How Fast Can the Wind Be in the Atmosphere of Saturn? : Astronomy & the Solar System – Video

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How Fast Can the Wind Be in the Atmosphere of Saturn? : Astronomy the Solar System
Subscribe Now: http://www.youtube.com/subscription_center?add_user=ehoweducation Watch More: http://www.youtube.com/ehoweducation Saturn has really violent w...

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How Fast Can the Wind Be in the Atmosphere of Saturn? : Astronomy & the Solar System - Video

Unprecedented 16-year study tracks stars orbiting Milky Way black hole – Video

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Unprecedented 16-year study tracks stars orbiting Milky Way black hole
Astronomy - Secrets of the Universe Revealed: Unprecedented 16-year study tracks stars orbiting Milky Way black hole In this second episode of the ESOcast Dr...

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Unprecedented 16-year study tracks stars orbiting Milky Way black hole - Video

The Major Theoretical Blunders That Held Back Progress In Modern Astronomy

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Here's the deal on 'scientific consensus' -- it's not always right, but it is the best guess at the time, supported by the majority of the evidence by smart people who know the subject.

You're right, and I agree that it's generally a safe bet to go with the "scientific consensus."

The issue is that a lot of people (including around here) seem to subscribe to what I'd say is a relatively naive form of logical positivism [wikipedia.org] , otherwise known as that sitcom hit "Everybody Loves Popper." I love Popper [wikipedia.org] too, but Popper's mechanisms to explain scientific progress are a little muddy. According to the naive idea of falsifiability, all scientific theories have to "falsifiable" and theoretically all open to be disproved by superior evidence at any time. The problem with this idea of science is that it doesn't specify how one actually progresses -- how do we choose our research from an infinite number of possible falsifiable statements?

The reality of scientific progress is that real science doesn't always work that way, and in fact no real philosophers of science today tend to think it does. Just to rehash the bits that happened 50 years ago, you have Kuhn's ideas [wikipedia.org] of "scientific revolutions" caused by shifts in research "paradigms," and responses by intelligent philosophers of science, such as Imre Lakatos's cool idea of "research programs [wikipedia.org] .

The point is, the real trajectory of scientific progress is "bumpy," and it needs to be. If everyone were ready to throw out every fundamental theory of science immediately when the slightest bit of new evidence comes along, we'd never be focused enough to do research on specific questions and make further progress. That's where most of science happens -- in fleshing out details of larger theories that are assumed to be true.

Anything else is more likely, not certainly, but more likely, to be wrong.

Yes -- and the times when the "scientific consensus" is actually less likely to be right can uncover some interesting elements about how science works, and can lead to some reasonable critiques. There were long stretches of time historically when the "scientific consensus" was actually "more likely to be wrong" on specific questions by a modern evaluation of the evidence, even assuming the knowledge of the day. But many of these times of disagreement pushed researchers on the other side to pursue evidence of the new theories even more strongly -- thus, arguably, leading to a stronger new scientific consensus on more firm ground once the "paradigm shift" occurred.

People tend to get very nervous when confronted with a "scientific consensus" that was proven wrong, particularly ones that hung around for decades (or, in a few cases, for centuries) even in the face of contrary evidence. But this is a necessary part of the messiness that forms the process of discovery.

It's kind of like having a debate without defining the fundamental terms under discussion. Until those are defined, meaningful debate can't happen. But in the process of debate, we sometimes might come to the conclusion that our initial definitions were inaccurate, or even that perhaps the disagreement can only be resolved by choosing new or different terms. That doesn't mean that the process of debate is necessarily flawed -- if we never started out with our initial terms, we'd never have been able to start making the kinds of distinctions that allowed progress to happen.

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The Major Theoretical Blunders That Held Back Progress In Modern Astronomy

Kickstarting the Youngest Astronomers with Universe in a Box

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Want to stay on top of all the space news? Follow @universetoday on Twitter

Children enjoy a view through a telescope at an astronomy event in Rochester, Illinois. Photo by Nancy Atkinson.

Most children are naturally interested in science. And if youve ever heard a five-year-old recite complicated dinosaur names, or all the planets in the Solar System (possibly with a passionate plea on behalf of poor Pluto!), you will know that when it comes to children and science, dinosaurs and astronomy lead the field.

I dont know about paleontologists, but astronomers are investing serious time and effort to build on childrens fascination with the universe. Probably the most successful program of this kind is Universe Awareness (UNAWE), aimed at bringing astronomy to children aged 4 to 10 and in particular to children in underprivileged communities. To help teachers and educators bring astronomy to their kindergarten and elementary school classrooms, UNAWE created a teaching kit: Universe in a Box, with materials for over 40 age-appropriate astronomy-related activities.

UNAWE has built 1,000 of these boxes, subjected them to intensive field-testing in classrooms around the world, and have now begun a kickstarter campaign to raise (at least) $15,000 to ship many of the boxes to underprivileged communities around the world, and to provide training for teachers and educators on how to use the boxes to maximum effect. Heres what they have to say:

I freely admit to being biased I work at Haus der Astronomie, a center for astronomy education and outreach in Germany, where Cecilia Scorza and Natalie Fischer, two astronomers-turned-outreach-scientists, developed the precursor for Universe in a box, including many of the hands-on activities (in cooperation with the local volunteer association Astronomieschule e.V., to give credit where its due). And Im proud that George Miley, Pedro Russo and the UNAWE team (which includes Cecilia and Natalie) have taken this idea and turned it into a truly global resource. Ive seen the Universe in a box work its magic (pardon: its science) on numerous children whove come to visit our center and have heard many good things from educators around the world who are using the box.

So please help the UNAWE team to get the boxes where they belong out into the classrooms! Also, help them help teachers and educators to make optimal use of the boxes.

The kickstarter currently stands at a bit over $8,000 of their $15,000 goal. It runs until Tuesday, June 10, 2014, at 5 am EDT.

Heres the kickstarter link again.

Markus Pssel is a theoretical physicist turned astronomical outreach scientist. He is the managing scientist at the Centre for Astronomy Education and Outreach a Haus der Astronomie in Heidelberg, Germany.

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Kickstarting the Youngest Astronomers with Universe in a Box

BRS Labs’ AISight Revolutionizes SCADA With World’s First Behavioral Recognition Analytics Platform – Video

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BRS Labs #39; AISight Revolutionizes SCADA With World #39;s First Behavioral Recognition Analytics Platform
Award-winning artificial intelligence system enables SCADA operators to recognize threats in real time and respond before alarm conditions have been met http://www.businesswire.com/news/home/20140...

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BRS Labs' AISight Revolutionizes SCADA With World's First Behavioral Recognition Analytics Platform - Video

Free Your Mind to Shine Radio: "Adventures Into Reality Pt. 1" w / Andrew Bartzis – Video

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Free Your Mind to Shine Radio: "Adventures Into Reality Pt. 1" w / Andrew Bartzis
In this 1st part of the 3 part series "Adventures Into Reality," Galactic Historian, Andrew Bartzis breaks down many different topics including: - "CERN" which is the dimensional teleport...

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Free Your Mind to Shine Radio: "Adventures Into Reality Pt. 1" w / Andrew Bartzis - Video

Artificial Intelligence – University of Washington

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David L. Waltz Vice President, Computer Science Research NEC Research Institute Bringing Common Sense, Expert Knowledge, and Superhuman Reasoning to Computers

Artificial Intelligence (AI) is the key technology in many of today's novel applications, ranging from banking systems that detect attempted credit card fraud, to telephone systems that understand speech, to software systems that notice when you're having problems and offer appropriate advice. These technologies would not exist today without the sustained federal support of fundamental AI research over the past three decades.

Although there are some fairly pure applications of AI -- such as industrial robots, or the IntellipathTM pathology diagnosis system recently approved by the American Medical Association and deployed in hundreds of hospitals worldwide -- for the most part, AI does not produce stand-alone systems, but instead adds knowledge and reasoning to existing applications, databases, and environments, to make them friendlier, smarter, and more sensitive to user behavior and changes in their environments. The AI portion of an application (e.g., a logical inference or learning module) is generally a large system, dependent on a substantial infrastructure. Industrial R&D, with its relatively short time-horizons, could not have justified work of the type and scale that has been required to build the foundation for the civilian and military successes that AI enjoys today. And beyond the myriad of currently deployed applications, ongoing efforts that draw upon these decades of federally-sponsored fundamental research point towards even more impressive future capabilities:

In a 1977 article, the late AI pioneer Allen Newell foresaw a time when the entire man-made world would be permeated by systems that cushioned us from dangers and increased our abilities: smart vehicles, roads, bridges, homes, offices, appliances, even clothes. Systems built around AI components will increasingly monitor financial transactions, predict physical phenomena and economic trends, control regional transportation systems, and plan military and industrial operations. Basic research on common sense reasoning, representing knowledge, perception, learning, and planning is advancing rapidly, and will lead to smarter versions of current applications and to entirely new applications. As computers become ever cheaper, smaller, and more powerful, AI capabilities will spread into nearly all industrial, governmental, and consumer applications.

Moreover, AI has a long history of producing valuable spin-off technologies. AI researchers tend to look very far ahead, crafting powerful tools to help achieve the daunting tasks of building intelligent systems. Laboratories whose focus was AI first conceived and demonstrated such well-known technologies as the mouse, time-sharing, high-level symbolic programming languages (Lisp, Prolog, Scheme), computer graphics, the graphical user interface (GUI), computer games, the laser printer, object-oriented programming, the personal computer, email, hypertext, symbolic mathematics systems (Macsyma, Mathematica, Maple, Derive), and, most recently, the software agents which are now popular on the World Wide Web. There is every reason to believe that AI will continue to produce such spin-off technologies.

Intellectually, AI depends on a broad intercourse with computing disciplines and with fields outside computer science, including logic, psychology, linguistics, philosophy, neuroscience, mechanical engineering, statistics, economics, and control theory, among others. This breadth has been necessitated by the grandness of the dual challenges facing AI: creating mechanical intelligence and understanding the information basis of its human counterpart. AI problems are extremely difficult, far more difficult than was imagined when the field was founded. However, as much as AI has borrowed from many fields, it has returned the favor: through its interdisciplinary relationships, AI functions as a channel of ideas between computing and other fields, ideas that have profoundly changed those fields. For example, basic notions of computation such as memory and computational complexity play a critical role in cognitive psychology, and AI theories of knowledge representation and search have reshaped portions of philosophy, linguistics, mechanical engineering and, control theory.

By the early 1980's an "expert systems" industry had emerged, and Japan and Europe dramatically increased their funding of AI research. In some cases, early expert systems success led to inflated claims and unrealistic expectations: while the technology produced many highly effective systems, it proved very difficult to identify and encode the necessary expertise. The field did not grow as rapidly as investors had been led to expect, and this translated into some temporary disillusionment. AI researchers responded by developing new technologies, including streamlined methods for eliciting expert knowledge, automatic methods for learning and refining knowledge, and common sense knowledge to cover the gaps in expert information. These technologies have given rise to a new generation of expert systems that are easier to develop, maintain, and adapt to changing needs.

Today developers can build systems that meet the advanced information processing needs of government and industry by choosing from a broad palette of mature technologies. Sophisticated methods for reasoning about uncertainty and for coping with incomplete knowledge have led to more robust diagnostic and planning systems. Hybrid technologies that combine symbolic representations of knowledge with more quantitative representations inspired by biological information processing systems have resulted in more flexible, human-like behavior. AI ideas also have been adopted by other computer scientists -- for example, "data mining," which combines ideas from databases, AI learning, and statistics to yield systems that find interesting patterns in large databases, given only very broad guidelines.

Authorizing Financial Transactions

Credit card providers, telephone companies, mortgage lenders, banks, and the U.S. Government employ AI systems to detect fraud and expedite financial transactions, with daily transaction volumes in the billions. These systems first use learning algorithms to construct profiles of customer usage patterns, and then use the resulting profiles to detect unusual patterns and take the appropriate action (e.g., disable the credit card). Such automated oversight of financial transactions is an important component in achieving a viable basis for electronic commerce.

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Artificial Intelligence - University of Washington

Breakthrough shows how DNA is ‘edited’ to correct genetic diseases

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PUBLIC RELEASE DATE:

26-May-2014

Contact: Philippa Walker 44-117-928-8086 University of Bristol

An international team of scientists has made a major step forward in our understanding of how enzymes 'edit' genes, paving the way for correcting genetic diseases in patients.

Researchers at the Universities of Bristol, Mnster and the Lithuanian Institute of Biotechnology have observed the process by which a class of enzymes called CRISPR pronounced 'crisper' bind and alter the structure of DNA.

The results, published in the Proceedings of the National Academy of Sciences (PNAS) today, provide a vital piece of the puzzle if these genome editing tools are ultimately going to be used to correct genetic diseases in humans.

CRISPR enzymes were first discovered in bacteria in the 1980s as an immune defence used by bacteria against invading viruses. Scientists have more recently shown that one type of CRISPR enzyme Cas9 can be used to edit the human genome - the complete set of genetic information for humans.

These enzymes have been tailored to accurately target a single combination of letters within the three billion base pairs of the DNA molecule. This is the equivalent of correcting a single misspelt word in a 23-volume encyclopaedia.

To find this needle in a haystack, CRISPR enzymes use a molecule of RNA - a nucleic acid similar in structure to DNA. The targeting process requires the CRISPR enzymes to pull apart the DNA strands and insert the RNA to form a sequence-specific structure called an 'R-loop'.

The global team tested the R-loop model using specially modified microscopes in which single DNA molecules are stretched in a magnetic field. By altering the twisting force on the DNA, the researchers could directly monitor R-loop formation events by individual CRISPR enzymes.

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Breakthrough shows how DNA is 'edited' to correct genetic diseases

Opening remarks by Chairman of the Military Committee – NATO Chiefs of Defence Meeting, 22 MAY 2014 – Video

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Opening remarks by Chairman of the Military Committee - NATO Chiefs of Defence Meeting, 22 MAY 2014
Opening statement by the Chairman of the NATO Military Committee, 22 May 2014. More from the event: http://goo.gl/jJ43rd.

By: NATO

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Opening remarks by Chairman of the Military Committee - NATO Chiefs of Defence Meeting, 22 MAY 2014 - Video

NATO Secretary General with Prime Minister of the former Yugoslav Republic of Macedonia – Video

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NATO Secretary General with Prime Minister of the former Yugoslav Republic of Macedonia
Remarks by NATO Secretary General Anders Fogh Rasmussen at the joint press point with the Prime Minister of the former Yugoslav Republic of Macedonia, Nikola Gruevski. 1. Turkey recognises...

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NATO Secretary General with Prime Minister of the former Yugoslav Republic of Macedonia - Video