to change the way we think about Artificial Intelligence in a number of ways.

It’s called the Adaptive Character of Thought-Rational architecture, or ACT-R, courtesy of the Naval Research Laboratory (NRL).  So what does it do?

According to the recently released White Paper, a cognitive architecture is a set of computational modules that, working together, strive to produce human-level intelligence.

I’m just going to let that sink in for a minute there.

“But wait,” I hear you saying, “didn’t you start off this blog talking about how humans are flawed?”

Yes.  I did.  That’s what makes this all the more exciting.  They’re not trying to create the perfect, godlike deathbots of SciFi lore and repute.  Rather, they’re creating a synthetic version of people, so to speak.
No, wait!  Don’t panic.  Let me explain.

Thinking like a person means thinking imperfectly.  We remember things strangely.  Our memories degrade over time.  We let our emotions guide us.  Humans are driven by patterns and associations and experience over facts and deductive reasoning.

As it turns out, that’s exactly what these scientists are trying to capture.

The Soar architecture uses a modest set of building blocks to achieve human intelligence, including different types of memories (procedural, semantic, episodic) and different types of learning (reinforcement, chunking, semantic learning, episodic learning).

Learning is the key point there.  Not retaining information in a database, but actually learning.

These scientists are using ACT-R and ACT-R/E (Adaptive Character of Thought-Rational/Embodied (ACT-R/E) architecture) to build better, more comprehensive models of human cognition and leverage these models to improve the robot’s ability to interact with humans.  So why is this architecture so unique?

Because it’s designed to model human mentality by placing an emphasis on the limitations of human cognition.

These robots are trying to “get us” down at our level.  Well, that’s an interesting idea.  But before you act insulted, consider this: the argument is that robots who understand people are, ultimately, better teammates and more natural computational agents.  I guess they have to be able to think like us in order to be efficient and productive for us.

Not to get too philosophical on you, but what does it really mean to think like a human?

It all comes down to how we remember things.

For example, say you meet someone for the first time at a party.  They tell you their name, and if you aren’t completely disinterested in them you will likely try to remember it.  When a person remembers something, they do so by using a series of patterns.  Your mind will try to tie the new information (the name) to defining factors (face, voice, clothing, etc).

When you see this person again, you try to use certain trigger cues.  You see the hair, or the face or smell the perfume and your brain tries to tie the new information (the name) to those things.  Priming from contextual clues could provide the boost you need in memory activation, and the earlier rehearsal of associating those things together would likely be enough for you to remember the name of this person.  Ideally.

Then again, we’re not perfect.  You might end up calling them by the wrong name a few more times before it sticks.

Anyway, the ACT-R works insomuch the same concept.  When the robot (or model, as they call it) is introduced to new information like this, it uses a similar structured pattern to remember things.  So this information is not just being dumped into a memory bank as raw data to be regurgitated on command.

Rather, it becomes a piece of information that’s associated with other things.

Octavia and a human escort (photo courtesy of the Naval Research Lab)
Octavia and a human escort (photo courtesy of the Naval Research Lab)


Octavia and a human escort (photo courtesy of the Naval Research Lab)

At a high level, ACT-R is a hybrid symbolic/subsymbolic production-based system.  That means everything is connected to everything else in order to create a memory.

How do they do this?  By using a system called Specialized Egocentrically Coordinated Spaces, or SECS.  This enables human-like, cognitively plausible spatial reasoning.

This architecture is more than just retaining information as it comes in.  As we all know, our bodies tend to function as a whole; that is, memory retention is often a result of the sum of our parts.

The ACT-R/E model is designed to act as a consumer of visual information provided by external visual systems.  Senses – like sight, sound, environment – all play a part in how we absorb and interpret information around us.  This architecture wants the robot to get that full memory-making experience as well.

One of the recent threads in cognitive science has been embodied, or grounded, cognition.

The focus has been on showing that the body has a major role in shaping the mind.  When the motor and visual modules participate fully in the spreading of contextual activation, it is possible for a robot to learn which objects are best grasped with which motor commands.

Basically, these robots have the capacity to “understand” all their working parts, and those parts can work together to form information.  So if it talks like a human and thinks like a human, that doesn’t mean it is a human.

Speaking of us living, breathing specimens…

There are some things about these robots that deviate from the standard human procedure.  Things like fatigue, emotional instability, unpredictability, sleepiness, weepiness, derpiness, they’re all intrinsically human aspects.  Aspects that robots have no real reason to contend with, though that hasn’t stopped some SciFi writers from exploring the possibility of having depressed, mopey robots.


Anyway, that doesn’t mean these robots cannot be taught how to approach humans by understanding what makes them so crazy *ahem* interesting.  The high-level goal behind this is to give robots a deep understanding of how people think at the process level in order to make them better teammates.

They’re doing this by equipping robots with the functionality to understand human behavior – like right vs wrong – and use that information to act accordingly.  Skeptical?  Well, so was I.  I mean, how does a robot know the difference between right and wrong when philosophers have been making a living debating that very idea for centuries?

Turns out, in this case it’s more of a holistic approach to situation and crisis.  Noticing how humans tend to make mistakes in predictable ways, for example, can set a standard, or watching how their eyes move when they retrieve memories.

By developing robots that further understand how people think – including errors – they can leverage these models as tools for robots to use as they encounter humans in the world.

For example, the scientists put a robot to work on a serious project: playing hide-and-seek.  Given the fact that the ATC-R is designed to learn and understand, the robot was able to grasp the concept of the game fairly quickly.  The model was in fact able to mimic the outward behavior of the person, perfectly matching the hiding behavior.

That sounds small, but it’s really a big, big deal.  The robot was also able to play a credible game of hide and seek against a human.  Think about that.

Don’t believe me?  See for yourself:


Just when you thought you’ve seen it all, eh?  It’s like watching the early stages of robot evolution take place.
This architecture is designed with a Theory of the Mind (ToM) concept.  That is, the ability to understand beliefs, desires, and intentions of others.  So why give the robots this empathetic concept?  ToM is used to improve the robot’s ability to interact with people.  This is pertinent because research in psychology has shown that without ToM, people can be severely impaired in their abilities to interact naturally with others.  Apparently, the same goes for robots.

Simply put, robots are a little freaky when they’re disregarding of these things.

So why all of this, you wonder?  Why give robots the ability to think like humans, consider their intentions, and learn to play well with us?  Well, why else do you train?  For the mission.  These robots are being designed to be good teammates to people.  To help them.  To perform missions.  Just like us, they are given a task – like fighting fires for example – and they need to be the best equipped to complete that task to the best of their ability.

In this case, learning how to help humans means having a better robo-understanding of them.  The best part?  This is only the beginning.  The road to good, embodied cognitive models has been and continues to be long, but the scientists at NRL say it’s going to be well-worth the effort.

I guess you know how the old saying goes…

To err is human.  To learn how to err is robot. 

Jessica L. Tozer is a blogger for DoDLive and Armed With Science.  She is an Army veteran and an avid science fiction fan, both of which contribute to her enthusiasm for technology in the military.
Special thanks to the Naval Research Laboratory for providing the information and general awesomeness factor needed for this story.

esoteric



SUBTITLES IN ENGLISH, ESPAÑOL, PORTUGUÊS

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MUFON

How to Digitally Record/Video a UFO sighting:


Como registar digitalmente ou gravar um vídeo de um avistamento de um UFO:




Stabilize the camera on a tripod. If there is no tripod, then set it on top of a stable, flat surface. If that is not possible lean against a wall to stabilize your body and prevent the camera from filming in a shaky, unsteady manner.

Estabilize a camera com um tripé. Se não tiver um tripé, então coloque-a em cima de uma superfície estável. Se não for possível, então encoste-se a uma parede para estabilizar o corpo e evitar que a camera registe de maneira tremida e instável.

Provide visual reference points for comparison. This includes the horizon, treetops, lampposts, houses, and geographical landmarks (i.e., Horsetooth Reservoir, Mt. Adams, etc.) Provide this in the video whenever is appropriate and doesn’t detract from what your focus is, the UFO.

Forneça pontos visuais de referência para comparação. Isso inclui o horizonte, cimo das árvores, postes de iluminação, pontos de referência geográficos (como o Reservatório de Horsetooth, Mone Adams, etc) Forneça esses pontos no vídeo sempre que for apropriado e não se distraia do que é o seu foco, o UFO/a Nave.

Narrate your videotape. Provide details of the date, time, location, and direction (N,S,E,W) you are looking in. Provide your observations on the weather, including approximate temperature, windspeed, any visible cloud cover or noticeable weather anomalies or events. Narrate on the shape, size, color, movements, approximate altitude of the UFO, etc and what it appears to be doing. Also include any unusual physical, psychological or emotional sensations you might have. Narrate any visual reference points on camera so they correlate with what the viewer will see, and thereby will be better able to understand.

Faça a narração do vídeo. Forneça pormenores sobre a data, hora, local e direcção (Norte, Sul, Este, Oeste) que está a observar. Faça observações sobre as condições atmosféricas, incluindo a temperatura aproximada, velocidade do vento, quantidade de nuvens, anomalias ou acontecimentos meteorológicos evidentes. Descreva a forma, o tamanho, a cor, os movimentos, a altitude aproximada onde se encontra o UFO/nave, etc e o que aparenta estar a fazer. Inclua também quaisquer aspectos pouco habituais de sensações físicas, psicológicas ou emocionais que possa ter. Faça a narração de todos os pontos de referência visual que o espectador irá ver e que, deste modo, será capaz de compreender melhor.

Be persistent and consistent. Return to the scene to videotape and record at this same location. If you have been successful once, the UFO sightings may be occurring in this region regularly, perhaps for specific reasons unknown, and you may be successful again. You may also wish to return to the same location at a different time of day (daylight hours) for better orientation and reference. Film just a minute or two under “normal” circumstances for comparison. Write down what you remember immediately after. As soon as you are done recording the experience/event, immediately write down your impressions, memories, thoughts, emotions, etc. so it is on the record in writing. If there were other witnesses, have them independently record their own impressions, thoughts, etc. Include in this exercise any drawings, sketches, or diagrams. Make sure you date and sign your documentation.

Seja persistente e não contraditório. Volte ao local da cena e registe o mesmo local. Se foi bem sucedido uma vez, pode ser que nessa região ocorram avistamentos de UFOs/naves com regularidade, talvez por razões específicas desconhecidas, e talvez possa ser novamente bem sucedido. Pode também desejar voltar ao mesmo lugar a horas diferentes do dia (durante as horas de luz)para ter uma orientação e referência melhor. Filme apenas um ,inuto ou dois em circunstâncias “normais” para ter um termo de comparação. Escreva tudo o que viu imediatamente após o acontecimento. Logo após ter feito o registo da experiência/acontecimento, escreva imediatamente as impressões, memórias, pensamentos, emoções, etc para que fiquem registadas por escrito. Se houver outras testemunhas, peça-lhes para registar independentemente as suas próprias impressões, pensamentos, etc. Inclua quaisquer desenhos, esbolos, diagramas. Certifique-se que data e assina o seu documento/testemunho.

Always be prepared. Have a digital camera or better yet a video camera with you, charged and ready to go, at all times. Make sure you know how to use your camera (and your cell phone video/photo camera) quickly and properly. These events can occur suddenly, unexpectedly, and often quite randomly, so you will need to be prepared.

Esteja sempre preparado, Tenha sempre uma camera digital, melhor ainda, uma camera vídeo consigo, carregada e pronta a usar sempre que necessário. Certifique-se que sabe como lidar com a sua camera (ou com o seu celular/camera fotográfica) rápida e adequadamente. Esses acontecimentos podem acontecer súbita e inesperadamente e, por vezes, acidentalmente, por isso, necessita estar preparado.

Look up. Be prepared. Report. Share.

Olhe para cima, Esteja preparado, Relate, Partilhe.

MUFON.COM

ESOTERIC



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