bascule

Moving right along... Care to give a name? Psst, when your only arguments are ad hominems, it's not particularly befitting to accuse your opponent of them, especially when they're coming back at you with substance.

This fuel, in a modern turbodiesel engine, will get you 40-60 mpg (17-26 km/L)

That's 170-340 barrels of oil per square mile per day (or 65-130 barrels of oil per square kilometer per day for the rest of the world)

Sure can:

Yes, and some snakes love trees:

This guy lives in Boulder and worked for Colorado State University, where I used to work: http://www.dailycamera.com/news/2006/dec/08/inventor-turns-algae-into-fuel/ His idea is to trap the CO2 output from coal-fired power plants and funnel it into enormous fields of enclosed algae pools. Coal-fired power plants produce 40% of America's carbon dioxide emissions, at least according to the article. The basic premise is to collect CO2 from power plants and use it to feed pools of algae with carbon dioxide-enriched water: The result? Biodiesel:

The evidence that greenhouse gasses are the primary culprit behind the present (i.e. past 50 years) rapid rise in global surface temperatures comes from dozens of independently developed models of Earth's entire climate system (known as General Circulation Models, or GCMs). Here's the data from temperature reconstructions of various GCMs graphed: After decades of work, these various models are all starting to give the same or very similar numbers, and CO2 has emerged as the primary forcing to which climate change can be attributed: (Notice that, like SkepticLance mentioned, there are many other forcings at work, primarily solar, ozone, and volcanic activity) Here's an excellent article on the issue of CO2 climate change attribution: http://www.realclimate.org/index.php/archives/2006/10/attribution-of-20th-century-climate-change-to-cosub2sub/ Note that I agree Kyoto does not make sense economically. I see the solution in the form of utilizing CO2 for constructive purposes, rather than simply exhausting it into the atmosphere. Let me start a thread on that. Ed: Thread created! http://www.scienceforums.net/forum/showthread.php?p=318986

Or the victims of a particular disease who want a cure can donate to the international fund. For example, the M-Prize (the prize for the first research group to produce a mouse in a state of negligable senescence) is already to $4.1 million. It could be a combination of whoever wants to donate. Nations could. Corporations could. Individuals could. The goal here is to change the dynamics and goal system of pharmeceutical research. If there were, say, a trillion dollar prize for the cure to HIV, or to cure to cancer, how would that change the dynamics of how pharmeceuticals operate? Because people are suffering and dying?

Bunny wins! http://www.youtube.com/watch?v=_Ez5QPW-ku4

Uhh, what cycle is that? What about increasing carbon dioxide? More frequent extreme weather? Disappearing glaciers? Melting Arctic and Antarctic sea ice? Greenland's ice sheet melting? Your statement demonstrates total ignorance of present scientific knowledge

Recently I have been thinking about the problems with the pharmeceutical industry, resulting in a high cost of drugs which, in addition to being a problem back home, means medical problems which are solvable using expensive medications run rampant in 3rd world countries. For example, the world's biggest killer is HIV. Problem: HIV is hard to cure! Despite enormous amounts of research spanning more than two decades, nothing close to a cure has been found, only expensive treatment regiments. New research is always promising, but none of it is anywhere near practical in terms of coming up with some sort of cure, or at least vaccination. Solution: Look for ways to prevent infection, at least in Africa. After all, only a scant percentage of people worldwide can afford HIV treatment, and thus 4000 people die every single day. If you can prevent people from getting infected in the first place, you can greatly diminish the number of people HIV kills. Problem: Herpes sores provide an ideal transmission vector for HIV. 50% of Africans have genital herpes. Solution: Treat herpes. Drugs like Valtrex can force the disease into its dormant state where it lies hidden deep in the nerves of the genital region. Problem: Valtrex is patented by GlaxoSmithKline. Solution: Illegal generic drug producers violate GlaxoSmithKline's patent Problem: They can't supply the entire country of Africa (...) Seriously, capitalism is failing here, and 4,000 people die every day. So, I could sit here and harp on capitalism, or I could offer a solution. Solution: change the way the entire pharmeceutical industry works. Here's what I'd suggest: First, abolish pharmeceutical patents. Problem: How do the pharmeceuticals make money to fund research? Patents let them rape the public for a short period of time, recouping the losses for their research. Once a drug goes generic, production becomes a cutthroat business with paper thin margins, so the only way to be a profitable drug producer is to either be an innovative researcher (in search of patents) or a cutthroat businessman who can undercut the competition (generic producer) Solution: An international prize fund. This model has successfully motivated the private sector to conduct a successful spaceflight and is being employed by the Immortalist movement to find a cure to aging. The Methuselah Mouse prize is being offered to the first research team who can produce a mouse in a state of "negligable senescence" Graduated prizes for accomplishing various steps towards an overall goal could be awared as well. The important point is: once a solution to these problems has been found, the knowledge enters the public domain. The cutthroat generic producers can worry about the actual execution. The research teams assume the risk of knowing that if they fail to outcompete everyone else, all their investment will be for nothing. But they also know that if they reach one of the goals with a prize attached, they don't have to rely on production and distribution to recoup the costs of R&D: they get their prize immediately and that's that. I think this same model can extend beyond pharmeceuticals (and with the X-Prize as the most successful demonstration of this model, that's ostensibly the case)

If you're talking about this: http://www.amazon.com/Bible-Code-Michael-Drosnin/dp/0684849739/sr=8-1/qid=1168114361/ref=pd_bbs_1/105-2421976-8300411?ie=UTF8&s=books It's a great example of bad math. And here's an equally great deconstruction: http://www.bluedonut.com/biblecode.htm When applying a similar methodology, stunning predictions were found to be hidden in the Microsoft Access Developer's Toolkit version 2.0 End User License Agreement! Among other things: OJ DID IT!

I'm largely an autodidact, and by that I mean... I find books that sound interesting, and read them.

Actually the White House tried that line, the whole "revisionist history" bit It was their way of saying "Yes, in 20/20 hindsight we f*cked up, but we had everyone on board at the time! And now some 'revisionist historians' are trying to say otherwise!"

No formal language can be both consistent and complete But the universe is complete How? TIME! We exist as a succession of meta-languages, each one describing the next in succession They form part of an infinite set, which together is complete That's it! Time is simple! BWAHAHA! In your face, guy who started two "Time explained" threads!

There's no way you're going to keep the statement as concise and correct. What I'm really trying to do is expand the statement into several paragraphs and eliminate all jargon. The classifiers aren't in the thalamus, they're in the neocortex. They interconnect with each other through the thalamus as an additional, mesh-like mode of persistent storage and communication, as opposed to the rigidly hierarchical structure of the neocortex itself. "Classifier" is a bit of unexplained jargon there. Furthermore, the neocortical algorithm is substantially different from "classifier" as typically used in computer science. A Naive Bayes Classifier, perhaps the most common in general usage, operates in a substantially different manner from the neocortical column. Naive Bayes Classifiers must be trained with several examples of a particular pattern and how that pattern should be classified. The closest equivalent to the NCC classification algorithm would be Numenta's Hierarchical Temporal Memory. The bottom of the hierarchy sends unclassifiable patterns up and essentially asks for help classifying the pattern from farther up the hierarchy. This is why, for example, you can drive a route every day and consciously lose track of where you are without having any trouble driving. The actual act of driving is being handled by the lower levels in the hierarchy, and since they're not running into unrecognized patterns, your higher levels can be concerned with something else entirely. Yesterday I was driving home and had to ask myself "Did I just go through a tunnel?" only to look in my rearview mirror to discover "Yes I did". The lower levels never informed the higher levels because they were anticipating the tunnel. How do we learn? How do we use what we learn to make predictions? How do we use predictions to make decisions? Where does perception/conscious experience take place? How are long term memories stored? I think you're also missing I'm trying to go for a functional, not anatomical description. Substituting "thalamus" for "global workspace" essentially introduces a black box into the system. What does the thalamus do? Judging from the above, you don't know what the thalamus does. That's why I'm trying to avoid using specific anatomical terms. A layman has no idea what a neocortex, thalamus, and hippocampus are. I think if you were to give your average Joe a pop quiz and ask what part of the body each of those are a part of, you'd likely not get "brain" as an answer to more than one.

The word is "temporospatial", and it certainly isn't superfluous. I could substitute "self-training hierarchical classifier", but then the question is how does a self-training classifier actually work? These classifiers are looking for sequences/sets (i.e. groups of symbols over time), hence the temporal component, and symbols must be discovered from underlying input data, hence the spatial component. The two feed off each other, using each other to provide input for their own classification. This is a very important distinction when comparing to other types of classification networks, which typically have to be trained explicitly and provide no sort of feedback mechanism. That's an apt criticism Well, it's trying to describe, in four words, the operation of the thalamus. Therein lies the entire conscious experience and perception. The words "global workspace" come from global workspace theory, a specific interpretation of the operation of the thalamus. It's not so much interpretations as predictions. Since different levels of the hierarchy act as temporospatial classifiers, identifying symbols and learning sequences/sets of them which occur in a given temporal sequence, once part of a sequence/set has been identified the upcoming members can be predicted and fed back down the hierarchy. Actually, it's that it's hard to describe in simple english. That's why I'm asking for "Help!" More specific, descriptive language allows you to explain a complex idea concisely. It's the most concisely I can explain the operation of the human brain, at least from a hippocampal-thalamocortical perspective.

A temporospatial classifer is essentially a self-training classifier, similar to a Bayesian network except: 1) The structure is hierarchical 2) The processes of training and classifying are unified. The temporal component (i.e. what symbols are seen in regular intervals) trains the spatial component (i.e. what data represent symbols?) and vice versa Probably the biggest component of understanding this is understanding how classification algorithms work. Here's Wikipedia to the rescue: http://en.wikipedia.org/wiki/Naive_Bayes_classifier

At least when I'm forum whoring, I still use Opera, at least on my PCs. I'm Firefox-only on Mac (except for testing web designs in Safari) I don't even use Adblock. I guess it's built into my brain.

Okay, what part of this sentence: ...is the most difficult to comprehend? I'd love to expand that into a layman-oriented description of how consciousness works, but, it's hard. I guess some potential questions would be: What's a temporospatial classifier? What's a global workspace? I don't get the hierarchy bit! Where does your comprehension of the statement break down?

http://ontheissues.org agrees: Hillary Clinton: They define Hillary Clinton as a "Moderate Liberal Populist" Barack Obama: They define Barack Obama as a "Populist-Leaning Liberal" Again, I predict failure in that circle. How could she possibly take the black vote from a black man who, sans lack of experience (especially executive experience, which Clinton also lacks) has all the makings of a viable Presidential candidate? What I really think Obama has the potential to do, which Hillary Clinton does not, is connect with moderate conservative voters. While he may be slightly more liberal, he seems much more adept at reaching out to the other side, whereas Hillary Clinton is viewed as something of a harpy (by conservatives and liberals like, myself included)

Hmmm... http://www.ontheissues.org/Senate/Hillary_Clinton.htm Abortion: Gay Rights: She's doomed in that circle

http://www.channelregister.co.uk/2006/12/21/japanese_light_trap/ Quantum computers move one step closer

Are you talking about a DOS TSR? Those would implement an interrupt handler routine (which essentially required the use of assembly), and predate the use of protected mode.

To a certain but very limited extent. Microprocessors implement a particular recursively enumerable language known as their Instruction Set Architecture (ISA). However programming in this language (machine language) directly is something which is done by a scant percentage of programmers. Most computer science problems are practically approached at a much higher level, generally expressed in a context-free language. Where computer science begins to play into computer technology is the design of the Instruction Set Architecture. One notable example of this is EPIC (Explicitly Parallel Instruction Computing), the ISA of Intel's Itanium processor. EPIC was designed from the standpoint of eliminating bottlenecks in code produced by compilers, so as to provide the most extensible platform for future compiler authors to continually optimize for. While this is great from a theoretical perspective, EPIC is both a nightmare for compiler authors and Intel/HP's Itanium team. The language the CPU implements is so complex that it is very difficult to design efficient compilers and implementations for (note that humans don't design CPUs anymore. CPU designs are generally created from a meta-language like the Verilog Hardware Description Language) For the time being, a simpler instruction set architecture with mass adoption generally seems to be the way to go. This is likely why AMD64, a set of 64-bit extensions to the seemingly archaic IA32, is quickly becoming the predominant platform used in computing today (in addition to Intel's variant, EM64T) There's a lot of crossover between CPU design a computer science, but there are many computer science problems which are never addressed by CPU designers. Sadly, I think many universities teach programming in the guise of "computer science". Mine certainly did. For a real computer science education, your best teachers will be books. I strongly recommend Don Knuth's Art of Computer Programming series as well as Noam Chomsky's Logical Structure of Linguistic Theory and Studies on Semantics in Generative Grammar.