I think the effective voltage compression in the voltage/timing binary transmission model would approach 1/3 or 1/4. I cannot remember which one offhand. Jim Bromer
On Sun, Jun 23, 2019 at 1:38 PM Jim Bromer <[email protected]> wrote: > I should have said: The method that neurons form generative 'connections' > is irrelevant to the capability of neural activity to transmit data. The > brain must be able to form reactions and to make choices like inhibiting or > activating different kinds of reactions to some event. This means that the > brain must be reacting across some distances. It could be done by long > axons, I have no way of knowing. > > According to Indiana.edu an axon can grow as long as 5 feet. > > Afer thinking about Matt's response to Steve's remark and Alan's response > in the other thread I realized I probably misunderstood what Steve was > saying. But I started thinking about what he said (what I now think he > said). A number of years ago I discovered that if you sent two bits, one > sent by timing or placement within a timing frame, you could get some > compression by using the two forms of data representation. One by voltage > (in my theory) and the other by timing. (There is a technical dilemma in > using contemporary computer technology, because you are sort of using a > trinary voltage state, no voltage, low voltage, and high voltage. But if > the system was designed around an actual timing mechanism, and no voltage > was just a default state and it meant nothing is being transmitted in that > time frame whenever there is a no voltage reading on the receiver side then > the quasi-trinary aspect is just a part of a technical specification.) I > cannot remember if the compression approached 1/2 or 1/3 or 3/4. So now I > have two questions. If there were n dimensions to the data transmission > could the voltage conservation compression approach an exponential rate on > n? Or would it just be a geometric compression rate? There would be a cost > to such a system so it would not be completely exponential or completely > geometric regardless of the resultant compression rate. For instance in the > voltage/timing mechanism the compression of the voltage signals sent would > cost something in the time taken to send the data out. Oh yeah, I remember. > The 1/3 or 3/4 ratios had something to do with the actual cost in voltage > (of the data transmission) which is relevant in contemporary technology > because of battery usage and heat build up. > So if you had 3 physically very distinct binary dimensions to transmit > data within a circuit, using voltage, timing, and routing, could you reduce > representation to 1/8th? Even if the data had to be statically represented > using all 3 dimensional bits could the circuit be nested with similar > circuits and used for compressing computations? It is going to take me some > time to figure this out. > > Jim Bromer > > > On Thu, Jun 20, 2019 at 9:54 PM Jim Bromer <[email protected]> wrote: > >> I guess I should have not said that I totally agree with Steve's comment. >> When he said dimensions I was thinking more of types such as abstract types >> or something that is effectively similar. Suppose there was a non-standard, >> innovative mathematics that was able to effectively deal with data of >> different abstract types. Then it would be capable of calculating with >> different abstractions some of which might be said to play roles similar to >> dimensions in standard contemporary mathematics of measurable objects. >> >> The method that neurons form generative 'connections' is irrelevant to >> the capability of neural activity to transmit data. The brain must be able >> to form reactions and to make choices like inhibiting or activating >> different kinds of reactions to some event. This means that the brain must >> be reacting across some distances. It could be done by long synapses, I >> have no way of knowing. >> >> If natural neural networks are able to implement logical or symbolic >> functions then they certainly have the potential to transmit richer data >> that is able to encode a great many variations of data objects. So, >> regardless of the details of how firing 'connections' are formed, the model >> of thought that most of us feel is in the neighborhood of the ballpark if >> not in the dugout is some sort of variation of the computational model of >> mind. The idea that Hebbian theory might be used to proscribe a severe >> limitation on the range of neural symbolic processing is not supported by >> our experiences. >> Jim Bromer >> >> >> On Thu, Jun 20, 2019 at 7:33 PM Matt Mahoney <[email protected]> >> wrote: >> >>> I disagree. By what mechanism would neurons representing feet and meters >>> connect, but not kilograms and liters? >>> >>> Neurons form connections by Hebb's rule. Neurons representing words form >>> connections when they appear close together or in the same context. >>> >>> On Thu, Jun 20, 2019, 4:14 PM Jim Bromer <[email protected]> wrote: >>> >>>> Steve said: I strongly suspect biological synapses are tagged in some >>>> way to only connect with other synapses carrying dimensionally compatible >>>> information. >>>> >>>> I totally agree. So one thing that I am wondering about is whether that >>>> can be computed using a novel kind of mathematics? Intuitively, I would say >>>> absolutely. >>>> >>>> A truly innovative AI mathematical system would not 'solve' every AI >>>> problem but could it be developed so that it helped speed up and direct an >>>> initial analysis of input? Intuitively I am pretty sure it can be done, but >>>> I am not at all sure that I could come up with a method. >>>> Jim Bromer >>>> >>>> >>>> On Thu, Jun 20, 2019 at 1:13 PM Steve Richfield < >>>> [email protected]> wrote: >>>> >>>>> Jim, >>>>> >>>>> Many systems, e.g. while adding probabilities to compute probabilities >>>>> doesn't make sense; adding counts having poor significance, which can look >>>>> a lot like adding probabilities, can make sense to produce a count. >>>>> >>>>> Where this gets confusing is in sensory fusion. Present practice is >>>>> usually some sort of weighted summation, when CAREFUL analysis would >>>>> probably involve various nonlinearities to convert inputs to cannonical >>>>> form that make sense to add, followed by another nonlinearity to convert >>>>> the sum to suitable output units. >>>>> >>>>> I strongly suspect biological synapses are tagged in some way to only >>>>> connect with other synapses carrying dimensionally compatible information. >>>>> >>>>> Everyone seems to focus on values being computed, when it appears that >>>>> it is the dimensionality that restricts learning to potentially rational >>>>> processes. >>>>> >>>>> Steve >>>>> >>>>> On Thu, Jun 20, 2019, 9:14 AM Jim Bromer <[email protected]> wrote: >>>>> >>>>>> I originally thought about novel computational rules. Arithmetic is >>>>>> not reversible because a computational result is not unique for the input >>>>>> operands. That makes it a type of compression. Furthermore it uses a >>>>>> limited set of rules. That makes it a super compression method. >>>>>> >>>>>> On Thu, Jun 20, 2019, 12:08 PM Jim Bromer <[email protected]> >>>>>> wrote: >>>>>> >>>>>>> I guess I understand what you mean. >>>>>>> >>>>>>> On Thu, Jun 20, 2019, 12:07 PM Jim Bromer <[email protected]> >>>>>>> wrote: >>>>>>> >>>>>>>> I think your use of metaphors, especially metaphors that were >>>>>>>> intended to emphasize your thoughts through exaggeration, may have >>>>>>>> confused >>>>>>>> me. Would you explain your last post Steve? >>>>>>>> >>>>>>>> On Thu, Jun 20, 2019, 12:02 PM Steve Richfield < >>>>>>>> [email protected]> wrote: >>>>>>>> >>>>>>>>> Too much responding without sufficient thought. After a week of >>>>>>>>> thought regarding earlier postings on this thread... >>>>>>>>> >>>>>>>>> Genuine computation involves manipulating numerically expressible >>>>>>>>> value (e.g. 0.62), dimensionality (e.g. probability), and significance >>>>>>>>> (e.g. +/- 0.1). Outputs of biological neurons appear to fit this >>>>>>>>> model. >>>>>>>>> >>>>>>>>> HOWEVER, much of AI does NOT fit this model - yet still appears to >>>>>>>>> "work". If this is useful than use it, but there usually is no path to >>>>>>>>> better solutions. You can't directly understand, optimize, adapt, >>>>>>>>> debug, >>>>>>>>> etc., because it is difficult/impossible to wrap your brain around >>>>>>>>> quantities representing nothing. >>>>>>>>> >>>>>>>>> Manipulations that don't fit this model are numerology, not >>>>>>>>> mathematics, akin to bring astrology instead of astronomy. >>>>>>>>> >>>>>>>>> It seems perfectly obvious to me that AGI, when it comes into >>>>>>>>> being, will involve NO numerological faux "computation". >>>>>>>>> >>>>>>>>> Sure, learning could involve developing entirely new computation, >>>>>>>>> but it would have to perform potentially valid computations on it's >>>>>>>>> inputs. >>>>>>>>> For example, adding probabilities is NOT valid, but ORing them could >>>>>>>>> be >>>>>>>>> valid. >>>>>>>>> >>>>>>>>> Steve >>>>>>>>> >>>>>>>>> On Thu, Jun 20, 2019, 8:22 AM Alan Grimes via AGI < >>>>>>>>> [email protected]> wrote: >>>>>>>>> >>>>>>>>>> It has the basic structure and organization of a conscious agent, >>>>>>>>>> obviously it lacks the other ingredients required to produce a >>>>>>>>>> complete >>>>>>>>>> mind. >>>>>>>>>> >>>>>>>>>> Stefan Reich via AGI wrote: >>>>>>>>>> > Prednet develops consciousness? >>>>>>>>>> > >>>>>>>>>> > On Wed, Jun 19, 2019, 06:51 Alan Grimes via AGI < >>>>>>>>>> [email protected] >>>>>>>>>> > <mailto:[email protected]>> wrote: >>>>>>>>>> > >>>>>>>>>> > Yay, it seems peeps are finally ready to talk about this!! >>>>>>>>>> =P >>>>>>>>>> > >>>>>>>>>> > >>>>>>>>>> > Lets see if I can fool anyone into thinking I'm actually >>>>>>>>>> making >>>>>>>>>> > sense by >>>>>>>>>> > starting with a first principles approach... Permalink >>>>>>>>>> > < >>>>>>>>>> https://agi.topicbox.com/groups/agi/T395236743964cb4b-M686d9fcf7662ad8dc2fc1130 >>>>>>>>>> > >>>>>>>>>> > >>>>>>>>>> > >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> -- >>>>>>>>>> Please report bounces from this address to [email protected] >>>>>>>>>> >>>>>>>>>> Powers are not rights. >>>>>>>>>> >>>>>>>>>> >>>>>>>>>> ------------------------------------------ >>>>>>>>>> Artificial General Intelligence List: AGI >>>>>>>>>> Permalink: >>>>>>>>>> https://agi.topicbox.com/groups/agi/T395236743964cb4b-Mdc530e65efee5618dc6de900 >>>>>>>>>> Delivery options: >>>>>>>>>> https://agi.topicbox.com/groups/agi/subscription >>>>>>>>>> >>>>>>>>> *Artificial General Intelligence List >>> <https://agi.topicbox.com/latest>* / AGI / see discussions >>> <https://agi.topicbox.com/groups/agi> + participants >>> <https://agi.topicbox.com/groups/agi/members> + delivery options >>> <https://agi.topicbox.com/groups/agi/subscription> Permalink >>> <https://agi.topicbox.com/groups/agi/T395236743964cb4b-M9defff2ab5e8b39a818f88fa> >>> ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T395236743964cb4b-Mef1b3077e998d1c903fdffd3 Delivery options: https://agi.topicbox.com/groups/agi/subscription
