Popcorn Sutton

I have to quote myself here, it's very easy to confuse expansion and contraction. After giving it some thought, I've decided that it can both be see as expansion or contraction. The system would have a multitude of experiences leading to one disposition. So given n occurrences, it equals n bits of information, leading to one result, adding n bits for the current disposition, both subordinating and superordinating to provide one result which equates to one bit. So 174936 bits lead to 1 result, in that tier one result, plus n bits for the input, adds 60 subordinate unconscious results which provides 10 bits for the superordinate tier, and the strongest superordinate bits become conscious.

It also implies that time is consistently subordinating, which provides support for contraction as opposed to expansion It's not a tangent either IMO, a computational mind requires external resources such a time and memory, just like a calculator.

"The question of whether machines can think is too meaningless to deserve discussion." Alan Turing. I've mentioned this several times here on the forums, but I don't think that it has fully sunk in yet. I used to argue that time is a dictionary, but after a very short moment, my friend on Facebook said why not a tuple? I looked into it, and it clicked. I think that you can get good results by treating it as a dictionary, but you won't get the best results unless you treat it as a tuple. If you treat t as a tuple, it's quantum, it's context sensitive, and it's dispositionally sensitive. It fits the notion of time perfectly. The physical implications are interesting to think about. One implication is that time itself is quantum. It's in superposition, it's both conscious and unconscious, and it gets prompted through radioactivity and interest.

I, personally, think of one bit as a sequence of occurrences. Any positive whole number of occurrences including zero.

It shouldn't be, you provided the source. I like to view reality as bits of information. As long as you can provide a sensory correlation between subjective and objective reality, consider whatever interests you as one bit. A bit of information can be an entire novel, a subatomic particle, the electromagnetic field, anything you can correlate, superimpose, superordinate, and label, is technically one bit. Computational neuroscience verifies this notion.

It is an argument from incredulity, sorry about that. It's not my field of expertise, but I have seen cells multiply in test tube environments. It's just strange to me to see how they can go from only one cell to a multitude of cells that are the same exact size as the original when we still don't know the origin of life. It's not like we can provide them with the resources when we don't know what they are. Again, this is an argument from incredulity.

Unicellular creatures may show simple behaviors, but we have yet to provide a good understanding of how one cell replicates exponentially while seemingly not having the resources to support the replication. It really is amazing to watch it happen.

According to connectionists, a concept is roughly equivalent to a neuron, so I guess that will have to do for now. That is the job of a theoretical physicist, not for a neuroscientist or biologist.

You're talking about externalized knowledge. Chomskyan linguists aren't looking for the chicken, we want to find the egg.

I'm not sure Moontanman. I was under the impression that if something is not a point of interest, then it doesn't have a definite location. I do think that radioactive decay plays a major role in prompting information though, so it does make sense to me. IMHO, if information is not radioactive, then it does not arise in the mind. I have to admit that it seems to be a very complicated task to provide an adequate theory of mind in terms of biophysical and chemical events. I don't think that it will never be done, but I do think that we need to be able to point at something and say with confidence that what we are looking at is in fact knowledge. I think that a lot of us are just waiting patiently for this answer. When we have it, it's going to be a game changer.

I actually believe the opposite. Nothing would exist of it weren't for quantum physics. Observation materializes reality. But even with this bit of information, even if we don't know what is real, we kind of have to assume that reality exists independent of observation in order to provide substantive explanations. http://en.m.wikipedia.org/wiki/Computational_neuroscience

Your point is not easy to argue. It's a matter of belief. I do believe that quantum physics is a major player in describing how the mind works, but classical mechanics clearly plays a role as well. You really can't have pattern recognition or even provide a pragmatic interface without classical mechanics. I think that the most promising avenue of research for determining the answer to this question is computational neuroscience.

The problem with Bayes is that if you automate the equation and use it to detect plausible inference, there is only one way you can detect the best answer, and the only way to do that is to question the algorithm every time it receives a new input. This would only work if the question was remembered only once or less because obviously if you question a person the same thing over and over, they will say a different phrase eventually. In my experience, a lot of actual humans have experiemented with this one. But why? Why? Why? Why? Why? Why? It's the only question word that I know of that can continually be answered. Indefinitely. But if you automate both the algorithm and the questioning of the algorithm, you can only hope that a human receives the answer because the actual chance of hearing the right answer at any given point is 1 over 7000000000000. 1/700000000000 approximately. The chance of any given person to reply at any given second is at a guess 100,000 in one second (whatever it may be). One person can only read one message every 10 minutes at most, and make inferences of their own at approximately 15-45 minutes before they conclude on the subject. I can do the math but it's going to take a minute. It's still going to take a while to evolve. 1/7000000000 people. 7000000000/ 52.1 / 7 / 24 / 60 / 10 - 45 / 7000000000. 7 billion people divided by 52.1 weeks in a year. That divided by 7 days in a week divided by 24 hours in a day divided by 10 to 45 minutes spent on inference divided by 7 billion people means that our chance of finding the quickest path of evolution is .00008% chance of one person finding the most likely answer in a single year on the best average.

People are using antiseptic soap now. It's doing a great job at fighting infections. I don't think you can buy it over the counter yet though.

Lucky for you guys, I know how to define the boundaries Take this example (in its simplicity). Evidence = ['my name is popcorn sutton'] Hypothesis = 'your name is popcorn' Add hypothesis to evidence and you get - ['your name is popcorn', 'my name is popcorn sutton'] There are two ways to define the boundaries, one is this- If the probability of 'n' given 'popcor' > .5 then add 'n' (= 'popcorn') Or If hypothesis = 'your name is popcornmy name is popcorn sutton' then if 'your name is popcorn' + 'my name is popcorn sutton' is in evidence, then the hypothesis equals 'your name is popcornmy name is popcorn sutton' I prefer the prior because it disregards spelling errors.

Can someone give an example of the mathematical process of Bayesian inference? I'm a strong supporter of it but I haven't taken an actual mathematics class that makes use of the equation. Can someone clarify the process step by step? I'll provide an example in computational linguistics lingo if someone can do me this favor.

Well, computational linguistics makes use of Bayesian inference in a different way then. The reason I say it gets smaller and smaller is because of language acquisition. Say that knowledge is evidence and output is a hypothesis, if knowledge consists of one billion trillion bits of information, using the relevant knowledge (evidence) could consist of one billion bits. If there is only one hypothesis (output) that is possible (or most probable) then the probability of that output could easily be 0.00000000000000000000000000000000001. But like I said, it still beats 0.000^10, 1. Because of this, all other relevant bits of information are not able to be put in the output because they don't suffice. It's like having subconscious thoughts. It's like ruling out the hypotheses that don't have as much evidence as the output.

I sincerely enjoyed reading this thread! Sorry I ended up deleting the original message. The intent was to say that Bayesian inference is applicable in all scenarios that we can think of. Given enough evidence, the likelihood of any hypothesis is going to be infinitesimally small, but there will still be one that is most likely.

You know, adding to this, have you ever heard of these so called demon messages when you play songs in reverse? Maybe the universe actually does exist in reverse... and we can even hear what the reverse universe has to say. This is just a speculation though but it's supported by evidence.

I forget the citation but I believe I heard something along these lines on the science channel. A father was rewinding a video tape and told his son, "[you know, even while rewinding the tape, the images are still obeying the laws of physics .]" I think it was through the wormhole. I think that it has implications and it may be possible that this particular universe can exist by our laws of physics in reverse.

Ok, so what does that tell us about knowledge? Why is RNA not commensurable to knowledge as well? The wikipedia says that it is a "[utility of transcription and translation]". I don't understand what that means exactly. The evidence suggests that it is stored in parts of the brain, but I don't think that knowledge is commensurable to a neuron. I think that a neuron is a container for the knowledge. I guess that it's not really an important distinction in the computational sense, but it would be interesting to point at something and say with confidence that it is knowledge. Here is an experiment. Find a correspondence between an area of the brain and something like snakes. Eliminate the RNA from that portion of the brain and stimulate it. See if it has the same effect.

People might know by now, the military in particular. My best guess is that RNA is a type of acquirable knowledge and it's structure interacts with other molecular components to cause a sort of fluctuation from within the cell. I call it a unit of knowledge, but we also accept by now that DNA is a type of knowledge as well. I don't think that anyone can truly tell you how either of these components work, but they are there and they play an important role. I actually have a friend who has alot of family involved in a particular type of intelligence who "had a slip" one day about this and said something along these lines, "knowledge is RNA." There are implications, and I think that they are apparent, but I hate inducing paranoia so I'll leave it be. The fact is that from what I've experienced using search algorithms and focusing techniques, the process prints one of two things, and they both look like DNA and RNA.

I agree with ed on this one. Personality involves motor processes, planning, comprehension, and imagination. The motor processes are frontal, imagination is near the supra marginal gyrus in the right hemisphere, emotions are behind the right eyebrow, planning is in the prefrontal cortex. Comprehension is in the wernickes area. I might even argue that the personality is almost completely synonomous with mind (and entirely synonomous if you consider yourself a behaviorist).

I thought about it for a little while and I decided that that is one of the nicest compliments I've ever received lolll. Thanks

Whatever wfu. Go enjoy your golf and $200 bottle of wine.