But if they *quit* their job, they must get a new visa, which means leaving the US and re-entering. That's why they're indentured servants. They can't voluntarily leave their job without getting a new visa.
This is exactly correct. Plus, H1B visa holders are tied to the company that issues the visa. If they leave the company, they must return to their home country. Tech companies like Facebook like to have such indentured servants.
H1B visas serve only to drive down wages for US employees. Additionally, they end up training foreign talent that are later kicked out of the country (after 3 or 6 years, depending upon whether the visa is renewed). They don't help the nation's interests, nor the public's interest. They serve only to increase the profit margins of the large firms.
Get rid of the H1B, and increase the green card slots available to foreign workers, especially the Indians. I've very pro-immigrant, but the H1B visa only provides for indentured servitude.
I posted a comment/question to a support web page for the backup device I use. About 10 minutes later, I get a call from a support technician, asking me to do stuff on my computer to verify the problem. He asked me to go to the "Start" menu, and open up something inside the control panel. I told him I don't own any Windows machines. He hung up almost immediately.
I should have strung him along for a while to see what he was trying to do. Oh well...next time.
One needs only to look at the origins of In-Q-Tel, and its connection to Peter Thiel, to know that the defense department has been funding some of the biggest and best known companies for the past 2 decades. Google, PayPal, Facebook, and Palantir all come to mind, although there are many others.
Well, I think you're both wrong. There are very many states of matter. Not everything fits in neatly to those buckets. What is glass? a liquid or a solid? (A: neither, or both, depending on how you look at it) What about Bose-Einstein condensates? Superfluids? There are many others, too. Their properties don't fit neatly into one of the four states you mentioned.
I'm a career programmer that has dabbled with machine learning, map/reduce, big data, and would also love to make it my career.
Taking out defense and finance, and I think you'll find that you're taking out most of the jobs that consume these services. I assume you include the NSA under defense, but if not, they have tons of positions in this area.
There are other options, though. Amazon, Netflix, Microsoft, and Google (among many others in the tech industry) hire lots of people to do these things. I imagine that sales and marketing are beginning to consume these services, although I am not familiar with that industry, nor do I know of any companies using such techniques in that field. Although you discount the medical field (due to animal testing?), you should look at the gene sequencing industry. They hire tons of people in these fields, and gene sequencing is pretty far removed from animal testing. Supply chain analysis is another area that hires people to do this sort of stuff--the airline industry, for example, has many companies that use big data to perform pricing analysis, flight scheduling, etc.
The hard part is finding such field that is close enough to one you already have experience in. It's tough to break into a new field doing this type of work, unless you're coming straight out of university with a degree in big data.
Except that, in the US, the Supreme Court sets precedents based upon the constitution, and they have repeatedly cited the term "separation of church and state". Since the law in the US is established by both the constitution and case law that interprets the constitution, the separation of church and state is well ensconced in US law. On this issue, Ron Paul is on the wrong side of the original libertarians, the founders of our nation (including Thomas Jefferson), as well as with the law itself, as evidenced by the extensive case history separating church and state.
These weapons work at ultrasonic frequencies, where sound beams from the source in a line (because the panel producing the sound is larger than 1/2 the wavelength). Set up two of the sound sources spaced slightly apart, and the interference between the two waves produces a sonic frequency. The ultrasonic frequencies are designed to resonate the bones, so earplugs are indeed ineffective. In fact, the bone resonating feature of these devices at much lower volume levels can cause the sensation that the sounds are coming from within one's head. Modulate a signal on the interference between the two waves, and one can broadcast a human voice, making it sound like voices are coming from within your head.
To tell you the truth, I had never heard of Erwise until today. A have a few questions about Erwise: - Did it support graphics other that XBM? - Did it render HTML, or some other markup language?
I did some consulting for a company called HyperMedia Corporation in 1991-92. As part of that work, I watched closely the development of HTML, NCSA Mosaic, and the lot. HMC's markup language was proprietary and binary. The first thing that struck me about HTML was the ease of editing--you didn't need a dedicated editor. Then, I remember seeing early builds of NCSA's browser (to become Mosaic) when they first added, IIRC, gif support. I remember being absolutely floored with the ability to create attractive content in only a few minutes. My first thought after seeing it was, "I need to find a new job!" Sure enough, within a few months HMC was out of business.
The end result is that there were many factors that led to the success of NCSA Mosaic and Netscape. First, Mosaic ran on platforms other than the X Window System, so it was more accessible. Second, it was among the first to support usable graphics (i.e. not XBM), at least on an accessible platform (Emacs' browser & WorldWideWeb.app had early image support, too, but both were on platforms that had very narrow distribution possibilities). Third, it used standard HTML.
Erwise might have had all of these, with the one caveat that it supported only Unix/X Window System. Hard to say from this article. However, I think it's a little simplistic to say that funding was the only thing holding these guys back from Netscape-like success.
Re:oh goody.
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C# In-Depth
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· Score: 3, Interesting
Yeah, that was what I thought before I started using C#. I am a 10+ year veteran of the Java world, and have spent the last year or so on a large C# project. C# has much better syntax in every way that it deviates from Java. Properties are quite clear, since VS does a nice job. Under the covers, there is *no* difference between a property with an implicit getter/setter (i.e. you didn't provide one, so you access the variable directly)--the bytecode creates a synthetic get_ and set_ method, allowing things like AOP to work even if no explicit getter/setter is provided.
The Java method results in much more verbose boilerplate code. This also causes many developers to do more cut-and-paste, another source of potential error. The Java method makes tech like AOP much harder, as there is no synthetic method call surrounding access to public member variables. The Java method is, in short, not object oriented, as it does not properly abstract away property access, so Java tacked on this stupid getXXX/setXXX naming convention in the JavaBean standard.
There are many reasons why Java is a superior platform than.Net/C# (maturity of 3rd party libraries, the open source community, the quality of design in the provided libraries). But the language itself is not one of them. I cannot think of a single area where Java bests C# in terms of the language itself. C# really is the next generation of Java, and has learned from Java's mistakes.
I like this concept of temporal signal processing phenomenon. I wouldn't worry about what others think. It takes "kooks" to make truly fundamental advances in science.
Yeah, I pretty much surmised it's a question of the definition of free will that was causing us to disagree. I believe that free will (according to my definition) exists, and that it is the spark that changes the living brain from a simple automaton to a creating, thinking entity. I don't believe in a soul, as per the religious concept at least. But my definition of free will most certainly does require non-deterministic behavior. Whether free will==intelligence is debatable, though, and I fully accept it as a non-provable (or disprovable) thing until we create true machine intelligence.
As far as AI is concerned, I don't believe that genetic algorithms (the sort of thing used to create this antenna, I presume, or the sort that has proved exhaustively the strongest form of a column at my alma mater) is true creativity or intelligence. It approximates creativity. It models intelligence. But it is not creative, nor is it intelligent. It is a tool, used by creative and intelligent beings to achieve a goal. Without the intelligent driver, I don't think such creativity is possible short of exhaustively trying every possible combination of everything. I don't think that's what creativity or intelligence is, and I don't think it's possible except in very narrow, well defined areas (that are narrow and well defined by the external creative/intelligent driver of the tool).
I don't think creativity and intelligence are embodied only by humans (I think very many living things are creative & intelligent, but my familiarity and use of AI tools to do financial analysis have given me the belief that nothing I have seen in the field of AI classifies as intelligence or creativity). That's nitpicking on your use of the phrase, "only by humans", though. I don't believe anything humans have manufactured/programmed would fit my concept of intelligence or creativity.
I'm not sure I follow you on the distinguisher function bit. Perhaps you can discuss that further? I'm not sure how imposing order necessarily removes the non-deterministic input from the system. My point about convergence is that while each individual datum of input may be non-deterministic, the overall distribution of inputs may well be modeled quite easily. The model won't be accurate/deterministic at the minute level, but the net effect of large numbers of input will be model-able and deterministic (this, in fact, is exactly what adding a clock to the quantum effects of a transistor does to create a deterministic switch out of a non-deterministic core effect of electrons maybe jumping from the N to the P junction).
My concept of embracing this non-deterministic behavior of transistors is analogous to my understanding of how individual neurons work, and how their outputs cascade as inputs into other neurons to create thought. The exact time that an individual transistor/neuron fires cannot be predetermined. But the net effect of a network of these transistors firing produces a result that converges over time. My premise is that occasional changes in timing for firing of individual transistors/neurons is (or may be, at least) the spark that initiates creativity, and that creativity is a prerequisite to what I call true intelligence. The only problem I see is that all avenues of research into quantum gates for quantum computers, or into asynchronous computing, intentionally attempts to eliminate the effect of "misfires" of transistors, or quantum gates, since non-deterministic logic doesn't really serve us well in the field of computing. I think we need to break free from that avenue of thought, and to embrace these "misfires".
My point about modeling systems whose state includes random information is that we can create such models that work *most* of the time. We can model the aggregate behavior of the system, but we will never be 100% accurate with our model. If we were 100% accurate with the model, then we would have the basis for the creation of a truly random number generator, and that would be truly newsworthy. W
Yeah, I feel sorry for my employer, too. He is me. My existence as a solipsist places me firmly in the realm of kooks. But, damn, I'm had a history of success in the field of financial analysis that is hard to attribute to chance.
Chaotic effects produce pseudo-random numbers. I am unaware of any truly random number generators that are not based upon quantum effects. I believe that quantum effects are the only physical phenomena that are believed to be truly random. Even then, some great minds (e.g. Einstein) never quite believed that quantum effects are truly random. "God doesn't play dice".
First, the definition of free will has been debated through the ages, and my definition is not universally accepted. Given that, my definition of free will implies that choices are *not* predetermined, that free will implies a non-determinate system. Now, there is no way I, or anyone, can prove or disprove that humans have free will by this definition (?until we create true intelligence based upon a determinate system?). Therefore, to follow my further arguments, you must accept this assumption that free will implies a non-determinate system, at least for the sake of this discussion.
Free will == non-determinate == truly random, not pseudorandom. Now, since humans interact with a computer network, and humans, by my previous assumption, have free will, network latency therefore is non-determinate.
All of this implies not chaotic behavior, but instead truly random behavior. There are bounds, and the randomness definitely converges. But, at its core, it is truly random, not pseudo-random, and therefore not chaotic.
Network latency does not generate, therefore, pseudo-randomness, but true randomness. Humans interact with the network, introducing truly random behavior. This randomness does not cause bad loading behavior. If you are familiar with neural networks, perhaps you've encountered situations where introducing a pseudo-random delay to a feedback loop can most definitely improve loading behavior for specific circumstances.
Truly random behavior does not imply that it cannot be modeled. It can be modeled. But the model will never be 100% accurate, and will never produce truly intelligent machines (as opposed to artificial intelligence that models, but does not create, true intelligence). Yes, I know that chaotic systems, according to currently accepted math, are non-predictable. But they are determinate. Determinate necessarily implies a lack of free will, by my earlier assumption (you don't have to agree with my assumption in reality, but, for the sake of this discussion, it is central to all of my other logic).
While we may be able to model significant portions of a mammalian brain, our models are not creative. Perhaps, with sufficient power, we will be able to model creativity. But, being determinate, it will only approximate true creativity.
One node per neuron is an extreme case. There must be some interaction that introduces truly random behavior for it to be truly intelligent. According to my prior assumption...this is really breaking down to a tautology, where if you agree with my base assumption, then the rest falls out based upon logic; if you reject my base assumption, the the rest is inherently inaccurate based upon logic.
I'm not saying that "modeling the brain exceeds the available power". I am instead saying that modeling the brain will approximate, but not create, true intelligence. It will get close. It may pass the Turing Test. But it won't be truly intelligent. It will just look intelligent. And, I posit without proof, it will not be creative.
Honestly, I hope you don't take this the wrong way, but I'm not looking for DARPA funding, and I don't give a fuck about DARPA. I've got a good day job, and I doubt DARPA would ever be able to match my working conditions, monetary compensation, and flexibility.
I like to discuss these things to expand my horizons. Slashdot has produced over the years many interesting discussions that expand my horizons (less so recently, aside from this thread--I've become more of a reddit lately). I enjoy discussing my ideas, and pushing my boundaries. The only reasons I'm discussing this here is because this thread will undoubtedly attract people that can expand my horizons. Quite frankly, it has achieved this, as I have found some additional reading already for my summer reading list. And I thoroughly enjoy this thread with you. Although you haven't asked as such, I am a solipsist at my core, so everything in life, this thread included, is mental masturbation. And that, in and of itself, is to be celebrated.
I should have said "non-determinate". Non-predictable is not sufficient, imho.
Non-determinate does not imply it does not converge. A transistor is a classic case of a non-determinate system, based on quantum effects, that converges. Because it is non-determinate, we have created clocks (i.e. synchronous computing) to sample the transistor only after it has converged. In other words, our logic systems for traditional computing are limited by our ability to create programs that rely upon non-deterministic behavior. This is the case of pretty much all computing, including current quantum computing, traditional synchronous computing, and research into asynchronous computing. I posit that we need to rethink this fundamental aspect of logic, to create a system that embraces non-deterministic behavior, but relies upon convergent behavior. Only in this way will we break free from "artificial" machine intelligence into the realm of "real" machine intelligence.
I didn't mean to imply that asynchronous computing is the only way to achieve this non-determinate behavior. A true random number generator indeed would do the trick. Network latency, as it involves external network traffic, is another for of non-deterministic behavior. Asynchronous computing does it rather directly, though. A transistor is a pretty good model for a neuron, except that neurons typically have dozens of inputs instead of only two.
There is plenty of evidence that our brain relies upon quantum behaviors. The sense of smell and the sense of taste, in particular, have been shown to have behavior that is best explained by quantum effects. The behavior of individual neurons is another area that is best explained by quantum effects. We know that a neuron *will* converge (i.e. fire) based upon certain inputs. We just don't know exactly *when* it will fire. Sort of like transistors.
I can go on. I haven't covered at all my models regarding the other human senses. Touch, vision, and hearing utilize our central nervous system to behave as sorts of Fourier transforms, transforming time-based data into frequency-based data. I suspect that the quantum effects sensed by the taste and smell are similarly transformed into frequency-based data. I firmly believe that the brain acts as a sort of pattern-finding engine. These patterns are far easier to discern in the frequency domain (my background includes signal processing and pattern finding, both of which I use in the financial world in combination with so-called learning systems to predict future risk and future prices of equities and commodities).
I am not an AI researcher; in fact, I believe that AI has fundamental problems that will prevent it from ever reaching true intelligence. But I am an applied AI software developer. I just think the term "AI" has loaded with false implications. I also think the current field is a dead end when it comes to creating true machine intelligence.
Chaos == determinate, non-predictable. I claim that determinism inherently rules out free will. I assume the human mind has free will, and that free will is a prerequisite for true intelligence (not simulating real intelligence). That assumption is a leap, and I fully understand and accept that. But, if you accept that assumption, a chaotic system cannot have true intelligence.
Asynchronous computing, using current models, does not produce or take advantage of quantum uncertainty. But I posit that they could, if designed for this. Instead, traditional computer design attempts to eliminate non-deterministic behavior. I state this (quantum uncertainty) as a potential for asynchronous computing, not as one that already exists. I'd love to see logic models where results are not deterministic, but do converge over time. In short, I'd like to see what an asynchronous computing model is capable of once one frees oneself from the current bounds of modern computing.
Network latency is most certainly non-determinate, at least in an open computer network. I'm not talking about latency as it relates to a single connection between two computers. I'm talking about latency that includes the cost of network collisions, which is determinate based upon the network traffic from other computers (presumably controlled by people that act not chaotically, but non-deterministicly).
Finally, I'm not trying to depict accurately the state of AI. I know quite well that these concepts are outside the norm of AI. In fact, I build learning systems for my day job--massively parallel computing that utilizes, among other things, neural networks, genetic algorithms, graph theory, etc. I'm trying to state what is required for true machine intelligence. This non-deterministic behavior is what will distinguish artificial intelligence and brain models from true machine intelligence.
True machine intelligence will not come from following the same standard old routes. I think there is some value to be had using massive parallel computing models where each node mimics a neuron, since these include the non-deterministic network latency I described earlier. Unfortunately, the resulting system that is required for modeling even moderately complex brains is enormous, far bigger than the biggest parallel clusters available today. An asynchronous computer is one way I think this effect (non-deterministic behavior) can be taken advantage of without spending billions (and it will be inherently faster because inter-"neuron" latency is reduced to nanosecond levels). I do not find much value in the effort to create true machine intelligence through the use of neural networks, genetic algorithms, and the such, although they do work well in determining pricing models for commodities & equities, as well as assessing risk, and these are both areas in which I utilize them.
You are correct in your assessment of my ideas as "a good philosophy". They are not practical ideas at this point, and they will not lead to any hardware or software designs any time soon. But these are the places where DARPA should be funding. They have a long and distinguished history of funding the Tesla-type research, not the Alexander Graham Bell-type research. There's already been tons of money, time, and effort poured down traditional AI research. What do we have as a result? Not much.
Shit, forgot to log in before posting. There. Oh, and for all of you young folk that think your ID is low, no, it isn't. Mine isn't even low. I forgot the login credentials for my first acct (in the 100s). Damn.
Caching proxies can be configured to do this at the site-level. I'm no squid expert, but I'm sure you can google some squid configurations that will do this if you are interested.
Slashdot Mirror
But if they *quit* their job, they must get a new visa, which means leaving the US and re-entering. That's why they're indentured servants. They can't voluntarily leave their job without getting a new visa.
This is exactly correct. Plus, H1B visa holders are tied to the company that issues the visa. If they leave the company, they must return to their home country. Tech companies like Facebook like to have such indentured servants.
H1B visas serve only to drive down wages for US employees. Additionally, they end up training foreign talent that are later kicked out of the country (after 3 or 6 years, depending upon whether the visa is renewed). They don't help the nation's interests, nor the public's interest. They serve only to increase the profit margins of the large firms.
Get rid of the H1B, and increase the green card slots available to foreign workers, especially the Indians. I've very pro-immigrant, but the H1B visa only provides for indentured servitude.
I posted a comment/question to a support web page for the backup device I use. About 10 minutes later, I get a call from a support technician, asking me to do stuff on my computer to verify the problem. He asked me to go to the "Start" menu, and open up something inside the control panel. I told him I don't own any Windows machines. He hung up almost immediately.
I should have strung him along for a while to see what he was trying to do. Oh well...next time.
One needs only to look at the origins of In-Q-Tel, and its connection to Peter Thiel, to know that the defense department has been funding some of the biggest and best known companies for the past 2 decades. Google, PayPal, Facebook, and Palantir all come to mind, although there are many others.
Well, I think you're both wrong. There are very many states of matter. Not everything fits in neatly to those buckets. What is glass? a liquid or a solid? (A: neither, or both, depending on how you look at it) What about Bose-Einstein condensates? Superfluids? There are many others, too. Their properties don't fit neatly into one of the four states you mentioned.
I'm a career programmer that has dabbled with machine learning, map/reduce, big data, and would also love to make it my career.
Taking out defense and finance, and I think you'll find that you're taking out most of the jobs that consume these services. I assume you include the NSA under defense, but if not, they have tons of positions in this area.
There are other options, though. Amazon, Netflix, Microsoft, and Google (among many others in the tech industry) hire lots of people to do these things. I imagine that sales and marketing are beginning to consume these services, although I am not familiar with that industry, nor do I know of any companies using such techniques in that field. Although you discount the medical field (due to animal testing?), you should look at the gene sequencing industry. They hire tons of people in these fields, and gene sequencing is pretty far removed from animal testing. Supply chain analysis is another area that hires people to do this sort of stuff--the airline industry, for example, has many companies that use big data to perform pricing analysis, flight scheduling, etc.
The hard part is finding such field that is close enough to one you already have experience in. It's tough to break into a new field doing this type of work, unless you're coming straight out of university with a degree in big data.
Wow...a little sensitive, are you?
Except that, in the US, the Supreme Court sets precedents based upon the constitution, and they have repeatedly cited the term "separation of church and state". Since the law in the US is established by both the constitution and case law that interprets the constitution, the separation of church and state is well ensconced in US law. On this issue, Ron Paul is on the wrong side of the original libertarians, the founders of our nation (including Thomas Jefferson), as well as with the law itself, as evidenced by the extensive case history separating church and state.
These weapons work at ultrasonic frequencies, where sound beams from the source in a line (because the panel producing the sound is larger than 1/2 the wavelength). Set up two of the sound sources spaced slightly apart, and the interference between the two waves produces a sonic frequency. The ultrasonic frequencies are designed to resonate the bones, so earplugs are indeed ineffective. In fact, the bone resonating feature of these devices at much lower volume levels can cause the sensation that the sounds are coming from within one's head. Modulate a signal on the interference between the two waves, and one can broadcast a human voice, making it sound like voices are coming from within your head.
OK, just realized the article has 3 pages :-). Looks like it did render HTML. The rest still holds.
To tell you the truth, I had never heard of Erwise until today. A have a few questions about Erwise:
- Did it support graphics other that XBM?
- Did it render HTML, or some other markup language?
I did some consulting for a company called HyperMedia Corporation in 1991-92. As part of that work, I watched closely the development of HTML, NCSA Mosaic, and the lot. HMC's markup language was proprietary and binary. The first thing that struck me about HTML was the ease of editing--you didn't need a dedicated editor. Then, I remember seeing early builds of NCSA's browser (to become Mosaic) when they first added, IIRC, gif support. I remember being absolutely floored with the ability to create attractive content in only a few minutes. My first thought after seeing it was, "I need to find a new job!" Sure enough, within a few months HMC was out of business.
The end result is that there were many factors that led to the success of NCSA Mosaic and Netscape. First, Mosaic ran on platforms other than the X Window System, so it was more accessible. Second, it was among the first to support usable graphics (i.e. not XBM), at least on an accessible platform (Emacs' browser & WorldWideWeb.app had early image support, too, but both were on platforms that had very narrow distribution possibilities). Third, it used standard HTML.
Erwise might have had all of these, with the one caveat that it supported only Unix/X Window System. Hard to say from this article. However, I think it's a little simplistic to say that funding was the only thing holding these guys back from Netscape-like success.
Yeah, that was what I thought before I started using C#. I am a 10+ year veteran of the Java world, and have spent the last year or so on a large C# project. C# has much better syntax in every way that it deviates from Java. Properties are quite clear, since VS does a nice job. Under the covers, there is *no* difference between a property with an implicit getter/setter (i.e. you didn't provide one, so you access the variable directly)--the bytecode creates a synthetic get_ and set_ method, allowing things like AOP to work even if no explicit getter/setter is provided.
The Java method results in much more verbose boilerplate code. This also causes many developers to do more cut-and-paste, another source of potential error. The Java method makes tech like AOP much harder, as there is no synthetic method call surrounding access to public member variables. The Java method is, in short, not object oriented, as it does not properly abstract away property access, so Java tacked on this stupid getXXX/setXXX naming convention in the JavaBean standard.
There are many reasons why Java is a superior platform than .Net/C# (maturity of 3rd party libraries, the open source community, the quality of design in the provided libraries). But the language itself is not one of them. I cannot think of a single area where Java bests C# in terms of the language itself. C# really is the next generation of Java, and has learned from Java's mistakes.
I like this concept of temporal signal processing phenomenon. I wouldn't worry about what others think. It takes "kooks" to make truly fundamental advances in science.
Yeah, there are tons of 4-digit UIDs. Wish I hadn't lost the login credentials of my original 3-digit one :-( Poor me.
Yeah, I pretty much surmised it's a question of the definition of free will that was causing us to disagree. I believe that free will (according to my definition) exists, and that it is the spark that changes the living brain from a simple automaton to a creating, thinking entity. I don't believe in a soul, as per the religious concept at least. But my definition of free will most certainly does require non-deterministic behavior. Whether free will==intelligence is debatable, though, and I fully accept it as a non-provable (or disprovable) thing until we create true machine intelligence.
As far as AI is concerned, I don't believe that genetic algorithms (the sort of thing used to create this antenna, I presume, or the sort that has proved exhaustively the strongest form of a column at my alma mater) is true creativity or intelligence. It approximates creativity. It models intelligence. But it is not creative, nor is it intelligent. It is a tool, used by creative and intelligent beings to achieve a goal. Without the intelligent driver, I don't think such creativity is possible short of exhaustively trying every possible combination of everything. I don't think that's what creativity or intelligence is, and I don't think it's possible except in very narrow, well defined areas (that are narrow and well defined by the external creative/intelligent driver of the tool).
I don't think creativity and intelligence are embodied only by humans (I think very many living things are creative & intelligent, but my familiarity and use of AI tools to do financial analysis have given me the belief that nothing I have seen in the field of AI classifies as intelligence or creativity). That's nitpicking on your use of the phrase, "only by humans", though. I don't believe anything humans have manufactured/programmed would fit my concept of intelligence or creativity.
I'm not sure I follow you on the distinguisher function bit. Perhaps you can discuss that further? I'm not sure how imposing order necessarily removes the non-deterministic input from the system. My point about convergence is that while each individual datum of input may be non-deterministic, the overall distribution of inputs may well be modeled quite easily. The model won't be accurate/deterministic at the minute level, but the net effect of large numbers of input will be model-able and deterministic (this, in fact, is exactly what adding a clock to the quantum effects of a transistor does to create a deterministic switch out of a non-deterministic core effect of electrons maybe jumping from the N to the P junction).
My concept of embracing this non-deterministic behavior of transistors is analogous to my understanding of how individual neurons work, and how their outputs cascade as inputs into other neurons to create thought. The exact time that an individual transistor/neuron fires cannot be predetermined. But the net effect of a network of these transistors firing produces a result that converges over time. My premise is that occasional changes in timing for firing of individual transistors/neurons is (or may be, at least) the spark that initiates creativity, and that creativity is a prerequisite to what I call true intelligence. The only problem I see is that all avenues of research into quantum gates for quantum computers, or into asynchronous computing, intentionally attempts to eliminate the effect of "misfires" of transistors, or quantum gates, since non-deterministic logic doesn't really serve us well in the field of computing. I think we need to break free from that avenue of thought, and to embrace these "misfires".
My point about modeling systems whose state includes random information is that we can create such models that work *most* of the time. We can model the aggregate behavior of the system, but we will never be 100% accurate with our model. If we were 100% accurate with the model, then we would have the basis for the creation of a truly random number generator, and that would be truly newsworthy. W
Yeah, I feel sorry for my employer, too. He is me. My existence as a solipsist places me firmly in the realm of kooks. But, damn, I'm had a history of success in the field of financial analysis that is hard to attribute to chance.
Chaotic effects produce pseudo-random numbers. I am unaware of any truly random number generators that are not based upon quantum effects. I believe that quantum effects are the only physical phenomena that are believed to be truly random. Even then, some great minds (e.g. Einstein) never quite believed that quantum effects are truly random. "God doesn't play dice".
First, the definition of free will has been debated through the ages, and my definition is not universally accepted. Given that, my definition of free will implies that choices are *not* predetermined, that free will implies a non-determinate system. Now, there is no way I, or anyone, can prove or disprove that humans have free will by this definition (?until we create true intelligence based upon a determinate system?). Therefore, to follow my further arguments, you must accept this assumption that free will implies a non-determinate system, at least for the sake of this discussion.
Free will == non-determinate == truly random, not pseudorandom. Now, since humans interact with a computer network, and humans, by my previous assumption, have free will, network latency therefore is non-determinate.
All of this implies not chaotic behavior, but instead truly random behavior. There are bounds, and the randomness definitely converges. But, at its core, it is truly random, not pseudo-random, and therefore not chaotic.
Network latency does not generate, therefore, pseudo-randomness, but true randomness. Humans interact with the network, introducing truly random behavior. This randomness does not cause bad loading behavior. If you are familiar with neural networks, perhaps you've encountered situations where introducing a pseudo-random delay to a feedback loop can most definitely improve loading behavior for specific circumstances.
Truly random behavior does not imply that it cannot be modeled. It can be modeled. But the model will never be 100% accurate, and will never produce truly intelligent machines (as opposed to artificial intelligence that models, but does not create, true intelligence). Yes, I know that chaotic systems, according to currently accepted math, are non-predictable. But they are determinate. Determinate necessarily implies a lack of free will, by my earlier assumption (you don't have to agree with my assumption in reality, but, for the sake of this discussion, it is central to all of my other logic).
While we may be able to model significant portions of a mammalian brain, our models are not creative. Perhaps, with sufficient power, we will be able to model creativity. But, being determinate, it will only approximate true creativity.
One node per neuron is an extreme case. There must be some interaction that introduces truly random behavior for it to be truly intelligent. According to my prior assumption...this is really breaking down to a tautology, where if you agree with my base assumption, then the rest falls out based upon logic; if you reject my base assumption, the the rest is inherently inaccurate based upon logic.
I'm not saying that "modeling the brain exceeds the available power". I am instead saying that modeling the brain will approximate, but not create, true intelligence. It will get close. It may pass the Turing Test. But it won't be truly intelligent. It will just look intelligent. And, I posit without proof, it will not be creative.
Honestly, I hope you don't take this the wrong way, but I'm not looking for DARPA funding, and I don't give a fuck about DARPA. I've got a good day job, and I doubt DARPA would ever be able to match my working conditions, monetary compensation, and flexibility.
I like to discuss these things to expand my horizons. Slashdot has produced over the years many interesting discussions that expand my horizons (less so recently, aside from this thread--I've become more of a reddit lately). I enjoy discussing my ideas, and pushing my boundaries. The only reasons I'm discussing this here is because this thread will undoubtedly attract people that can expand my horizons. Quite frankly, it has achieved this, as I have found some additional reading already for my summer reading list. And I thoroughly enjoy this thread with you. Although you haven't asked as such, I am a solipsist at my core, so everything in life, this thread included, is mental masturbation. And that, in and of itself, is to be celebrated.
Well, hot damn. Thanks. Didn't realize he and I shared beliefs. Guess I've got some more reading to add to my summer reading list.
I should have said "non-determinate". Non-predictable is not sufficient, imho.
Non-determinate does not imply it does not converge. A transistor is a classic case of a non-determinate system, based on quantum effects, that converges. Because it is non-determinate, we have created clocks (i.e. synchronous computing) to sample the transistor only after it has converged. In other words, our logic systems for traditional computing are limited by our ability to create programs that rely upon non-deterministic behavior. This is the case of pretty much all computing, including current quantum computing, traditional synchronous computing, and research into asynchronous computing. I posit that we need to rethink this fundamental aspect of logic, to create a system that embraces non-deterministic behavior, but relies upon convergent behavior. Only in this way will we break free from "artificial" machine intelligence into the realm of "real" machine intelligence.
I didn't mean to imply that asynchronous computing is the only way to achieve this non-determinate behavior. A true random number generator indeed would do the trick. Network latency, as it involves external network traffic, is another for of non-deterministic behavior. Asynchronous computing does it rather directly, though. A transistor is a pretty good model for a neuron, except that neurons typically have dozens of inputs instead of only two.
There is plenty of evidence that our brain relies upon quantum behaviors. The sense of smell and the sense of taste, in particular, have been shown to have behavior that is best explained by quantum effects. The behavior of individual neurons is another area that is best explained by quantum effects. We know that a neuron *will* converge (i.e. fire) based upon certain inputs. We just don't know exactly *when* it will fire. Sort of like transistors.
I can go on. I haven't covered at all my models regarding the other human senses. Touch, vision, and hearing utilize our central nervous system to behave as sorts of Fourier transforms, transforming time-based data into frequency-based data. I suspect that the quantum effects sensed by the taste and smell are similarly transformed into frequency-based data. I firmly believe that the brain acts as a sort of pattern-finding engine. These patterns are far easier to discern in the frequency domain (my background includes signal processing and pattern finding, both of which I use in the financial world in combination with so-called learning systems to predict future risk and future prices of equities and commodities).
I am not an AI researcher; in fact, I believe that AI has fundamental problems that will prevent it from ever reaching true intelligence. But I am an applied AI software developer. I just think the term "AI" has loaded with false implications. I also think the current field is a dead end when it comes to creating true machine intelligence.
Chaos == determinate, non-predictable. I claim that determinism inherently rules out free will. I assume the human mind has free will, and that free will is a prerequisite for true intelligence (not simulating real intelligence). That assumption is a leap, and I fully understand and accept that. But, if you accept that assumption, a chaotic system cannot have true intelligence.
Asynchronous computing, using current models, does not produce or take advantage of quantum uncertainty. But I posit that they could, if designed for this. Instead, traditional computer design attempts to eliminate non-deterministic behavior. I state this (quantum uncertainty) as a potential for asynchronous computing, not as one that already exists. I'd love to see logic models where results are not deterministic, but do converge over time. In short, I'd like to see what an asynchronous computing model is capable of once one frees oneself from the current bounds of modern computing.
Network latency is most certainly non-determinate, at least in an open computer network. I'm not talking about latency as it relates to a single connection between two computers. I'm talking about latency that includes the cost of network collisions, which is determinate based upon the network traffic from other computers (presumably controlled by people that act not chaotically, but non-deterministicly).
Finally, I'm not trying to depict accurately the state of AI. I know quite well that these concepts are outside the norm of AI. In fact, I build learning systems for my day job--massively parallel computing that utilizes, among other things, neural networks, genetic algorithms, graph theory, etc. I'm trying to state what is required for true machine intelligence. This non-deterministic behavior is what will distinguish artificial intelligence and brain models from true machine intelligence.
True machine intelligence will not come from following the same standard old routes. I think there is some value to be had using massive parallel computing models where each node mimics a neuron, since these include the non-deterministic network latency I described earlier. Unfortunately, the resulting system that is required for modeling even moderately complex brains is enormous, far bigger than the biggest parallel clusters available today. An asynchronous computer is one way I think this effect (non-deterministic behavior) can be taken advantage of without spending billions (and it will be inherently faster because inter-"neuron" latency is reduced to nanosecond levels). I do not find much value in the effort to create true machine intelligence through the use of neural networks, genetic algorithms, and the such, although they do work well in determining pricing models for commodities & equities, as well as assessing risk, and these are both areas in which I utilize them.
You are correct in your assessment of my ideas as "a good philosophy". They are not practical ideas at this point, and they will not lead to any hardware or software designs any time soon. But these are the places where DARPA should be funding. They have a long and distinguished history of funding the Tesla-type research, not the Alexander Graham Bell-type research. There's already been tons of money, time, and effort poured down traditional AI research. What do we have as a result? Not much.
Er, my post was the "True AI won't happen until...". Seems I'm not too intelligent, myself, sometimes.
Shit, forgot to log in before posting. There. Oh, and for all of you young folk that think your ID is low, no, it isn't. Mine isn't even low. I forgot the login credentials for my first acct (in the 100s). Damn.
Caching proxies can be configured to do this at the site-level. I'm no squid expert, but I'm sure you can google some squid configurations that will do this if you are interested.
As you are also a good scientist, I'm assuming that when you say "55 degrees Kelvin", you mean "55 Kelvin", as there are no degrees with Kelvin.