BDi:: January 2017

Tuesday, January 31, 2017

http://www.cjob.com/2017/01/29/5-dead-in-quebec-city-mosque-shooting/

http://heavy.com/news/2017/01/alexandre-bissonnette-quebec-city-canada-mosque-shooting-attack-suspect-gunman-shooter-photos-pictures-video-motive/

Monday, January 30, 2017

After hunting a massive alligator, etc.

https://www.youtube.com/watch?v=FLaXcxE5spI

NZ RB, etc.
https://www.youtube.com/watch?v=nVY58mBA7IU&t=125s

https://www.youtube.com/watch?v=1bx-NLt7doY

https://www.youtube.com/watch?v=30mOnCEpMxI

https://www.youtube.com/watch?v=HYmMXrV8fqc

https://www.youtube.com/watch?v=GmahvjLfq2o rabbit food
https://www.youtube.com/watch?v=udN5b-38Wms ,
https://www.youtube.com/watch?v=dpDmHG_8pwE

zzs

Moon's Been Getting Oxygen from Earth's Plants for Billions of Years

https://ca.yahoo.com/news/moons-getting-oxygen-earths-plants-211700052.html

Saturday, January 28, 2017

11-bible-quotes-that-everyone-gets-wrong

http://www.weirdworm.com/11-bible-quotes-that-everyone-gets-wrong

Thursday, January 26, 2017

radio and internet

http://streema.com/radios/CJOB ,

http://streema.com/radios/570_KLIF

https://databits-jf.blogspot.ca/2017/01/radio-and-internet.html

https://the-loaf-etc.blogspot.ca/2017/01/putlockers-movie.html

putlockers-movie

http://www.putlockers-movie.com/1979-watch-arrival-online-free-putlocker.html

http://www.putlockers-movie.com/sci-fi-movies-online-putlocker/

http://www.putlockers-movie.com/1944-watch-jack-reacher-never-go-back-online-free-putlocker.html

Wednesday, January 25, 2017

https://en.wikipedia.org/wiki/Paris_in_the_Twentieth_Century#Summary

Hetzel rejected Verne's 1863 manuscript for Paris in the Twentieth Century because he thought it presented a vision of the future that was far too negative and unbelievable for contemporary audiences, though to many present-day scholars the story was remarkably accurate in its predictions. Verne locked the manuscript away and no longer wrote futuristic, dystopian stories. Paris in the Twentieth Century was first published in France in 1994.
https://en.wikipedia.org/wiki/Pierre-Jules_Hetzel#Biography

https://en.wikipedia.org/wiki/Nautilus_(Verne)

http://jv.gilead.org.il/biblio/voyages.html

Tuesday, January 24, 2017

5-strange-celebrity-deaths

http://www.coasttocoastam.com/article/video-5-strange-celebrity-deaths/

jim-whittenberger-mystery-glass-magic-window

http://midnightinthedesert.com/tue-jan-24-jim-whittenberger-mystery-glass-magic-window/

Little Tiger vs Big Rat

https://www.youtube.com/watch?v=hwfV-w5Ibkc

Ben
https://www.youtube.com/watch?v=-mCvkVXgYdk

lancaster-avro-nx611 and 911

https://data--stream.blogspot.ca/2017/01/lancaster-avro-nx611-is-undergoing.html

Martin Waldseemuller 11-september-1470

https://data--stream.blogspot.ca/2017/01/martin-waldseemuller-11-september-1470.html

9-11

Monday, January 23, 2017

William (Bill) Tompkins

“We already have the means to travel among the stars but these technologies are
locked up in Black Projects...and it would take an act of God to ever get them
out to benefit humanity. Anything you can imagine, we already know how to do.”
- Ben Rich, Former Director Of Lockheed Skunkworks shortly before his passing
“We now have the technology to take ET home. No, it won’t take someone’s
lifetime to do it. There is an error in the equations. We know what it is. We now
have the capability to travel to the stars."
- Ben Rich, Former Director Of Lockheed Skunkworks shortly before his passing
Ben Rich was asked how UFO propulsion functioned. His reply was remarkable.
“Let me ask you. How does ESP work?” The man asking the question of Mr Rich
said - “All points in time and space are connected?” Ben Rich then replied,
“That’s how it works!”

http://www.rense.com/general96/deepspaceexmp4.html

http://www.rense.com/Datapages/tompkinsdata.htm

rensewebmaster@gmail.com

https://desert-shapes.blogspot.ca/2017/01/william-tompkins-etc.html

re news

http://phibetaiota.net/2017/01/special-trump-trips-preibus-spicer-betrayal-deception-gaslighting-and-lies-the-war-between-two-alternative-forms-of-fake-news/

http://www.rense.com/general96/trumpsunforced.htm

Robert SteeleHas The Establishment
Already Isolated Trump?

Trump Trips, Preibus-Spicer Betrayal,

Deception, Gaslighting & Lies -
The War Between Two
Alternative Forms Of Fake News

Steele - Trump’s Unforced Errors -
Is Preibus Our Judas?

William Tompkins
The UFO Disclosure
Continues…Another
Extraordinary Conversation

Ultra Secret Documents &
Stunning Revelations

Air Force Systems Command Manual

Click Here

http://www.rense.com/general96/deepspaceexmp4.html

Thursday, January 19, 2017

silicon-valley

https://www.theguardian.com/lifeandstyle/2017/jan/19/silicon-valley-no-sex-peter-thiel-san-francisco
zzs

THE MOODY BLUES - The Classic Seven

https://www.youtube.com/watch?v=HjLHtWwAH_A

Wednesday, January 18, 2017

Blu Ray Home Theater Systems

http://www.usa.philips.com/c-p/HTS3106_F7/blu-ray-home-theater-system

http://bestofhouse.net/blu-ray-home-theater-systems

http://www.usa.philips.com/c-m-so/home-cinema-sound/5-1-home-cinema/latest#filters=5_1_HOME_THEATER_SYSTEMS_SU&sliders=&support=&price=&priceBoxes=&page=&layout=12.subcategory.p-grid-icon

https://www.google.ca/search?q=bluray+home+theater+systems&espv=2&biw=1280&bih=667&source=lnms&tbm=isch&sa=X&ved=0ahUKEwi42L2Sx83RAhUT52MKHX6mAIsQ_AUICSgC

https://www.google.ca/search?q=home+theater+systems&espv=2&source=lnms&tbm=isch&sa=X&ved=0ahUKEwjzud3uxs3RAhUSxWMKHSGxBooQ_AUICCgB&biw=1280&bih=667

astonishing-crop-circles-amaze-researchers

http://midnightinthedesert.com/astonishing-crop-circles-amaze-researchers/

a-releases-13-million-pages-declassified-documents-online

http://midnightinthedesert.com/cia-releases-13-million-pages-declassified-documents-online/

http://www.bbc.com/news/world-us-canada-38663522

http://www.coasttocoastam.com/article/cia-posts-huge-cache-of-rv-files/

midnightinthedesert.com/bill-birnes

http://midnightinthedesert.com/bill-birnes/

Robert-Anton-Wilson

http://visualmelt.com/Robert-Anton-Wilson

south-africa-and-ww-iii-prophecy-and-the-boer

http://disinfo.com/2017/01/south-africa-and-ww-iii-prophecy-and-the-boer

Charles Dellschau: Tech Visionary

Charles_Dellschau , http://www.charlesdellschau.com , http://www.shishigami.com/srfa/CAAD art

http://disinfo.com/2015/06/nymza-aeros-charles-dellschau-secret-airships-1850s

https://www.theatlantic.com/technology/archive/2013/03/charles-a-a-dellschau-dreams-of-flying-the-amazing-story-of-an-airship-club-that-might-never-have-existed/274170

http://selftaughtgenius.org/artworks/flying-machines-broad-cutt-vogel-charles-a-a-dellschau

https://www.google.ca/search?espv=2&q=charles+aa+dellschau&spell=1&sa=X&ved=0ahUKEwitnI-0mM3RAhVC22MKHUpPAvQQBQgZKAA&biw=1280&bih=667

Hamlet's Mill

https://en.wikipedia.org/wiki/Hamlet's_Mill ,
https://www.youtube.com/watch?v=PgHIuksuHQk

http://www.bibliotecapleyades.net/hamlets_mill/hamletmill.htm

http://www.incapabledesetaire.com/edito3/hamlet.pdf

https://www.google.ca/search?sourceid=chrome-psyapi2&ion=1&espv=2&ie=UTF-8&q=hamlet%27s%20mill%20pdf&oq=hamlets%20mill&aqs=chrome.2.69i57j0l5.9779j0j7

More John Titor BS?

https://www.youtube.com/playlist?list=PLA1pyjGPRDTIJ4OQsC6sTlpWDnPJqU6Ss

Tuesday, January 17, 2017

the-search-for-mh370-is-over

http://midnightinthedesert.com/the-search-for-mh370-is-over/

space...

https://en.wikipedia.org/wiki/Kennedy_Space_Center#Historical_programs

https://en.wikipedia.org/wiki/Space_Shuttle_Challenger

https://en.wikipedia.org/wiki/STS-6

https://en.wikipedia.org/wiki/Space_Shuttle_Challenger_disaster

https://upload.wikimedia.org/wikipedia/commons/4/4f/CSM-119_Skylab_Rescue.jpg ,

https://en.wikipedia.org/wiki/Canceled_Apollo_missions#Skylab_Rescue

https://upload.wikimedia.org/wikipedia/commons/2/2d/Shuttle_Carrier_Aircraft_N911NA_on_display_in_Palmdale%2C_California_in_June_2015.jpg ,
https://en.wikipedia.org/wiki/Shuttle_Carrier_Aircraft#Retirement

https://upload.wikimedia.org/wikipedia/commons/6/60/Shuttle_Enterprise_Flight_to_New_York_%28201204270023HQ%29.jpg

https://en.wikipedia.org/wiki/Canceled_Apollo_missions#Skylab_Rescue

https://en.wikipedia.org/wiki/Kennedy_Space_Center_Launch_Complex_39

dark energy

http://www.daviddarling.info/encyclopedia/D/dark_energy.html

Monday, January 16, 2017

Eugene Cernan

https://en.wikipedia.org/wiki/Eugene_Cernan

http://www.daviddarling.info/encyclopedia/C/Cernan.html

http://www.eaglelander3d.com/cernan.html

JPW

http://midnightinthedesert.com/joshua-p-warren

http://www.joshuapwarren.com

contact

Contact@JoshuaPWarren.com

monstrous-gator-filmed-in-florida

http://www.coasttocoastam.com/article/monstrous-gator-filmed-in-florida/

kyrgyzstan-blames-pilot-error-for-turkish-cargo-plane-crash

http://www.thestar.com.my/news/world/2017/01/17/kyrgyzstan-blames-pilot-error-for-turkish-cargo-plane-crash/

https://www.google.ca/search?q=plane+crash+in+Kyrgyzstan&espv=2&biw=1538&bih=738&source=lnms&sa=X&ved=0ahUKEwiw3fq6rMjRAhWIq1QKHa-MDV4Q_AUIBygA&dpr=1.25

ch of the gods

http://chariotsofthegods.com

incurable-bacteria-resist-nearly-antibiotics-continuing-spread-worldwide

http://midnightinthedesert.com/incurable-bacteria-resist-nearly-antibiotics-continuing-spread-worldwide/

flesh-eating-screwworms-reach-floridas-mainland

http://midnightinthedesert.com/flesh-eating-screwworms-reach-floridas-mainland/

https://www.theatlantic.com/science/archive/2017/01/screwworms-florida-mainland/512966/

wired .com/ matrix 2

https://www.wired.com/2003/05/matrix2/

mathematical-model-reveals-the-patterns-of-how-innovations-arise

Mathematical Model Reveals the Patterns of How Innovations Arise

The work could lead to a new approach to the study of what is possible, and how it follows from what already exists.

by Emerging Technology from the arXiv
January 13, 2017

Innovation is one of the driving forces in our world. The constant creation of new ideas and their transformation into technologies and products forms a powerful cornerstone for 21st century society. Indeed, many universities and institutes, along with regions such as Silicon Valley, cultivate this process.

And yet the process of innovation is something of a mystery. A wide range of researchers have studied it, ranging from economists and anthropologists to evolutionary biologists and engineers. Their goal is to understand how innovation happens and the factors that drive it so that they can optimize conditions for future innovation.

This approach has had limited success, however. The rate at which innovations appear and disappear has been carefully measured. It follows a set of well-characterized patterns that scientists observe in many different circumstances. And yet, nobody has been able to explain how this pattern arises or why it governs innovation.

Today, all that changes thanks to the work of Vittorio Loreto at Sapienza University of Rome in Italy and a few pals, who have created the first mathematical model that accurately reproduces the patterns that innovations follow. The work opens the way to a new approach to the study of innovation, of what is possible and how this follows from what already exists.

The notion that innovation arises from the interplay between the actual and the possible was first formalized by the complexity theorist Stuart Kauffmann. In 2002, Kauffmann introduced the idea of the “adjacent possible” as a way of thinking about biological evolution.

The adjacent possible is all those things—ideas, words, songs, molecules, genomes, technologies and so on—that are one step away from what actually exists. It connects the actual realization of a particular phenomenon and the space of unexplored possibilities.

But this idea is hard to model for an important reason. The space of unexplored possibilities includes all kinds of things that are easily imagined and expected but it also includes things that are entirely unexpected and hard to imagine. And while the former is tricky to model, the latter has appeared close to impossible.

What’s more, each innovation changes the landscape of future possibilities. So at every instant, the space of unexplored possibilities—the adjacent possible—is changing.

“Though the creative power of the adjacent possible is widely appreciated at an anecdotal level, its importance in the scientific literature is, in our opinion, underestimated,” say Loreto and co.

Nevertheless, even with all this complexity, innovation seems to follow predictable and easily measured patterns that have become known as “laws” because of their ubiquity. One of these is Heaps’ law, which states that the number of new things increases at a rate that is sublinear. In other words, it is governed by a power law of the form V(n) = knβ where β is between 0 and 1.

Words are often thought of as a kind of innovation, and language is constantly evolving as new words appear and old words die out.

This evolution follows Heaps’ law. Given a corpus of words of size n, the number of distinct words V(n) is proportional to n raised to the β power. In collections of real words, β turns out to be between 0.4 and 0.6.

Another well-known statistical pattern in innovation is Zipf’s law, which describes how the frequency of an innovation is related to its popularity. For example, in a corpus of words, the most frequent word occurs about twice as often as the second most frequent word, three times as frequently as the third most frequent word, and so on. In English, the most frequent word is “the” which accounts for about 7 percent of all words, followed by “of” which accounts for about 3.5 percent of all words, followed by “and,” and so on.

This frequency distribution is Zipf’s law and it crops up in a wide range of circumstances, such as the way edits appear on Wikipedia, how we listen to new songs online, and so on.

These patterns are empirical laws—we know of them because we can measure them. But just why the patterns take this form is unclear. And while mathematicians can model innovation by simply plugging the observed numbers into equations, they would much rather have a model which produces these numbers from first principles.

Enter Loreto and his pals (one of which is the Cornell University mathematician Steve Strogatz). These guys create a model that explains these patterns for the first time.

They begin with a well-known mathematical sand box called Polya’s Urn. It starts with an urn filled with balls of different colors. A ball is withdrawn at random, inspected and placed back in the urn with a number of other balls of the same color, thereby increasing the likelihood that this color will be selected in future.

This is a model that mathematicians use to explore rich-get-richer effects and the emergence of power laws. So it is a good starting point for a model of innovation. However, it does not naturally produce the sublinear growth that Heaps’ law predicts.

That’s because the Polya urn model allows for all the expected consequences of innovation (of discovering a certain color) but does not account for all the unexpected consequences of how an innovation influences the adjacent possible.

So Loreto, Strogatz, and co have modified Polya’s urn model to account for the possibility that discovering a new color in the urn can trigger entirely unexpected consequences. They call this model “Polya’s urn with innovation triggering.”

The exercise starts with an urn filled with colored balls. A ball is withdrawn at random, examined, and replaced in the urn.

If this color has been seen before, a number of other balls of the same color are also placed in the urn. But if the color is new—it has never been seen before in this exercise—then a number of balls of entirely new colors are added to the urn.

Loreto and co then calculate how the number of new colors picked from the urn, and their frequency distribution, changes over time. The result is that the model reproduces Heaps’ and Zipf’s Laws as they appear in the real world—a mathematical first. “The model of Polya’s urn with innovation triggering, presents for the first time a satisfactory first-principle based way of reproducing empirical observations,” say Loreto and co.

The team has also shown that its model predicts how innovations appear in the real world. The model accurately predicts how edit events occur on Wikipedia pages, the emergence of tags in social annotation systems, the sequence of words in texts, and how humans discover new songs in online music catalogues.

Interestingly, these systems involve two different forms of discovery. On the one hand, there are things that already exist but are new to the individual who finds them, such as online songs; and on the other are things that never existed before and are entirely new to the world, such as edits on Wikipedia.

Loreto and co call the former novelties—they are new to an individual—and the latter innovations—they are new to the world.

Curiously, the same model accounts for both phenomenon. It seems that the pattern behind the way we discover novelties—new songs, books, etc.—is the same as the pattern behind the way innovations emerge from the adjacent possible.

That raises some interesting questions, not least of which is why this should be. But it also opens an entirely new way to think about innovation and the triggering events that lead to new things. “These results provide a starting point for a deeper understanding of the adjacent possible and the different nature of triggering events that are likely to be important in the investigation of biological, linguistic, cultural, and technological evolution,” say Loreto and co.

We’ll look forward to seeing how the study of innovation evolves into the adjacent possible as a result of this work.

Ref: arxiv.org/abs/1701.00994: Dynamics on Expanding Spaces: Modeling the Emergence of Novelties

https://www.technologyreview.com/s/603366/mathematical-model-reveals-the-patterns-of-how-innovations-arise/

neuroscience-cant-explain-how-an-atari-works

The brain is complex—but when techniques developed to analyze how it works were applied to a chip running Donkey Kong, they were found lacking.

by Jamie Condliffe
January 12, 2017

When you apply tools used to analyze the human brain to a computer chip that plays Donkey Kong, can they reveal how the hardware works?

Many research schemes, such as the U.S. government’s BRAIN initiative, are seeking to build huge and detailed data sets that describe how cells and neural circuits are assembled. The hope is that using algorithms to analyze the data will help scientists understand how the brain works.

But those kind of data sets don’t yet exist. So Eric Jonas of the University of California, Berkeley, and Konrad Kording from the Rehabilitation Institute of Chicago and Northwestern University wondered if they could use their analytical software to work out how a simpler system worked.

They settled on the iconic MOS 6502 microchip, which was found inside the Apple I, the Commodore 64, and the Atari Video Game System. Unlike the brain, this slab of silicon is built by humans and fully understood, down to the last transistor.

The researchers wanted to see how accurately their software could describe its activity. Their idea: have the chip run different games—including Donkey Kong, Space Invaders, and Pitfall, which have already been mastered by some AIs—and capture the behavior of every single transistor as it did so (creating about 1.5 GB per second of data in the process). Then they would turn their analytical tools loose on the data to see if they could explain how the microchip actually works.

For instance, they used algorithms that could probe the structure of the chip—essentially the electronic equivalent of a connectome of the brain—to establish the function of each area. While the analysis could determine that different transistors played different roles, the researchers write in PLOS Computational Biology, the results “still cannot get anywhere near an understanding of the way the processor really works.”

Elsewhere, Jonas and Kording removed a transistor from the microchip to find out what happened to the game it was running—analogous to so-called lesion studies where behavior is compared before and after the removal of part of the brain. While the removal of some transistors stopped the game from running, the analysis was unable to explain why that was the case.

In these and other analyses, the approaches provided interesting results—but not enough detail to confidently describe how the microchip worked. “While some of the results give interesting hints as to what might be going on,” explains Jonas, “the gulf between what constitutes ‘real understanding’ of the processor and what we can discover with these techniques was surprising.”

It’s worth noting that chips and brains are rather different: synapses work differently from logic gates, for instance, and the brain doesn’t distinguish between software and hardware like a computer. Still, the results do, according to the researchers, highlight some considerations for establishing brain understanding from huge, detailed data sets.

First, simply amassing a handful of high-quality data sets of the brains may not be enough for us to make sense of neural processes. Second, without many detailed data sets to analyze just yet, neuroscientists ought to remain aware that their tools may provide results that don’t fully describe the brain’s function.

As for the question of whether neuroscience can explain how an Atari works? At the moment, not really.

https://www.technologyreview.com/s/603362/neuroscience-cant-explain-how-an-atari-works/?utm_campaign=internal&utm_medium=homepage&utm_source=top-stories_3&set=603368