Tragically, polar melting is outpacing most climate models.
http://www.reuters.com/article/environmentNews/idUSTRE5332BU20090404
Which models you ask? Those ones that predict global desertification in 90 years. So granted that these climate models might be wrong and they have large error bars. But it seems to me that we are seeing evidence that warming is occurring at the UPPER end of those error bars. So maybe Earth will be a desert in 70 or 50 years instead of the 90 predicted.
Saturday, April 4, 2009
Tuesday, March 24, 2009
The Great Filter Discovered
We have never discovered extraterrestrial life. Why not? Something must be stopping life from getting sufficiently advanced. This something, mysterious as it is, has been called The Great Filter.
What is The Great Filter? It could be as banal a idea that intelligent life like ourselves is just a very rare thing. So many conditions have to be just so, that in fact it arises only once per trillion stars say. But more ominously, The Great Filter could be the inescapable tendency for intelligent civilizations to wipe themselves out.
As for the first possibility: We are finding a lot of planets orbiting stars already. Clearly there are many, many planets out there. Organic chemicals are quite common, we know from comets. Are planets like ours really that scarce? Admittedly they have to be watery, far from big clusters of stars and associated frequent gamma ray bursts, and in a system with some outer gas giants to shield them from collisions. But I doubt such conditions are all that rare.
So we're left with that sticky little second possibility: that civilizations invariably wipe themselves out before getting to the technological state to spread through the galaxy.
Sounds nutty that we can observe no little green men and conclude therefore that we are likely doomed to be wiped out soon. Yet there are 100 billion stars in our galaxy, and they have had billions of years of time to colonize the galaxy (or to build space probes called "Von Neuman Probes"). It would only take about 20 million years to reach every star in the galaxy, assuming probes could reach 1 percent of the speed of light. So little green colonists or Von Neuman Probes should have been here for billions of years. Yet they are not. Why not?
Well I think that recent events have provided us with a likely answer. The Great Filter is... climate change. Here is my reasoning.
Over the millions of years required to develop intelligent life, planets tend to accumulate carbon. This carbon gets sequestered in various places around the planet, such as gaseous carbon in cold places (methane trapped in permafrost, methane stores in the ocean floor) as well as liquid and solid forms, stored in warmer, more accessable places (oil fields, coal deposits). Such carbon is too easy a fuel source, and an intelligent civilization will invariably learn to burn the warmer sources of carbon, achieving rapid growth in population.
Every planet has a limit at which it will be overwhelmed with the greenhouse effect achieved from burning carbon (i.e. from CO2), to the point that a warming trend eventually releases the trapped gaseous carbon, sealing the planet's fate. It so happens that planets can hit the released carbon tipping point much sooner than they can learn to build intragalactic rockets or Von Neumann Probes. They hit the tipping point before they can develop technologies to reverse it (carbon sequestration). Even before they have time to convert to carbon neutral energy sources (wind, nuclear).
It turns out that our gaseous carbon tipping point will likely occur very soon, like within a decade, according to climate scientists who build predictive models. Our planet will likely be a very hostile place, mostly desert by the end of this century. One climatologist predicts Earth's population to be just 1 billion by 2099.
It's fashionable at this point in the discussion to put a positive spin on things and say we can solve our problems. I see no reason to do this. Positive spins just promote complacency and inaction. There is no reason for positive spin here. We can pretty much be certain that 6.76 billion Earthlings are not going to come together and stop burning fuels. We are not even going to come together and slow the rate at which we increase burning fuels any time soon. Carbon sequestration technologies are not going to happen on a large enough scale.
Our planet, like the 10 to the x ones before it, will wipe itself out due to climate change. And that will probably occur over just the next couple centuries. Even today's child is likely to experience major hardship or early demise because of this problem. Sorry folks.
That said, I do not believe in fatalism. I intend to do all I can to delay this. The more generations we can eek through our post-industrial Fools Paradise the better.
What is The Great Filter? It could be as banal a idea that intelligent life like ourselves is just a very rare thing. So many conditions have to be just so, that in fact it arises only once per trillion stars say. But more ominously, The Great Filter could be the inescapable tendency for intelligent civilizations to wipe themselves out.
As for the first possibility: We are finding a lot of planets orbiting stars already. Clearly there are many, many planets out there. Organic chemicals are quite common, we know from comets. Are planets like ours really that scarce? Admittedly they have to be watery, far from big clusters of stars and associated frequent gamma ray bursts, and in a system with some outer gas giants to shield them from collisions. But I doubt such conditions are all that rare.
So we're left with that sticky little second possibility: that civilizations invariably wipe themselves out before getting to the technological state to spread through the galaxy.
Sounds nutty that we can observe no little green men and conclude therefore that we are likely doomed to be wiped out soon. Yet there are 100 billion stars in our galaxy, and they have had billions of years of time to colonize the galaxy (or to build space probes called "Von Neuman Probes"). It would only take about 20 million years to reach every star in the galaxy, assuming probes could reach 1 percent of the speed of light. So little green colonists or Von Neuman Probes should have been here for billions of years. Yet they are not. Why not?
Well I think that recent events have provided us with a likely answer. The Great Filter is... climate change. Here is my reasoning.
Over the millions of years required to develop intelligent life, planets tend to accumulate carbon. This carbon gets sequestered in various places around the planet, such as gaseous carbon in cold places (methane trapped in permafrost, methane stores in the ocean floor) as well as liquid and solid forms, stored in warmer, more accessable places (oil fields, coal deposits). Such carbon is too easy a fuel source, and an intelligent civilization will invariably learn to burn the warmer sources of carbon, achieving rapid growth in population.
Every planet has a limit at which it will be overwhelmed with the greenhouse effect achieved from burning carbon (i.e. from CO2), to the point that a warming trend eventually releases the trapped gaseous carbon, sealing the planet's fate. It so happens that planets can hit the released carbon tipping point much sooner than they can learn to build intragalactic rockets or Von Neumann Probes. They hit the tipping point before they can develop technologies to reverse it (carbon sequestration). Even before they have time to convert to carbon neutral energy sources (wind, nuclear).
It turns out that our gaseous carbon tipping point will likely occur very soon, like within a decade, according to climate scientists who build predictive models. Our planet will likely be a very hostile place, mostly desert by the end of this century. One climatologist predicts Earth's population to be just 1 billion by 2099.
It's fashionable at this point in the discussion to put a positive spin on things and say we can solve our problems. I see no reason to do this. Positive spins just promote complacency and inaction. There is no reason for positive spin here. We can pretty much be certain that 6.76 billion Earthlings are not going to come together and stop burning fuels. We are not even going to come together and slow the rate at which we increase burning fuels any time soon. Carbon sequestration technologies are not going to happen on a large enough scale.
Our planet, like the 10 to the x ones before it, will wipe itself out due to climate change. And that will probably occur over just the next couple centuries. Even today's child is likely to experience major hardship or early demise because of this problem. Sorry folks.
That said, I do not believe in fatalism. I intend to do all I can to delay this. The more generations we can eek through our post-industrial Fools Paradise the better.
Friday, March 6, 2009
Q: How many vicious cycles does it take to kill a planet?
Answer: 1
But my occasional read of the popular science magazines finds 5.
(1) Warming planet melts polar ice caps, which reduces polar reflectivity, which increases absorption of sunlight, which warms planet, ...
(2) CO2 acidifies the oceans to the point that calcium carbonate dissolves, killing the organisms that have been sequestering carbon, which increases CO2, ...
(3) Melting permafrost releases methane, which has ~23X the global warming potential of CO2, which causes warming, which melts permafrost, ...
(4) Warming oceans release methane trapped near the bottom, which warms oceans, ...
(5) Human technology (a) invariably through history increases human consumption and (b) increases human technology, which ...
See this alarming article. It says that many climatologists' models predict that the world will be mostly uninhabitable just 90 years from now.
http://www.newscientist.com/article/mg20126971.700-how-to-survive-the-coming-century.html
We humans need to wake up and get our heads around the very real likelihood that we will destroy our world in but a century.
But my occasional read of the popular science magazines finds 5.
(1) Warming planet melts polar ice caps, which reduces polar reflectivity, which increases absorption of sunlight, which warms planet, ...
(2) CO2 acidifies the oceans to the point that calcium carbonate dissolves, killing the organisms that have been sequestering carbon, which increases CO2, ...
(3) Melting permafrost releases methane, which has ~23X the global warming potential of CO2, which causes warming, which melts permafrost, ...
(4) Warming oceans release methane trapped near the bottom, which warms oceans, ...
(5) Human technology (a) invariably through history increases human consumption and (b) increases human technology, which ...
See this alarming article. It says that many climatologists' models predict that the world will be mostly uninhabitable just 90 years from now.
http://www.newscientist.com/article/mg20126971.700-how-to-survive-the-coming-century.html
We humans need to wake up and get our heads around the very real likelihood that we will destroy our world in but a century.
Friday, February 13, 2009
What differentiates INQLE?
People often ask me: Dave, what's so special about this project you've been working on?? Well people seldom do. But you, dear Hypothetical Reader, will get a response nonetheless.
Here are INQLE's innovations, for the record.
(1) I have not seen a wizard-driven semantic data importer like INQLE's. Since ~all data is captured nonsemantically, a good data importer is critical functionality. Specifically, INQLE's data importer (a) makes the process of capturing semantic data and URIs somewhat intuitive, (b) introduces a coherent semantic framework for organizing (measured) data from unchanging attributes, which are more identifiers, and (c) it captures both explicit data (data in the table) and implicit data (data that describes the table)
(2) INQLE introduces sampling (i.e. gathering learnable data), by issuing SPARQL queries against internal data stores and/or remote SPARQL endpoints. Our first sampling algorithm, Simple Subject Sparql Sampler, demonstrates a method whereby semantic arcs are discovered, and used to identify learnable data withing an RDF graph. Semantic graphs (Jena Models) are assembled by issuing SPARQL CONSTRUCT query to capture these arcs. Multiple RDF graphs/models can be combined easily, to form an aggregate learnable data set. So local and remote data can be combined andmined.
(3) INQLE introduces automated machine learning on semantic data. I have not seen that elsewhere.
(4) INQLE exposes the pieces of the learning cycle, such as data harvesting algorithms ("samplers"), as plugin-friendly extension types (in an OSGi container). So it expects to have new sampling & learning automated algorithms plugged into it.
(5) Whereas there has been some work toward applying data mining to the semantic web, I have not seen the reverse. INQLE applies semantic technology to solve problems with data mining. Most notably, data mining typically works with nonstandard formats of data, with nonstandard naming conventions for the methodologies/learning algorithms/statistical measures. Data mining offers no standard format for publishing experimental results. Data mining offers no means for combining 2 data sets into one. These are examples of problems with data mining, for which semantic technology offers solutions.
That about does it. I am sure I forgot something.
Here are INQLE's innovations, for the record.
(1) I have not seen a wizard-driven semantic data importer like INQLE's. Since ~all data is captured nonsemantically, a good data importer is critical functionality. Specifically, INQLE's data importer (a) makes the process of capturing semantic data and URIs somewhat intuitive, (b) introduces a coherent semantic framework for organizing (measured) data from unchanging attributes, which are more identifiers, and (c) it captures both explicit data (data in the table) and implicit data (data that describes the table)
(2) INQLE introduces sampling (i.e. gathering learnable data), by issuing SPARQL queries against internal data stores and/or remote SPARQL endpoints. Our first sampling algorithm, Simple Subject Sparql Sampler, demonstrates a method whereby semantic arcs are discovered, and used to identify learnable data withing an RDF graph. Semantic graphs (Jena Models) are assembled by issuing SPARQL CONSTRUCT query to capture these arcs. Multiple RDF graphs/models can be combined easily, to form an aggregate learnable data set. So local and remote data can be combined andmined.
(3) INQLE introduces automated machine learning on semantic data. I have not seen that elsewhere.
(4) INQLE exposes the pieces of the learning cycle, such as data harvesting algorithms ("samplers"), as plugin-friendly extension types (in an OSGi container). So it expects to have new sampling & learning automated algorithms plugged into it.
(5) Whereas there has been some work toward applying data mining to the semantic web, I have not seen the reverse. INQLE applies semantic technology to solve problems with data mining. Most notably, data mining typically works with nonstandard formats of data, with nonstandard naming conventions for the methodologies/learning algorithms/statistical measures. Data mining offers no standard format for publishing experimental results. Data mining offers no means for combining 2 data sets into one. These are examples of problems with data mining, for which semantic technology offers solutions.
That about does it. I am sure I forgot something.
Wednesday, October 1, 2008
INQLE 0.1.4
Finally uploading the next release. Skipped 0.1.3 to emphasize the grandeur of 0.1.4. And doesn't it have an air of glory about it? "0.1.4".
Bugs notwithstanding, this version has quite an advanced spreadsheet importer. I have not seen a RDF importer wizard of this sophistication. It can do all of the following things:
Quite a nifty bit o work if I do say so myself! And this is my excuse as to why it was almost 4 months in coming. Hopefully all this reengineering will pay off and make the process of importing data as RDF as easy and comprehensive as possible. My reasoning is that if you can import most any structure of CSV data, then you make it a whole lot easier for folks to use INQLE.
Future work: hook the thing up to the full UMBEL subject database, so we can look up subjects and properties from a richer source. Plus all the billions of other things in the INQLE roadmap.
http://code.google.com/p/inqle/wiki/INQLE_Roadmap
Bugs notwithstanding, this version has quite an advanced spreadsheet importer. I have not seen a RDF importer wizard of this sophistication. It can do all of the following things:
- It captures as RDF not only explicit data (i.e., that which sits in the spreadsheet) but also implicit data (i.e., data about the spreadsheet as a whole, like "this spreadsheet is a bunch of data collected in Wilmington, Delaware by so-and-so organization").
- It does not require users to enter in RDF URIs, as I considered this to be a major usability impediment.
- It has a lookup capability for finding subject classes.
- It automatically retrieves known properties for the subject in question and provides form elements for entering literal values of thos properties or for specifying which column in the spreadsheet contains the values in question.
- It permits users to add their own subjects and/or properties.
- It registers new subjects and properties in the Central INQLE Server, and makes these discoverable by other INQLE users running the importer wizard.
Quite a nifty bit o work if I do say so myself! And this is my excuse as to why it was almost 4 months in coming. Hopefully all this reengineering will pay off and make the process of importing data as RDF as easy and comprehensive as possible. My reasoning is that if you can import most any structure of CSV data, then you make it a whole lot easier for folks to use INQLE.
Future work: hook the thing up to the full UMBEL subject database, so we can look up subjects and properties from a richer source. Plus all the billions of other things in the INQLE roadmap.
http://code.google.com/p/inqle/wiki/INQLE_Roadmap
Monday, July 7, 2008
Releasing INQLE version 0.1.2
This version of INQLE fixes a few minor bugs. It adds relatively little new end-user functionality. However, we have added a new plugin type: org.inqle.datasets. This plugin type permits plugins to specify a new internal dataset for the purposes of containing data associated with them. This facilitates quicker lookups. This was also a prerequisite for us to be able to store incoming info (in the Central INQLE server). This is an important feature which will come in the next release in a few weeks. More later.
Davo Donohue
Davo Donohue
Sunday, June 22, 2008
INQLE version 0.1 is born!
My open source project INQLE (Intelligent Network of Querying and Learning Engines) has reached the ripe old age of 0.1! I had intended this version to be very bare bones, such that it would barely work. But I found that a few features were needed to make the bloody thing usable. Most notably I added 3 big features:
- a wizard for loading spreadsheet data as RDF. This is a pretty powerful feature.
- a setup wizard which runs upon starting INQLE for the first time
- an embedded database. This dramatically simplifies the process of installing INQLE. To my delight, I discovered that Jena has recently begin supporting the fantastic H2 database, which performs very well as an embedded database (in fact it outperforms non-embedded databases significantly). I find INQLE runs much faster using an embedded H2 database than an external PostgreSQL database.
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