Exploring mainly Heterodox type Economics, Monetary Reform, Environmental Sustainability, and Climate Change. It is a resource of Internet articles, and also promotes awareness of a futuristic modern universal Paradigm known as TFE, or Transfinancial Economics which is probably the most advanced, and most "scientific" form of Economics in the world .
The following is from part of an interesting site, and gives some data on Transfinancial Economics originating from the Kheper site. Unfortunately, this specific data may be removed as it is an old version of the same subject. The most authorative, and accurate page for TFE originates on the following link at the present time. http://www.p2pfoundation.net/Transfinancial_Economics
Freedom is a possession of inestimable value. Marcus Tullius Cicero
Our monetary woes are not going to go away by themselves. One thing is certain, they will go away. The question is only how and when. The number one cause of all the worlds troubles is us. You and me. It has to do with the monetary system. Not our monetary system, the monetary system. This idea is as easy to accept as it is to prove. Lets say I want to play Doug's game. So I make up the rules for Doug's game and try to attract people to play. What makes Doug's game a hit? A success? Players. I need players. Every game that is being played today requires consent and participation from the players. Without it, there is no game. It can't go anywhere.
It's easy to think that the monetary troubles on earth are extremely complicated and that my simple comparison doesn't really hold true. It does. There is nothing complicated in getting out of the mess we're in. It's very, very simple. It's not that the monetary system needs fixed. It needs to end. The idea that we need money or exchange systems to live is silly. The creators of the game can't afford for this thinking to surface. Surface is the right term. The idea is there, it just needs to come to our full awareness. The rule makers will kill anyone who attempts to bring this idea to it's full state of conscious awareness. I don't say this without a complete understanding of the rule makers. You can see the proof anywhere that someone is putting together a different game. Anywhere the threat, to the monetary game, becomes viable, people die. Anywhere the rules of the game are not being followed people are being killed. The other places that people are being killed is in those places where people want to stop playing the game. Also people will die so the game can be played where they were previously "in the way". If a place isn't serving the games purpose it gets killed. So it's not the rules that need modified. It's not that the system needs improvements. The system needs to end. The game must stop. There is only one way this will happen. The players must stop playing.
How do we stop playing? Have you all read the hundredth monkey story? If not search it and read it. Make sure you get the entire story. There is more than just the monkeys. It is an illustration in the relationship we have to each other at the conscious level. You will read that when a certain amount of people know something, all of a sudden everybody will know it. Knowing the way this works what do we need to do to change the world? When a certain amount of people "wake up" the rest will be awake. We could make this our game. I'll give an example of how this game works on the negative side. Actually as soon as I do you'll see so many examples it will astound you. "The difficulties in feeding the worlds populace." That's the negative idea. This idea has been fed into our brains over and over. As it is accepted it gets harder and harder to end starvation. The farmers disappear. Real food is being replaced by engineered product. Land is being destroyed so no food will grow on it. The list goes on and on. Why? Because people have accepted the idea. Do the rule makers understand the concept of the accepted idea? They may be stupid, but they're not stupid. In other words they have a very keen understanding of what makes us tick. They take this understanding and do stupid things with it. So here is the question - do you think that it's hard to feed the world? If you do, then you are working to make starvation a reality. You are fully immersed in a game of unconsciousness.
With that in mind here's the next experiment. "Do we think we need a monetary system?" If we accept that we do, then we are destined to have one. The preceding sentence reveals everything you'll ever need to know about destiny. We will have everything we have now as long as we think that it's hard to - not have it. That, in a nutshell, is the game we're playing. It's a hideous game we all play on the people of the world, ourselves included. It's the "it's hard game". One other destructive game we've been swept up in is the "someone will save us game". Here is a fact: we will save ourselves or we will be extinct. We can never save ourselves by playing the game that leads to our destruction. So how do we put an end to it? How do we put an end to world suffering? We see the possibility of something different. There is something I have written about a lot on my site. This is the concept of being convinced. It is this: nothing happens for us until we are convinced that it needs to happen. Nothing changes for us until we are convinced of the need for change. We can only change things if we know what those things are. We can only change them by addressing cause. We have to find cause. Then we can be successful and deal realistically with what we want to change. Then we can change our lives. Likewise we can change the world if we first recognize what needs to be changed. Once we're convinced of this we must be convinced that it's possible. In order to become convinced that it's possible we must understand cause. If we don't understand and deal with things at the causal level we as a race, here on earth, will be extinct. The cause of the worlds trouble is this: we see it as a fact of life. A natural product of life. This idea is being generated. It's part of the game. As hard as it seems to swallow we are killing ourselves with ideas that will only kill us once we voluntarily accept them. We must agree to our own demise. Is that not the height of craziness? All these ridiculous ideas need to be discarded. If they aren't, they will destroy us. We will destroy ourselves with them. We must be convinced, now, that our acceptance of ideas causes destruction. It doesn't matter where the ideas originated. ( but it is something we might all be interested in ) It has now become our idea. It is then, ours to be rid of. Our responsibility. We are responsible for the outcome of humanity. This is possibly a little overwhelming. It doesn't have to be. Our part, as individuals, isn't hard.
In fact like everything else that is real it's pretty simple. We must get the idea that a monetary system is necessary out of our heads. The other idea that we must be convinced of is this: as soon as enough people believe this it will change. As soon as that magic number of individuals sees this clearly it will go very rapidly. It will just sweep through the rest of the consciousness. That's how it works.
Financial amnesia (video) On 9/10/01 the Bush Administration announced that the Pentagon had lost $2.3 trillion.
Then they spent $3 trillion (or more) on the "War on Terror" including the disaster in Iraq. Now, as they're heading out the door, they've instructed the Fed to throw another few trillion on the fire. Is anyone keeping track? This is starting to add up to real money.
Our money system is not what we have been led to believe. The creation of money has been "privatized," or taken over by a private money cartel. Except for coins, all of our money is now created as loans advanced by private banking institutions - including the private Federal Reserve. Banks create the principal but not the interest to service their loans. To find the interest, new loans must continually be taken out, expanding the money supply, inflating prices - and robbing you of the value of your money.
Not only is virtually the entire money supply created privately by banks, but a mere handful of very big banks is responsible for a massive investment scheme known as "derivatives," which now tallies in at hundreds of trillions of dollars. The banking system has been contrived so that these big banks always get bailed out by the taxpayers from their risky ventures, but the scheme has reached its mathematical limits. There isn't enough money in the entire global economy to bail out the banks from a massive derivatives default today. When the investors realize that the "insurance" against catastrophe that they have purchased in the form of derivatives is worthless, they are liable to jump ship and bring the whole shaky edifice crashing down.
Web of Debt unravels the deceptions in our money scheme and presents a crystal clear picture of the financial abyss towards which we are heading. Then it explores a workable alternative, one that was tested in colonial America and is grounded in the best of American economic thought, including the writings of Benjamin Franklin, Thomas Jefferson and Abraham Lincoln.
Introduction: The summary found here gives one a basic overview of Trans-financial Economics, or TFE which then leads on to a more detailed essay, or "paper". It should just take a few minutes to read for those pressed for time. However, it should be noted that it comes after a short summary of Positive Human Politics, or PHP. Like TFE it is a research, and development project but no detailed essay, or "paper" follows it. Essentially, PHP is the basic political background of our main subject matter. One can skip it if desired, and go straight to the summary on TFE.
Also, a short list of references are placed right at the end of this presentation. Alot more may be added at some future date.
Positive Human Politics
, or PHP/ The Basic Summary preceding Trans-financial Economics Overview. Positive Human Politics, or PHP can be seen as the Modern Universal "Paradigm". Like TFE it is neither right-wing, or left-wing in approach but simply creates a basic trans formative humanitarian framework. In it realistic, civilized,and progressive solutions, or options are presented. It seeks for the popularization of such notions to largely replace negative thinking, and general apathy on all things political.
Most of the major ideas for PHP already exist under different terms, and tend to vary only in "minor" detail as far as theory, and practice are concerned (eg. gaian democracies, co-intelligence, holistic politics, et al).A book entitled The Age of Consent by the journalist George Monbiot is a good example of advanced thinking involving among other things the concept of a genuinely accountable World Parliament. The futurist Jacque Fresco offers in his writings, and talks a more "Utopian" view of what could be. He draws his inspiration from technocracy,trans humanism, and the like.
There are many examples of Positive Human Politics. They notably include the following:-
a) The continued relevance, and importance of the Universal Declaration of Human Rights as the basic ethical foundation for change. This would lead to the greater development of possible enforceable International Laws along with their "correct" interpretation.
b) Empower positive citizenship.
c)The possible option of direct participatory democracy using computer voting by an educated informed public.
d) Greater evolution away from adversarial politics to something more positive, and progressive.
e)Reducing the information overload notably of social, economic, and political knowledge using the least number of words to describe issues for, and against a topic in a way which is seen to be genuinely open, holistic,and accountable. This would have notable implications for direct democracy.
f)Binary Economics, and other similar proposals for fairer wealth distribution.
g)The importance of the proper, and safe development of new sustainable technologies.
h) Full-scale nuclear disarmament if at all possible, or at least the simultaneous development of non-lethal weapons in which death, and destruction no longer occur in "pointless" wars.
i) The European Union can also be seen as a form of positive, progressive evolution, but still requires more reforms to make it more open, and legally accountable. The idea of a Super-State may seem fine in principle but such a political union may well be superfluous. Growing cooperation between independent sovereign states is arguably the best, and "safest" way forward.
Such proposals are good examples of PHP. Yet, we have no intention of expanding this subject. Much of it anyway is pretty obvious to all "right-thinking people".Unlike TFE there is as yet no lengthy essay on PHP giving further details. Now, we examine the former.
Trans financial Economics
~ The Basic Summary ~
Trans financial Economics, or TFE itself is also known as Non-Taxation Monetary Reform. It believes that new unearned money could be created for democratic governments both local, and national without raising taxes. Many NGOs, or independent non-governmental organizations could also be funded in a similar manner either in full, or in part. Thus, in most cases, fund raising, and donations should be largely unnecessary.This can also lead to greater decentralization of power from central government if desired.
Anyway,the creation of new unearned money itself without taxes, or fund raising would not lead to uncontrolled inflation, and devaluation of currency.This would be directly controlled by advanced computer technology. However, anonymous cash transactions would still be possible.
There is more than enough money to change the world. The problem notably for NGOs is legal access to it.
In TFE there is no redistribution of financial wealth, but NGOs concerned with fairer wealth distribution, and morally progressive concepts such as Binary Economics would be financially empowered as never before. Thus, their influence on public opinion would be far greater.
For some people TFE can be seen as a "transitional" system that would ideally lead from the greed of competitive capitalism to fairer economic systems both large, and small which would cooperate with each other. Unfortunately, this process would probably take many, many decades to occur.Though "scientific" evidence indicates that mutual cooperation for selfish ends is the real natural driving force in society there will "always" be the few who are "greedy," and "competitive" enough to succeed as top businessmen, and command huge sums of "earned" money, and resources.
On the other hand, real genuine socialism which confessedly has a more just, and fairer understanding of capital may gradually manifest itself fully. There may even come a time when everything may become free on demand without exchange of money at all.
Global Subsistence Economy
Message from Ervin Laszlo, founder and president of The Club of Budapest, co-founder of the WorldShift Foundation and president of its board of trustees.
We support the shift of our economic focus from transnational corporate "fusionism" to regional subsistence. Subsistence economy focuses on a "natural" way of living. This is not "back to stone age". It rather means a spiral, wavelike progress out of the life-destroying habits of today's so-called civilization and accepting and welcoming the complexity of life.
We support the development of sustainable, decentralized - that is local - high-tech production, combined with local use of local resources. and the redesign of our monetary system according to a fourfold model: 1) economy of gifting (a basic matriarchal feature), 2) counter-trade (barter) economy, 3) complementary local monetary systems for regional trade, and 4) unified currency (for example called "terra") for interregional and global trade. In our eyes compound interest has to be abolished. Also the concept of "owning" land must be reconsidered.
Regional subsistence is committed to fair trade. It appreciates community, supports redevelopment of social structures and teaches the necessity and the pleasure to share resources - thus making regions ready to downscale consumption, shift values from material to social wealth and to deal with migration in a peaceful way.
HAPPINESS ECONOMY ………………………………………………………………………… A call for a new economics: It’s time to redefine success By Ethan Case ……….. a global conversation has begun that has clear relevance to what’s being discussed here-and-now at the grassroots level across the country. This spring, why not smile in the face of fear and join millions of others in imagining and articulating an economy that makes us all happier? http://grist.org/business-technology/a-call-for-a-new-economics-its-time-to-redefine-success/ …………………………………………………………………………… This article is published as part of the Office for National Statistics (ONS) Measuring National Well-being Programme. The programme aims to produce accepted and trusted measures of the well-being of the nation – how the UK as a whole is doing. This article explores in more detail aspects of governance considered important for understanding National Well-being. It considers information on the involvement in democracy and trust in how the UK is run including statistics on the percentage of registered voters who voted, percentage who trust in parliament and in national government. http://www.ons.gov.uk/ons/rel/wellbeing/measuring-national-well-being/governance/art-governance.html
http://www.ons.gov.uk/ons/dcp171766_285148.pdf …………………………………………………….…………………………………………………………. On Monday, Federal Reserve Chairman Ben Bernanke gave a new jolt of momentum to the growing push for new measures of progress going “beyond GDP.” In prepared remarks for the 32nd general conference of the International Association for Research in Income and Wealth (IARIW), held this week in Cambridge, Massachusetts, Bernanke noted the failure of conventional market indicators in capturing the severe household impacts of the Great Recession and the continuing distress for many families and individuals. But his main point, addressing an important forum for national statisticians and academic experts in the field, was broader and more philosophical. We need new measurement approaches that bring us closer to the “ultimate purpose of economics,” Bernanke asserted, and that purpose is “to understand and promote the enhancement of well-being.” In some detail, he emphasized the importance of subjective well-being, or “happiness,” measures. Coming from America’s superintendent of price stability and maximum employment, Bernanke’s deep plunge into ideas about a happiness economy naturally set the blogosphere and news wires abuzz, mostly favorably like this piece from Bloomberg Businessweek. http://www.policyshop.net/home/2012/8/8/fed-chief-looks-beyond-gdp-to-happiness-measures.html ……………………………………………………………………………. ………… ACADEMICS http://www.wellbeingandpublicpolicy.org/uploads/3/8/0/4/3804146/conference_booklet_final___12_june_2012.pdf http://eprints.lse.ac.uk/47349/1/Community%20currencies%20and%20the%20quantification%20of%20social%20value%20in%20the%20digital%20economy(lsero).pdf
The Economic Value of Voluntary Work in Bhutan Prepared by Karen Hayward Ronald Colman Monograph No. 2, 2012 National Statistics Bureau Thimphu
Bhutan will be the first country in the world to create GNH Accounts that properly value our precious natural, social, cultural, and human resources, and the costs of their depreciation, along with the manufactured and financial resources that are presently counted. Such full-cost accounts are the necessary foundation of a genuine wellbeing and sustainability-based economic system and will assess the true benefits and costs of economic activity.
- Lyonchhen Jigmi Y. Thinley
The Honourable Prime Minister,
Royal Government of Bhutan
dominate our economic thinking and our policy and planning processes — globally as well as nationally — economic accounts can therefore provide a useful tool for communication between the market and non-market sectors. Certainly accounting for the value of non-market assets and services will provide a more accurate measure of the nation’s overall wealth than can ever be achieved by measures that omit critical social and environmental variables entirely. In the long run, by pointing to important linkages between the sectors, Bhutan’s new National The Economic Value of Voluntary Works in Bhutan
……….. if at some time there was a policy reason to especially promote either ecological responsibility or social responsibility, the federal government could say that a certain percentage of your taxes would have to be paid in ecodollars (and/or socialdollars), or that federal contractors would have to pay their employees in ecodollars (and/or social dollars). Or the government might recruit certain businesses to accept ecodollars in payment for socialdollar charges, but not vice versa. The government (or corporations or philanthropists) could give prizes (for races or contests or Pulitzers) in one currency or the other. In an extreme case, the government could mandate a tax on the use of socialdollars (or ecodollars) — so, for example, you would have to pay 22 ecodollars to amount to 20 socialdollars, which would effectively lower the value of ecodollars in relation to socialdollars
As people became aware of the flexibility and potential change in their currency, consumers and corporations would begin seeking a balance of currencies — an effort which would, itself, improve the social and environmental responsibility of the economy as a whole. This balance-seeking would essentially be no different than people who today hedge or balance their investments across levels of probable risk and dependability, as with stocks, bonds, gold, etc. — in the face of fluctuating markets and inflation. But this responsible-dollar version of fluctuation would have a consciously positive impact on the society.
As a side effect, we would then probably see new currency and futures markets emerge around these new currencies!
This would obviously need a lot of computer modeling and experiments to work out the bugs in advance — and a lot of political/economic organizing to make it happen. But it seems to me it would serve to realize that most important of purposes in a wise capitalism: To internalize the social and environmental benefits (and, by contrast, the costs). Its novelty is that it would do this internalization into the currency itself rather than through government taxes and fees on harmful extraction, production and products.
John Fullerton is founder and president of Capital Institute, a think tank devoted to transforming finance. In this clip John speaks about the profound challenge of our time: the re-thinking of our fundamental beliefs about the economy. capitalinstitute.org, moneyandlifemovie.com
http://vimeo.com/35344478 ……………………………………………………………….. Transfinancial Economics is an evolving project nearing basic completion. It should be said that there has been a degree of interest in it from some economists.In April 2010 it was also a subject discussed at a major scientific conference (the ICEME, or International Conference of Engineering, and Meta-Engineering, Florida, USA). It is important to add that TFE regards the financial system as a huge global IT system, and recognizes the reality that virtually all money exists as electronic,or digital data transmitted from one bank account to another. ……………… Transfinancial Economics is a major global paradigm which believes that progress towards a fairer, and better world could be greatly facilitated by a reformed financial system. As such, it champions the cause for a non-debt based economy in which taxes, and indeed, interest on loans could overtime be phased out altogether. It claims too that non-repayable debt-free money (ie.new unearned money) could be used where necessary with interest free loans. The former would not lead to serious inflation as too much of it would not be created. This notion is like Quantitative Easing, or QE. Such innovative funding, or Facilitation Finance created by Facilitation Banks, or FBs would essentially be targetted at "major" environmental/climate change projects, and socio-economic initiatives where notably the initial capital is difficult, or even "impossible" to raise via conventional methods (eg. venture capitalism notably). Moreover, with the phasing in of what may be termed advanced Transfinancial Economics it would be possible to get a highly accurate electronic profile of the entire economy. Since this would be so, it would also give future economists a very accurate understanding of how much new non-repayable debt-free money could be created without serious inflation by FBs, and indeed,by democratic governments which could phase out taxation overtime. Among other things already mentioned such innovative funding could in part, or in full fund in time charitable NGOs.The social, economic, and political implications of this would be immense. It could infact lead to an advanced automated technocratic world in which money, and wage slavery would no longer be necessary.All this could occur in the context of open democracy, and respect for universal human rights. Also, it should be noted that TFE believes that success in the introduction of this reform would probably come about by working pragmatically with banks, and corporations rather than otherwise. It is important to understand that we are not discussing a soviet style command/planned economy but one in which a more responsible form of capitalism could be developed with the right financial incentives, and the right marketing strategies. http://p2pfoundation.net/Transfinancial_Economics …………………………………………
World Bank ::: P2P Cash is working with the World Bank to establish worldwide mobile banking standards. VISA created standard procedures to enable any bank to issue credit cards and any retailer to accept them. We believe that the World Bank will be successful in creating a similar structure to provide financial services to the unbanked. P2P Cash is committing its resources including its patent portfolio to assist in these standard development endeavors.
GSMA ::: The GSMA is the worldwide Association of Wireless Telecommunications Carriers that support the GSM communication technology standard. Standardization has significantly improved their ability to create economies of scale between the carriers and therefore benefited every carrier in the Association. P2P Cash is working with the GSMA to conduct mobile wallet interoperability trials between carriers to be considered as part of the emerging financial services standards.
Distribution Partners ::: P2P Cash is working with several distribution partners to promote and enlarge the Trusted Agent Network (TAN). Technology Partners ::: The P2P Cash patent pending technology is a distributed peer to peer technology. To take advantage of this technology, the Company is aggregating various mobile wallet technology providers around a central clearing and settlement network. P2P Cash is working with the following technology providers to accomplish the goal of a worldwide standard.
The ability to screen applicants and individually choose particular borrowers.
Once you develop a good sense of the type of borrowers that suits your investment profile, you can continue to find similar type borrowers given Prosper’s marketplace is so huge.
There are literally thousands of borrowers with various ratings you can choose from to tailor your desired returns. The higher the risk, the higher the returns and vice versa.
If a borrower ever wants to borrow again on Prosper.com, they need to honor their loan. The Prosper marketplace theoretically reduces default risk over the long term for investors. The idea is similar to one’s social capital online. You don’t want to have many bad reviews or else nobody will ever want to deal with you!
Prosper will hire a collection agency to help you get the non-payer to fulfill their loan obligation.
Regulated by the SEC.
Benefits For Borrowers Of P2P Lending
Access to money and credit without having to go to the bank or go through loan shark companies.
Easy to use online platform walks you through step by step when filling out your application.
Entire process is easier to go through, with less documentation required than traditional loans in most cases.
You can explain why you have bad credit and sell your story to investors. Banks are now super stringent and are unwilling to lend to anybody with poor credit. In a time when so many people have foreclosed on their homes, this is a big problem for potential borrowers.
If the borrower creates a second listing, after having 6-9 months of no missed payments, Prosper shows their exact payback history with them during that time. This is only seen if the borrower creates another listing though. In other words, borrowers can build their borrowing reputation to keep coming back for more.
Loans through prosper are unsecured, meaning borrowers don’t have to come up with collateral such as a house or car to get a lone.
http://www.scoop.it/t/the-emergent-report/p/2769499296/finland-is-about-to-start-using-crowdsourcing-to-create-new-laws ……………………………. Banking is a protected industry and that protection results in limited competition and little innovation. He makes the point that a lack of common language hinders new entrants. We see that today with P2P lending platforms. He sugests barriers to entry need to be lowered so that companies such as Paypal, and Zopa can be allowed to grow and develop better models than existing banks. Commercial peer-to-peer lending, using the web as a conduit, is an emerging business. For example, in the UK companies such as Zopa, Funding Circle and Crowdcube are developing this model. At present, these companies are tiny. But so, a decade and a half ago, was Google. If eBay can solve the lemons problem in the second-hand sales market, it can be done in the market for loans. With open access to borrower information, held centrally and virtually, there is no reason why end-savers and end-investors cannot connect directly. The banking middle men may in time become the surplus links in the chain. Where music and publishing have led, finance could follow. An information web, linked by a common language, makes that disintermediated model of finance a more realistic possibility. Relevance to Bankwatch: It’s a fascinating talk. Basically Haldane suggests:
A root problem of banks is a lack of consistent entity assessment and of product assessment
This root problem means there is no ready means to assess the risk of other entities (banks, funds etc) or the risk of the products those entities produce
A second root problem lies in banks lack of technology innovation. Banks are as fragmented internally, as they are fragmented amongst each other. This fragmentation is especially evident in their technology.
This second root problem means that even with the consistent entity and product assessment problem solved, it would be impossible to effectively share that with each other and with the regulators.
Finally he notes that perhaps the best solution is to encourage new entrants who (I would suggest) are more skilled in technology, and will be better placed to solve these problems from the outside and in so doing perhaps force the incumbents to change. http://thebankwatch.com/?s=haldane Just as a bank stores money, Google Apps stores data, and the onus is on Google to convince you and your business that this data is properly protected. “It’s very similar to the situation banks were in hundreds of years ago,” says Feigenbaum, the director of security for Google’s various enterprise products and services, including its Google Apps suite of online business applications. “They had to convince us to give them our money, to take the money out from under the mattress and put it in the bank.” http://www.wired.com/wiredenterprise/2012/05/google-apps-iso/
A sample Google Analytics dashboard. Tools like this help businesses identify trends and make decisions.
Analytics is the discovery and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. Analytics often favors data visualization to communicate insight.
Firms may commonly apply analytics to business data, to describe, predict, and improve business performance. Specifically, arenas within analytics include enterprise decision management, retail analytics, store assortment and stock-keeping unit optimization, marketing optimization and marketing mix analytics, web analytics, sales force sizing and optimization, price and promotion modeling, predictive science, credit risk analysis, and fraud analytics. Since analytics can require extensive computation (See Big Data), the algorithms and software used for analytics harness the most current methods in computer science, statistics, and mathematics.[1]
Analytics is a two-sided coin. On one side, it uses descriptive and predictive models to gain valuable knowledge from data - data analysis. On the other, analytics uses this insight to recommend action or to guide decision making - communication. Thus, analytics is not so much concerned with individual analyses or analysis steps, but with the entire methodology. There is a pronounced tendency to use the term analytics in business settings e.g. text analytics vs. the more generic text mining to emphasize this broader perspective.[citation needed]
Marketing has evolved from a creative process into a highly data-driven process. Marketing organizations use analytics to determine the outcomes of campaigns or efforts and to guide decisions for investment and consumer targeting. Demographic studies, customer segmentation, conjoint analysis and other techniques allow marketers to use large amounts of consumer purchase, survey and panel data to understand and communicate marketing strategy. Web analytics allows marketers to collect session-level information about interactions on a website using an operation called sessionization. Those interactions provide the web analytics information systems with the information to track the referrer, search keywords, IP address, and activities of the visitor. With this information, a marketer can improve the marketing campaigns, site creative content, and information architecture.
Analysis techniques frequently used in marketing include marketing mix modeling, pricing and promotion analyses, sales force optimization, customer analytics e.g.: segmentation. Web analytics and optimization of web sites and online campaigns now frequently work hand in hand with the more traditional marketing analysis techniques. A focus on digital media has slightly changed the vocabulary so that marketing mix modeling is commonly referred to as attribution modeling in the digital or mixed-media context.
These tools and techniques support both strategic marketing decisions (such as how much overall to spend on marketing and how to allocate budgets across a portfolio of brands and the marketing mix) and more tactical campaign support in terms of targeting the best potential customer with the optimal message in the most cost effective medium at the ideal time. An example of the holistic approach required for this strategy is the Astronomy Model.
A common application of business analytics is portfolio analysis. In this, a bank or lending agency has a collection of accounts of varying value and risk. The accounts may differ by the social status (wealthy, middle-class, poor, etc.) of the holder, the geographical location, its net value, and many other factors. The lender must balance the return on the loan with the risk of default for each loan. The question is then how to evaluate the portfolio as a whole.
The least risk loan may be to the very wealthy, but there are a very limited number of wealthy people. On the other hand there are many poor that can be lent to, but at greater risk. Some balance must be struck that maximizes return and minimizes risk. The analytics solution may combine time series analysis, with many other issues in order to make decisions on when to lend money to these different borrower segments, or decisions on the interest rate charged to members of a portfolio segment to cover any losses among members in that segment.
Predictive models in banking industry is widely developed to bring certainty across the risk scores for individual customers. Credit scores are built to predict individual’s delinquency behaviour and also scores are widely used to evaluate the credit worthiness of each applicant and rated while processing loan applications.
Digital analytics is a set of business and technical activities that define, create, collect, verify or transform digital data into reporting, research, analyses, recommendations, optimizations, predictions, and automations.[2]
In the industry of commercial analytics software, an emphasis has emerged on solving the challenges of analyzing massive, complex data sets, often when such data is in a constant state of change. Such data sets are commonly referred to as big data. Whereas once the problems posed by big data were only found in the scientific community, today big data is a problem for many businesses that operate transactional systems online and, as a result, amass large volumes of data quickly.[3]
The analysis of unstructured data types is another challenge getting attention in the industry. Unstructured data differs from structured data in that its format varies widely and cannot be stored in traditional relational databases without significant effort at data transformation.[4] Sources of unstructured data, such as email, the contents of word processor documents, PDFs, geospatial data, etc., are rapidly becoming a relevant source of business intelligence for businesses, governments and universities.[5] For example, in Britain the discovery that one company was illegally selling fraudulent doctor's notes in order to assist people in defrauding employers and insurance companies,[6] is an opportunity for insurance firms to increase the vigilance of their unstructured data analysis. The McKinsey Global Institute estimates that big data analysis could save the American health care system $300 billion per year and the European public sector €250 billion.[7]
These challenges are the current inspiration for much of the innovation in modern analytics information systems, giving birth to relatively new machine analysis concepts such as complex event processing, full text search and analysis, and even new ideas in presentation.[8] One such innovation is the introduction of grid-like architecture in machine analysis, allowing increases in the speed of massively parallel processing by distributing the workload to many computers all with equal access to the complete data set.[9]
Analytics is increasingly used in education, particularly at the district and government office levels. However, the complexity of student performance measures presents challenges when educators try to understand and use analytics to discern patterns in student performance, predict graduation likelihood, improve chances of student success, etc. For example, in a study involving districts known for strong data use, 48% of teachers had difficulty posing questions prompted by data, 36% did not comprehend given data, and 52% incorrectly interpreted data.[10] To combat this, some analytics tools for educators adhere to an over-the-counter data format (embedding labels, supplemental documentation, and a help system, and making key package/display and content decisions) to improve educators’ understanding and use of the analytics being displayed.[11]
One more emerging challenge is dynamic regulatory needs. For example, in the banking industry, Basel III and future capital adequacy needs are likely to make even smaller banks adopt internal risk models. In such cases, cloud computing and open source R (programming language) can help smaller banks to adopt risk analytics and support branch level monitoring by applying predictive analytics.[citation needed]
Jump up ^U.S. Department of Education Office of Planning, Evaluation and Policy Development (2009). Implementing data-informed decision making in schools: Teacher access, supports and use. United States Department of Education (ERIC Document Reproduction Service No. ED504191)
The Blue Gene/P supercomputer at Argonne National Lab runs over 250,000 processors using normal data center air conditioning, grouped in 72 racks/cabinets connected by a high-speed optical network[1]
A supercomputer is a computer at the frontline of contemporary processing capacity – particularly speed of calculation.
Supercomputers were introduced in the 1960s, made initially and, for decades, primarily by Seymour Cray at Control Data Corporation (CDC), Cray Research and subsequent companies bearing his name or monogram. While the supercomputers of the 1970s used only a few processors, in the 1990s machines with thousands of processors began to appear and, by the end of the 20th century, massively parallel supercomputers with tens of thousands of "off-the-shelf" processors were the norm.[2][3] As of November 2013[update], China's Tianhe-2 supercomputer is the fastest in the world at 33.86 petaFLOPS.
Systems with massive numbers of processors generally take one of two paths: In one approach (e.g., in distributed computing), a large number of discrete computers (e.g., laptops) distributed across a network (e.g., the internet) devote some or all of their time to solving a common problem; each individual computer (client) receives and completes many small tasks, reporting the results to a central server which integrates the task results from all the clients into the overall solution.[4][5] In another approach, a large number of dedicated processors are placed in close proximity to each other (e.g. in a computer cluster); this saves considerable time moving data around and makes it possible for the processors to work together (rather than on separate tasks), for example in mesh and hypercubearchitectures.
The use of multi-core processors combined with centralization is an emerging trend; one can think of this as a small cluster (the multicore processor in a smartphone, tablet, laptop, etc.) that both depends upon and contributes to the cloud.[6][7]
Supercomputers play an important role in the field of computational science, and are used for a wide range of computationally intensive tasks in various fields, including quantum mechanics, weather forecasting, climate research, oil and gas exploration, molecular modeling (computing the structures and properties of chemical compounds, biological macromolecules, polymers, and crystals), and physical simulations (such as simulations of the early moments of the universe, airplane and spacecraft aerodynamics, the detonation of nuclear weapons, and nuclear fusion). Throughout their history, they have been essential in the field of cryptanalysis.[8]
The history of supercomputing goes back to the 1960s, with the Atlas at the University of Manchester and a series of computers at Control Data Corporation (CDC), designed by Seymour Cray. These used innovative designs and parallelism to achieve superior computational peak performance.[9]
The Atlas was a joint venture between Ferranti and the Manchester University and was designed to operate at processing speeds approaching one microsecond per instruction, about one million instructions per second.[10] The first Atlas was officially commissioned on 7 December 1962 as one of the world's first supercomputers – considered to be the most powerful computer in the world at that time by a considerable margin, and equivalent to four IBM 7094s.[11]
The CDC 6600, released in 1964, was designed by Cray to be the fastest in the world by a large margin. Cray switched from germanium to silicon transistors, which he ran very fasy, solving the overheating problem by introducing refrigeration.[12] Given that the 6600 outran all computers of the time by about 10 times, it was dubbed a supercomputer and defined the supercomputing market when one hundred computers were sold at $8 million each.[13][14][15][16]
Cray left CDC in 1972 to form his own company.[14] Four years after leaving CDC, Cray delivered the 80 MHz Cray 1 in 1976, and it became one of the most successful supercomputers in history.[17][18] The Cray-2 released in 1985 was an 8 processor liquid cooled computer and Fluorinert was pumped through it as it operated. It performed at 1.9 gigaflops and was the world's fastest until 1990.[19]
While the supercomputers of the 1980s used only a few processors, in the 1990s, machines with thousands of processors began to appear both in the United States and in Japan, setting new computational performance records. Fujitsu's Numerical Wind Tunnel supercomputer used 166 vector processors to gain the top spot in 1994 with a peak speed of 1.7 gigaflops per processor.[20][21] The Hitachi SR2201 obtained a peak performance of 600 gigaflops in 1996 by using 2048 processors connected via a fast three dimensional crossbar network.[22][23][24] The Intel Paragon could have 1000 to 4000 Intel i860 processors in various configurations, and was ranked the fastest in the world in 1993. The Paragon was a MIMD machine which connected processors via a high speed two dimensional mesh, allowing processes to execute on separate nodes; communicating via the Message Passing Interface.[25]
A Blue Gene/L cabinet showing the stacked blades, each holding many processors
Approaches to supercomputer architecture have taken dramatic turns since the earliest systems were introduced in the 1960s. Early supercomputer architectures pioneered by Seymour Cray relied on compact innovative designs and local parallelism to achieve superior computational peak performance.[9] However, in time the demand for increased computational power ushered in the age of massively parallel systems.
While the supercomputers of the 1970s used only a few processors, in the 1990s, machines with thousands of processors began to appear and by the end of the 20th century, massively parallel supercomputers with tens of thousands of "off-the-shelf" processors were the norm. Supercomputers of the 21st century can use over 100,000 processors (some being graphic units) connected by fast connections.[2][3]
Throughout the decades, the management of heat density has remained a key issue for most centralized supercomputers.[26][27][28] The large amount of heat generated by a system may also have other effects, e.g. reducing the lifetime of other system components.[29] There have been diverse approaches to heat management, from pumping Fluorinert through the system, to a hybrid liquid-air cooling system or air cooling with normal air conditioning temperatures.[19][30]
Systems with a massive number of processors generally take one of two paths: in one approach, known as grid computing, the processing power of a large number of computers in distributed, diverse administrative domains, is opportunistically used whenever a computer is available.[4] In another approach, a large number of processors are used in close proximity to each other, e.g. in a computer cluster. In such a centralized massively parallel system the speed and flexibility of the interconnect becomes very important and modern supercomputers have used various approaches ranging from enhanced Infiniband systems to three-dimensional torus interconnects.[31][32] The use of multi-core processors combined with centralization is an emerging direction, e.g. as in the Cyclops64 system.[6][7]
As the price/performance of general purpose graphic processors (GPGPUs) has improved, a number of petaflop supercomputers such as Tianhe-I and Nebulae have started to rely on them.[33] However, other systems such as the K computer continue to use conventional processors such as SPARC-based designs and the overall applicability of GPGPUs in general purpose high performance computing applications has been the subject of debate, in that while a GPGPU maybe tuned to score well on specific benchmarks its overall applicability to everyday algorithms may be limited unless significant effort is spent to tune the application towards it.[34] However, GPUs are gaining ground and in 2012 the Jaguar supercomputer was transformed into Titan by replacing CPUs with GPUs.[35][36][37]
A number of "special-purpose" systems have been designed, dedicated to a single problem. This allows the use of specially programmed FPGA chips or even custom VLSI chips, allowing better price/performance ratios by sacrificing generality. Examples of special-purpose supercomputers include Belle,[38]Deep Blue,[39] and Hydra,[40] for playing chess, Gravity Pipe for astrophysics,[41]MDGRAPE-3 for protein structure computation molecular dynamics[42] and Deep Crack,[43] for breaking the DEScipher.
A typical supercomputer consumes large amounts of electrical power, almost all of which is converted into heat, requiring cooling. For example, Tianhe-1A consumes 4.04 Megawatts of electricity.[44] The cost to power and cool the system can be significant, e.g. 4MW at $0.10/kWh is $400 an hour or about $3.5 million per year.
Heat management is a major issue in complex electronic devices, and affects powerful computer systems in various ways.[45] The thermal design power and CPU power dissipation issues in supercomputing surpass those of traditional computer cooling technologies. The supercomputing awards for green computing reflect this issue.[46][47][48]
The packing of thousands of processors together inevitably generates significant amounts of heat density that need to be dealt with. The Cray 2 was liquid cooled, and used a Fluorinert "cooling waterfall" which was forced through the modules under pressure.[19] However, the submerged liquid cooling approach was not practical for the multi-cabinet systems based on off-the-shelf processors, and in System X a special cooling system that combined air conditioning with liquid cooling was developed in conjunction with the Liebert company.[30]
In the Blue Gene system IBM deliberately used low power processors to deal with heat density.[49] On the other hand, the IBM Power 775, released in 2011, has closely packed elements that require water cooling.[50] The IBM Aquasar system, on the other hand uses hot water cooling to achieve energy efficiency, the water being used to heat buildings as well.[51][52]
The energy efficiency of computer systems is generally measured in terms of "FLOPS per Watt". In 2008 IBM's Roadrunner operated at 376 MFLOPS/Watt.[53][54] In November 2010, the Blue Gene/Q reached 1684 MFLOPS/Watt.[55][56] In June 2011 the top 2 spots on the Green 500 list were occupied by Blue Gene machines in New York (one achieving 2097 MFLOPS/W) with the DEGIMA cluster in Nagasaki placing third with 1375 MFLOPS/W.[57]
Since the end of the 20th century, supercomputer operating systems have undergone major transformations, as sea changes have taken place in supercomputer architecture.[58] While early operating systems were custom tailored to each supercomputer to gain speed, the trend has been to move away from in-house operating systems to the adaptation of generic software such as Linux.[59]
Given that modern massively parallel supercomputers typically separate computations from other services by using multiple types of nodes, they usually run different operating systems on different nodes, e.g. using a small and efficient lightweight kernel such as CNK or CNL on compute nodes, but a larger system such as a Linux-derivative on server and I/O nodes.[60][61][62]
While in a traditional multi-user computer system job scheduling is in effect a tasking problem for processing and peripheral resources, in a massively parallel system, the job management system needs to manage the allocation of both computational and communication resources, as well as gracefully dealing with inevitable hardware failures when tens of thousands of processors are present.[63]
Although most modern supercomputers use the Linux operating system, each manufacturer has made its own specific changes to the Linux-derivative they use, and no industry standard exists, partly due to the fact that the differences in hardware architectures require changes to optimize the operating system to each hardware design.[58][64]
The parallel architectures of supercomputers often dictate the use of special programming techniques to exploit their speed. Software tools for distributed processing include standard APIs such as MPI and PVM, VTL, and open source-based software solutions such as Beowulf.
In the most common scenario, environments such as PVM and MPI for loosely connected clusters and OpenMP for tightly coordinated shared memory machines are used. Significant effort is required to optimize an algorithm for the interconnect characteristics of the machine it will be run on; the aim is to prevent any of the CPUs from wasting time waiting on data from other nodes. GPGPUs have hundreds of processor cores and are programmed using programming models such as CUDA.
Moreover, it is quite difficult to debug and test parallel programs. Special techniques need to be used for testing and debugging such applications.
Example architecture of a grid computing system connecting many personal computers over the internet
Opportunistic Supercomputing is a form of networked grid computing whereby a “super virtual computer” of many loosely coupled volunteer computing machines performs very large computing tasks. Grid computing has been applied to a number of large-scale embarrassingly parallel problems that require supercomputing performance scales. However, basic grid and cloud computing approaches that rely on volunteer computing can not handle traditional supercomputing tasks such as fluid dynamic simulations.
The fastest grid computing system is the distributed computing projectFolding@home. F@h reported 8.1 petaflops of x86 processing power as of March 2012[update]. Of this, 5.8 petaflops are contributed by clients running on various GPUs, 1.7 petaflops come from PlayStation 3 systems, and the rest from various CPU systems.[66]
The BOINC platform hosts a number of distributed computing projects. As of May 2011[update], BOINC recorded a processing power of over 5.5 petaflops through over 480,000 active computers on the network[67] The most active project (measured by computational power), MilkyWay@home, reports processing power of over 700 teraflops through over 33,000 active computers.[68]
As of May 2011[update], GIMPS's distributed Mersenne Prime search currently achieves about 60 teraflops through over 25,000 registered computers.[69] The Internet PrimeNet Server supports GIMPS's grid computing approach, one of the earliest and most successful grid computing projects, since 1997.
Quasi-opportunistic supercomputing is a form of distributed computing whereby the “super virtual computer” of a large number of networked geographically disperse computers performs huge processing power demanding computing tasks.[70] Quasi-opportunistic supercomputing aims to provide a higher quality of service than opportunistic grid computing by achieving more control over the assignment of tasks to distributed resources and the use of intelligence about the availability and reliability of individual systems within the supercomputing network. However, quasi-opportunistic distributed execution of demanding parallel computing software in grids should be achieved through implementation of grid-wise allocation agreements, co-allocation subsystems, communication topology-aware allocation mechanisms, fault tolerant message passing libraries and data pre-conditioning.[70]
Supercomputers generally aim for the maximum in capability computing rather than capacity computing. Capability computing is typically thought of as using the maximum computing power to solve a single large problem in the shortest amount of time. Often a capability system is able to solve a problem of a size or complexity that no other computer can, e.g. a very complex weather simulation application.[71]
Capacity computing in contrast is typically thought of as using efficient cost-effective computing power to solve a small number of somewhat large problems or a large number of small problems, e.g. many user access requests to a database or a web site.[71] Architectures that lend themselves to supporting many users for routine everyday tasks may have a lot of capacity but are not typically considered supercomputers, given that they do not solve a single very complex problem.[71]
Top supercomputer speeds: logscale speed over 60 years
In general, the speed of supercomputers is measured and benchmarked in "FLOPS" (FLoating Point Operations Per Second), and not in terms of MIPS, i.e. as "instructions per second", as is the case with general purpose computers.[72] These measurements are commonly used with an SI prefix such as tera-, combined into the shorthand "TFLOPS" (1012 FLOPS, pronounced teraflops), or peta-, combined into the shorthand "PFLOPS" (1015 FLOPS, pronounced petaflops.) "Petascale" supercomputers can process one quadrillion (1015) (1000 trillion) FLOPS. Exascale is computing performance in the exaflops range. An exaflop is one quintillion (1018) FLOPS (one million teraflops).
No single number can reflect the overall performance of a computer system, yet the goal of the Linpack benchmark is to approximate how fast the computer solves numerical problems and it is widely used in the industry.[73] The FLOPS measurement is either quoted based on the theoretical floating point performance of a processor (derived from manufacturer's processor specifications and shown as "Rpeak" in the TOP500 lists) which is generally unachievable when running real workloads, or the achievable throughput, derived from the LINPACK benchmarks and shown as "Rmax" in the TOP500 list. The LINPACK benchmark typically performs LU decomposition of a large matrix. The LINPACK performance gives some indication of performance for some real-world problems, but does not necessarily match the processing requirements of many other supercomputer workloads, which for example may require more memory bandwidth, or may require better integer computing performance, or may need a high performance I/O system to achieve high levels of performance.[73]
Pie Chart of Supercomputer Countries Share as of Nov 2012
Since 1993, the fastest supercomputers have been ranked on the TOP500 list according to their LINPACK benchmark results. The list does not claim to be unbiased or definitive, but it is a widely cited current definition of the "fastest" supercomputer available at any given time.
This is a recent list of the computers which appeared at the top of the TOP500 list,[74] and the "Peak speed" is given as the "Rmax" rating. For more historical data see History of supercomputing.
The IBM Blue Gene/P computer has been used to simulate a number of artificial neurons equivalent to approximately one percent of a human cerebral cortex, containing 1.6 billion neurons with approximately 9 trillion connections. The same research group also succeeded in using a supercomputer to simulate a number of artificial neurons equivalent to the entirety of a rat's brain.[81]
Modern-day weather forecasting also relies on supercomputers. The National Oceanic and Atmospheric Administration uses supercomputers to crunch hundreds of millions of observations to help make weather forecasts more accurate.[82]
In 2011, the challenges and difficulties in pushing the envelope in supercomputing were underscored by IBM's abandonment of the Blue Waters petascale project.[83]
Diagram of a 3-dimensional torus interconnect used by systems such as Blue Gene, Cray XT3, etc.
Given the current speed of progress, industry experts estimate that supercomputers will reach 1 exaflops (1018, one quintillion FLOPS) by 2018. China has stated plans to have a 1 exaflop supercomputer online by 2018.[84] Using the Intel MIC multi-core processor architecture, which is Intel's response to GPU systems, SGI plans to achieve a 500-fold increase in performance by 2018, in order to achieve one exaflop. Samples of MIC chips with 32 cores, which combine vector processing units with standard CPU, have become available.[85] The Indian government has also stated ambitions for an exaflop-range supercomputer, which they hope to complete by 2017.[86]
Erik P. DeBenedictis of Sandia National Laboratories theorizes that a zettaflop (1021, one sextillion FLOPS) computer is required to accomplish full weather modeling, which could cover a two-week time span accurately.[87][not in citation given] Such systems might be built around 2030.[88]
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