Re: [FRIAM] REPOST: The meaning of inner.
If you were to go about programming a computer to think about itself, how would you do it? Even if we program a computer to think about itself, the computer would be extremely bored, because he is as intelligent as a cash register or washing machine. He just follows commands, only extremely fast. You can program a computer to behave like a complex adaptive system which acts, reacts and learns. Such a system or agent is able to act flexible, adapting itself to the environment, choosing the right action. It has a kind of free will, because it can choose the action it likes. Here it makes more sense to develop software that thinks about itself, but if the system can only recognize a few categories, a sense of itself is not more than a faint emotion. To reach human intelligence, you need a vast number of computers, because the brain is obviously a huge distributed system. Then the interesting question is: can the system be aware of itself? It sounds paradox, but if we want to enable a system of computers to think about itself, we must prevent any detailed self-knowledge. If we could perceive how our minds work on the microscopic level of neurons, we would notice that there is no central organizer or controller. The illusion of the self would probably break down if a brain would be conscious of the distributed nature of it's own processing. In this sense, self- consciousness is only possible because the true nature of the self is not conscious to us.. The complex adaptive system in question is aware of what is doing only indirectly through and with the help of the external world. To be more precise, the system can only watch its own activity on a certain level: on the macroscopic level it can recognize macroscopic things, and on the microscopic level, it can recognize other microscopic things - a neuron can recognize and react to other neurons - but there is no level-crossing awareness of the own activity. So you have to build a giant system which consists of a huge number of computers, and only if it doesn't have the slightest idea how it works, it can develop a form of self-consciousness. And only if you take a vast number of items - neurons, computers or servers - the system is complex enough to get the impression that a single item is in charge.. Quite paradox, isn't it? But there is something else we need: the idea of the self must have a base, a single item to identify oneself with. Thus we need two worlds: one mental world where the thinking - the complex information processing - takes place, and where the system is a large distributed network of nodes, and one physical world where a single self walks around and where the system appears to be a single, individual item: a person. This physical world could also be any virtual world which is complex enough to support AI. Each of this worlds could be be realized by a number of advanced data centers. There are a number of conditions for both worlds: The hidden, mental world must be grounded in the visible, physical world, it must be complex enough to mirror it, and it must be fast enough to react instantly. Grounded means we need a 1:infinite connection between both worlds. The collective action of the hidden system must result in a single action of an item in the visible system. And a single instant in the visible system must in turn trigger a collective activity of the hidden system during perception. Every perception and action for the system must pass a single point in the visible, physical world. If both worlds are complex enough, then this is the point where true self-consciousness can emerge. To summarize, in order to build a computer system which is able to think about itself, we need to separate the thinking from the self: (a) a prevention of self-knowledge which enables self-awareness (b) a 1:infinite connection between two very complex worlds which are in coincidence with each other When we think, certain patterns are brought into existence. Since a brain contains more than 100 billion neurons, each pattern is a vast collection of nearly invisible little things or processes. When we think of ourselves, a pattern is brought into existence, too. It is the identification of a vast collection of nearly invisible little items with a single thing: yourself. Except the abstract idea, there is no immaterial self hovering over hundred billion flickering neurons. The idea of a self or soul as the originator of the own thoughts is an illusion - but you may ask if the self is unreal, then who is reading this?. So maybe it is more precise to say that the self is a confusing insight or an insightful confusion. The essence of self-consciousness seems to be this strange combination of insight and confusion. Self-consciousness is both: the strange, short-lived feeling associated with intricated patterns of feedback loops which arise if inconsistent items are
Re: [FRIAM] REPOST: The meaning of inner.
Jochen Fromm wrote: Since a brain contains more than 100 billion neurons, each pattern is a vast collection of nearly invisible little things or processes. For comparison, LANL Roadrunner has about 5 trillion transistors for the CPUs (~13000 PowerXCell 8i processors and ~6500 dual core Opterons) and another 800 trillion for RAM (~100 TB). FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
Re: [FRIAM] REPOST: The meaning of inner.
With a little reorganization and forethought, you can even have your own mini-supercomputer using banks of GPU cards to crunch vectors and matrices. See Nvidia's CUDA development system, and their Tesla computer system. - Ken -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Jochen Fromm Sent: Sunday, July 20, 2008 12:52 PM To: The Friday Morning Applied Complexity Coffee Group Subject: Re: [FRIAM] REPOST: The meaning of inner. Yes, an impressive supercomputer. I think it is much more difficult to use a supercomputer with a trillion operations per second than a huge cluster of ordinary computers, as you can find them in Google's data centers. -J. - Original Message - From: Marcus G. Daniels [EMAIL PROTECTED] To: The Friday Morning Applied Complexity Coffee Group friam@redfish.com Sent: Sunday, July 20, 2008 7:49 PM Subject: Re: [FRIAM] REPOST: The meaning of inner. For comparison, LANL Roadrunner has about 5 trillion transistors for the CPUs (~13000 PowerXCell 8i processors and ~6500 dual core Opterons) and another 800 trillion for RAM (~100 TB). FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
Re: [FRIAM] REPOST: The meaning of inner.
Jochen Fromm wrote: I think it is much more difficult to use a supercomputer with a trillion operations per second than a huge cluster of ordinary computers, as you can find them in Google's data centers. One code for investigating synthetic cognition is called PetaVision. This code was adapted to Roadrunner and, like LINPACK, exceeded 1000 trillion floating point operations a second in recent benchmarks. Another project is the Blue Brain project at EPFL. Codes like this are usually use MPI (message passing) and often latency limited (i.e. transaction speed is limited by the speed of light). For such applications, computers connected with ordinary networking just won't scale. To say it is more difficult to build systems and software to cope with that is really just to say they are hard problems. The main limitations to silicon system are heat and distance. Although there are multiple layers of circuitry on modern microprocessors (~10), nothing like the 3D integration that exists with the brain. Marcus FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
Re: [FRIAM] REPOST: The meaning of inner.
In my opinion, biologically detailed large-scale models of the brain offer little value if the system is not embedded in a physical world. It is a first step in the right direction to examine vision. The brain is an adaptive system which becomes useless if it is cut off the environment. This brain-scale simulation of the neocortex on the IBM Blue Gene/L supercomputer for instance has brought little new insight. Maybe it is useful to understand thalamocortical oscillations, or to understand how neural assemblies interact, but if you want to go beyond traditional AI, maybe it is not recommendable to build a biologically detailed large-scale model. A human brain has not only more than 100 billion neurons but also 100 trillion synapses. It is impossible to model this in the finest level of detail. I believe it is possible to achieve human-like cognitive performance and self-consciousness with computers, though, in the way I tried to describe in the first post: if the processing is parallel enough, if the model is not too biological, and if the system embedded in some kind of physical world (whether real or virtual). Maybe also a RoadRunner which controls an agent in the successor of SecondLife. Who knows.. Brain-scale simulation of the neocortex on the IBM Blue Gene/L supercomputer http://www.research.ibm.com/journal/rd/521/djurfeldt.html -J. - Original Message - From: Marcus G. Daniels [EMAIL PROTECTED] To: The Friday Morning Applied Complexity Coffee Group friam@redfish.com Sent: Sunday, July 20, 2008 10:48 PM Subject: Re: [FRIAM] REPOST: The meaning of inner. One code for investigating synthetic cognition is called PetaVision. This code was adapted to Roadrunner and, like LINPACK, exceeded 1000 trillion floating point operations a second in recent benchmarks. Another project is the Blue Brain project at EPFL. FRIAM Applied Complexity Group listserv Meets Fridays 9a-11:30 at cafe at St. John's College lectures, archives, unsubscribe, maps at http://www.friam.org
