Oahu #39;s North Shore Real Estate, Beaches More
A drive from Mokuleia (western part of North Shore) to Laie (eastern part of North Shore), showcasing real estate, beaches more. See homes for sale on Oahu...
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GTA V in Minecraft #26 | Beautiful beaches
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Box jellyfish along Kailua shores and beaches
A rare occurrence of box jellyfish found between Lanikai and Kalama Beach. Subscribe to KITV on YouTube now for more: http://bit.ly/1hxKwsa Get more Honolulu news: http://kitv.com Like...
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Astronomy - Ch. 4: History of Astronomy (16 of 16) The Giants of Astronomy: Albert Einstein
Visit http://ilectureonline.com for more math and science lectures! In this video I will some of the history, laws, and theories of Albert Einstein. First vi...
By: Michel van Biezen
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Astronomy - Ch. 4: History of Astronomy (16 of 16) The Giants of Astronomy: Albert Einstein - Video
Weve all been seeing hype and excitement around artificial intelligence, big data, machine learning and deep learning. Theres also a lot of confusion about what they really mean and whats actually possible today. These terms are used arbitrarily and sometimes interchangeably, which further perpetuates confusion.
So, lets break down these terms and offer some perspective.
Artificial Intelligence is a branch of computer science that deals with algorithms inspired by various facets of natural intelligence. It includes performing tasks that normally require human intelligence, such as visual perception, speech recognition, problem solving and language translation. Artificial intelligence can be seen in many every day products, from intelligent personal assistants in your smartphone to the X-box 360 Kinect camera, allowing you to interact with games through body movement. There are also well-known examples of AI that are more experimental, from the self-aware Super Mario to the widely discussed driverless car. Other less commonly discussed examples include the ability to sift through millions of images to pull together notable insights.
Big Data is an important part of AI and is defined as extremely large data sets that are so large they cannot be analyzed, searched or interpreted using traditional data processing methods. As a result, they have to be analyzed computationally to reveal patterns, trends, and associations. This computational analysis, for instance, has helped businesses improve customer experience and their bottom line by better understand human behavior and interactions. There are many retailers that now rely heavily on Big Data to help adjust pricing in near-real time for millions of items, based on demand and inventory. However, processing of Big Data to make predictions or decisions like this often requires the use of Machine Learning techniques.
Machine Learningis a form of artificial intelligence which involves algorithms that can learn from data. Such algorithms operate by building a model based on inputsand using that information to make predictions or decisions, rather than following only explicitly programmed instructions. There are lots of basic decisions that can be performed leveraging machine learning, like Nest with its learning thermostats as one example. Machine Learning is widely used in spam detection, credit card fraud detection, and product recommendation systems, such as with Netflix or Amazon.
Deep Learningis a class of machine learning techniques that operate by constructing numerous layers of abstraction to help map inputs to classifications more accurately. The abstractions made by Deep Learning methods are often observed as being human like, and the big breakthrough in this field in recent years has been the scale of abstraction that can now be achieved. This, in recent years, has resulted in breakthroughs in computer vision and speech recognition accuracy. Deep Learning is inspired by a simplified model of the way Neural Networks are thought to operate in the brain.
No doubt AI is in a hype cycle these days. Recent breakthroughs in Distributed AI and Deep Learning, paired with the ever-increasing need for deriving value from huge stashes of data being collected in every industry, have helped renew interest in AI. Unfortunately, along with the hype, there has also been much concern about the risks of AI. In my opinion, much of this concern is misplaced and unhelpful most of the concerns raised apply equally to technology in general, and just because this specific branch of technology is inspired by natural intelligence should not make it particularly more or less of a concern.
[Recently on Insights:The Upside of Artificial Intelligence Development|Google and Elon Musk to Decide What Is Good for Humanity]
As mortal humans, we do not understand the functionality of many of the technologies we use, and in this age of information, many decisions are already being made for us automatically by computers. If not understanding how these technologies around us work is concerning, then there is plenty to be concerned about before we start worrying about AI. The fact of the matter is that AI technologies already enable many of the products and services we know and love, so better to start understanding more about what these technologies are and how they work, than to believe in the Hollywood-style hype about futuristic scenarios.
When it comes to the potential of the recent AI breakthroughs, there is, in spite of the hype, much to be excited about. While there is a vast and growing amount of data available related to critical problems, it remains mostly unmined, unrefined and un-monetized. There is an inability to analyze and utilize available data to make intelligent, bias-free, decisions. Companies should be using refined data to make the right decisions and solve the worlds most vexing challenges. The speed and computing scale required to make advances in mission critical problem solving has not existed until now.
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01/25/15 RHM Peregrine Falcon Pair ID On Boeing Aerospace Bld. @ Kent, Wa
I created this video with the YouTube Video Editor (http://www.youtube.com/editor)
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The Ferrell Phelps Show Celebrating Black History Month in Houston Texas
The Ferrell Phelps Show with Author Dr. Florita Bell Griffin and the owner of Universal Elite Aerospace Pilot Kenneth E.Morris Learn more about our guest Dr. Florita Bell Griffin, Author ...
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The Ferrell Phelps Show Celebrating Black History Month in Houston Texas - Video
The QuickBird satellite designed and built by Ball Aerospace for DigitalGlobe de-orbited successfully last month after making 70,000 trips around the Earth during its more than 13 years on orbit.
QuickBird, which far exceeded its five-year design life, provided the highest resolution Earth imagery that was commercially available when it launched in October 2001. Ball Aerospace designed, fabricated, integrated and tested the total space segment consisting of a spacecraft bus and 61-centimeter imaging instrument aboard the pioneering satellite. Ball and DigitalGlobe have continued to team on three additional remote sensing satellites with advanced capabilities: WorldView-1, WorldView-2 and WorldView-3.
QuickBird was our first venture into the commercial spacecraft market, and became the basis for the development and maturation of a string of highly successful Ball commercial spacecraft and instruments, said Cary Ludtke, vice president and general manager for Balls Operational Space business unit. QuickBird demonstrates the longevity and reliability of spacecraft and instruments built by Ball in the fixed-price market.
A firm, fixed-price spacecraft, QuickBird used the Ball Commercial Platform 2000 to capture 61 centimeter (black and white) and 2.4 meter multispectral (color) digital images of Earth's surface. QuickBird circled the globe 450 km (about 280 miles) above Earth while the Ball high-resolution camera gathered images of the Earth's surface during daylight hours. The world-class images have contributed significantly to mapping, agricultural and urban planning, weather research and military surveillance.
Ball Aerospace & Technologies Corp. supports critical missions for national agencies such as the Department of Defense, NASA, NOAA and other U.S. government and commercial entities. The company develops and manufactures spacecraft, advanced instruments and sensors, components, data exploitation systems and RF solutions for strategic, tactical and scientific applications. Ball continues to invest and innovate in affordable, high resolution imaging systems, contributing to the needs of civil, military and commercial customers. For more information, visit http://www.ballaerospace.com/.
Ball Corporation (NYSE: BLL) supplies innovative, sustainable packaging solutions for beverage, food and household products customers, as well as aerospace and other technologies and services primarily for the U.S. government. Ball Corporation and its subsidiaries employ 14,500 people worldwide and reported 2014 sales of $8.6 billion. For more information, visit http://www.ball.com, or connect with us on Facebook or Twitter.
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Ball Aerospace's QuickBird Retired from DigitalGlobe Remote Sensing Constellation
Comparing health insurance plans whether signing up through Healthcare.gov or weighing employer-sponsored plans with a spouse can feel like wading through a sea of information on deductibles, co-payments and monthly premiums. Now that more than 11 million people have chosen a plan during this years Healthcare.gov enrollment period, which ended on Feb. 15, three experts are pondering how to make this intimidating task even easier for next years registrants? They have laid out their prescription for improving the health insurance marketplace, grounded in psychology and behavioral research, in a perspective published Wednesday in the New England Journal of Medicine.
This is a really complicated decision to make and a pretty high-stakes one, too -- it can mean a lot of money, Peter Ubel, a co-author and health marketing expert at Duke University, says. I think a better designed system would actually be faster to go through and yet still help you make a better decision.
In the existing marketplace, the authors dont like the way plans are sorted into gold, silver and bronze categories.They think these labels make the gold plans inherently more desirable. The team did a preliminary test of this theory by presenting a choice of two plans to public bus riders in North Carolina one offering lower monthly premiums but higher out-of-pocket costs than the other and alternately labeled them gold and bronze. Inevitably, more than half of riders chose the gold plan, no matter if it had the higher or lower premiums and deductibles.
These subtle cues inherent in the labels and layout of the current marketplace may prompt consumers to make a decision that is not in their best interests. Now that we've made health insurance accessible in a legal sense, we have to make it accessible in a behavioral sense, Douglas Hough, a health economist at Johns Hopkins School of Public Health who was not involved in the research, says.
Another issue: Many state exchanges rank plans by monthly premium and list the plans with the lowest monthly premiums at the top. Ubel and his co-authors, who include a behavioral scientist from the University of Stirling in the U.K. and a business professor from Columbia University, say this strategy could cause a disproportionate number of people to choose the first plan, citing research that shows a tendency for consumers to choose the wine that is listed first on a curated menu. Arranging plans by deductibles or the number of doctors and hospitals covered may prompt consumers to pick plans in an entirely different pattern, a theory that Ubel says should be tested.
Hough thinks the health insurance marketplace software should play a more active role in aiding consumer decisions by offering suggestions based on their searches or the way other registrants have acted. Given the complexity, I think people are looking for heuristics, rules of thumb -- they're looking for a guide, he says. His vision would look more like Amazon.com. People who bought this have also bought that, people who looked at this have also looked at that, he says. Or, the interface might work like TurboTax in asking a series of simple questions meant to steer consumers in the right direction.
Since the early technological woes of the Healthcare.gov rollout have largely been overcome, Ubel hopes the Department of Health and Human Services, as well as the agencies that oversee state exchanges, can finally start to speak with behavioral researchers and apply some of these principles. I actually talked to a couple of groups when they were designing the exchanges to see if they wanted free consultation, he says. I had great preliminary phone calls but they were too busy to get back to me, which I understand.
Hough cautions that while behavioral scientists may be able to lend some insight into this process, they cant be expected to provide all the answers. One of the dangers of behavioral economics is people get really excited for it and start applying it willy-nilly without recognizing that there's a lot of things we don't know, he says. We know what the solutions are conceptually, but not really at the ground floor where we really need to make the changes.
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Obama's Healthcare.gov Website Isn't Consumer-Friendly Enough, Experts Say
In a new paper, a group of MIT researchers argue that science is producing PhDs in far greater numbers than there are available tenured jobs for them to fill.
The authors, engineers Richard C. Larson, Navid Ghaffarzadegan, and Yi Xue, start out by noting that
The academic job market has become more and more competitive nowadays, less than 17% of new PhDs in science, engineering and health-related fields find tenure-track positions within 3 years after graduation.
But why? Are we simply producing too many PhDs nowadays? Larson et al. approach this question by borrowing a concept from epidemiology: R0 (R nought), known as the basic reproduction number. In the context of an infectious disease, R0 is the average number of people who are newly infected by the disease by each existing patient. Influenza, for example, has an R0 of about 1.2 1.6. If R0 is greater than 1, the disease will spread exponentially.
Larson et al. define the academic R0 as the total number of PhD graduates created by (supervised by) the average tenure-track academic (i.e professor) over the course of the professors career. If this number is greater than 1, more PhDs will be created than there are tenured posts for them all to occupy assuming that the number of tenured professors is roughly constant.
It turns out that the R0 at MIT is approximately 10. MIT produces some 500 PhDs per year, and it has 1000 faculty. So each faculty member produces 0.5 students per year. Since the average faculty members career at MIT spans 20 years, each faculty member produces 10 PhDs in total.
By using the same approach, Larson et al. say that the R0 across the whole field of engineering in the USA is 7.8. But this varies across specialties. Mining and Architectural Engineering both have a sustainable R0 of just 1, while Environmental Engineering (ironically) is the gas-guzzler of the bunch, with an R0 of 19.
Larson et al. conclude that
Our back-of-the-envelope calculations suggest that R0 for the entire engineering field is 7.8, which implies that in a steady state, only 1/7.8 (i.e. 12.8%) of PhD graduates in engineering can attain academic positions in the USA the system in many places is saturated.
In demography, any living population eventually meets a ceiling of limited resources. Similarly in academia, the growing PhD population will eventually hit the natural ceiling of limited tenure-track positions. In some fields, it already has hit that limit the oversupply must move to nonacademic positions or be underemployed in careers that require lesser degrees.
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Does Science Produce Too Many PhD Graduates?
Denver, COLO (PRWEB) February 18, 2015
C. Thomas Howard, Ph.D., thought leader on Behavioral Investing debuts his second book this month, published and released by Harriman House. His first book Behavioral Portfolio Management, released in 2014 details his insights from years of research on Behavioral Investing and explains how investment professionals can harness price distortions driven by emotional crowds to create superior portfolios. Dr. Howards newest book The New Value Investing: How to Apply Behavioral Finance to Stock Valuation Techniques and Build a Winning Portfolio, applies the Behavioral Finance lens to value investing. His goal is to help investors identify undervalued stocks and build their own successful value investing portfolio.
It is important to understand that value investing is inextricably linked with Behavioral Finance, and research advances in this area in recent years strengthen the case for value investing, says Dr. Howard. If investors have a system of identifying stocks for their portfolio, it helps to remove the emotion from the investing process which is crucial to their success. This book helps them strengthen their system.
Howard explains how stock prices are determined by emotional crowds, how this leads to mispriced stocks and opportunities for the value investor, and how an investor can harness the insights of Behavioral Finance to improve their value investing approach. He skillfully shows in the book how to follow the path from analysis of the economy, to the industry, to company financial statements, to creating a value range for a companys stock. He even includes two complete worked examples of stock valuation for real-life companies.
Dr. Howards newest book draws upon decades of academic research and many years of successfully managing portfolios with a Behavioral Portfolio Management approach. Manager of the award-winning Athena Pure Valuation | Profitability Portfolio, Howard uses his expertise to give readers a glimpse into the decision making process of a value-oriented manager and the discipline and patience thats necessary to produce successful results. The key is patience, comments Howard. Not everyone is a value-oriented investor, but for those that follow the approach, this book should prove an invaluable resource.
About the Author: C. Thomas Howard is co-founder of AthenaInvest, a Greenwood Village-based SEC Registered Investment Advisor. He led the research project that resulted in Behavioral Portfolio Management, the methodology which underlies AthenaInvest's investment approach. He oversees Athena's ongoing research which has led to a number of patents, publication of his research and many speaking engagements at industry conferences. Dr. Howard currently serves as CEO, Director of Research, and Chief Investment Officer at AthenaInvest.
Thomas Howard is also a Professor Emeritus at the Reiman School of Finance, Daniels College of Business, University of Denver, where for over 30 years he taught courses and published articles in the areas of investment management and international finance. Professor Howard holds a BS in mechanical engineering from the University of Idaho, an MS in management science from Oregon State University, and a Ph.D. in finance from the University of Washington. His thought leadership in Behavioral Portfolio Management has generated significant interest across the country with his articles being some of the most widely read on industry and academic websites.
For media inquiries requesting more information on AthenaInvest, please contact Pamela Saunders at (415) 254-7169. For financial professionals requesting more information, please visit http://www.AthenaInvest.com or call (877) 430-5675.
Book available on Amazon.com and BarnesandNoble.com.
Headquartered in Greenwood Village, Colorado, AthenaInvest is a SEC Registered Investment Advisor. Please visit http://www.athenainvest.com for additional information. 2015 by AthenaInvest, Inc. All Rights Reserved Protected by US Patents 7734526, 8352347, 8694406 and Singapore Patents 150371 and184692.
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C. Thomas Howard of AthenaInvest Releases Second Book: The New Value Investing
Skin Science - The New Key to Anti-Aging Medicine - Professor Adiel Tel-Oren
Skin Science - The New Key to Anti-Aging Medicine by Professor Adiel Tel-Oren, MD, DC, DABFM, DABCN, CCN, LN, presented on January 15, 2015. What does the ne...
By: Silicon Valley Health Institute
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Skin Science - The New Key to Anti-Aging Medicine - Professor Adiel Tel-Oren - Video
Final Fantasy 7 CENSORED - Bad Language/Swearing Dialogue- Video Game Censorship
Did you know PC versions of Final Fantasy 7 (7) censor some of the dialogue? In the PC versions of FF7, some of the bad language and swearing is actually censored!...
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Final Fantasy 7 CENSORED - Ending Cutscene Movie - Video Game Censorship
Did you know the 1998 PC version of Final Fantasy 7 (7) censor the ending #39;s cutscene movie? In the 1998 PC version of FF7, Cid Highwind swearing with the word...
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Crime Fighters CENSORED - Level 2 #39;s Woman #39;s Ass Poster - Video Game Censorship
Did you know non-Japanese versions of Crime Fighters () censor a poster during level 2? In the Japanese version of Crime Fighters, the poster of a female #39;s ass...
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Crime Fighters CENSORED - Level 2's Woman's Ass Poster - Video Game Censorship - Video
Crime Fighters CENSORED - Level 6 #39;s Woman #39;s Lips Poster - Video Game Censorship
Did you know non-Japanese versions of Crime Fighters () censor a poster during level 6? In the Japanese version of Crime Fighters, the poster of a woman #39;s lips...
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Crime Fighters CENSORED - Level 6's Woman's Lips Poster - Video Game Censorship - Video
Crime Fighters CENSORED - Humping Skimpy Leather Enemy - Video Game Censorship
Did you know non-Japanese versions of Crime Fighters () censor an enemy? In the Japanese version of Crime Fighters, there #39;s actually a enemy wearing skimpy leather...
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Resident Evil 2 CENSORED - Player Death Scenes/Animations - Video Game Censorship
Did you know the Japanese version of Resident Evil 2 censor the player #39;s death scenes/animations? In the JP version of RE2, the screen actually fades to black right after dying - censoring...
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Breath Of Fire 4 CENSORED - Fou-Lu Decapitating Emperor Soniel - Video Game Censorship
Did you know non-Japanese versions of Breath Of Fire 4 ( 4) censor Emperor Soniel #39;s death? In the JP version of BoF4, Fou-Lu is shown actually decapitating Emperor...
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Breath Of Fire 4 CENSORED - Fou-Lu Decapitating Emperor Soniel - Video Game Censorship - Video