MIND CONTROL SWEDEN 2010
The Mind Has No Firewall,,,
That some of today’s cutting-edge neuroscience breakthroughs in nanotechnology, computer-brain integration and information technologies not yet recognized because they are too controversial with regard to the prevailing legal and IT policy and medical diagnostics.
The age of pharmaceutical microchipping is now upon us. Novartis AG, one of the largest drug companies in the world, has announced a plan to begin embedding microchips in medications to create “smart pill” technology.
The microchip technology is being licensed from Proteus Biomedical of Redwood City, California. Once activated by stomach acid, the embedded microchip begins sensing its environment and broadcasting data to a receiver warn by the patient. This receiver is also a transmitter that can send the data over the internet to a doctor.
Pacemaker for Your Brain: Brain-to-Computer Chip Revolutionizes Neurological Therapy
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Mind uploading or whole brain emulation (sometimes called mind transfer) is the hypothetical process of scanning and mapping a biological brain in detail and copying its state into a computer system or another computational device. The computer would have to run asimulation model so faithful to the original that it would behave in essentially the same way as the original brain, or for all practical purposes, indistinguishably. The simulated mind is assumed to be part of a virtual reality simulated world, supported by a simplified body simulation model. Alternatively, the simulated mind could be assumed to reside in a computer inside (or connected to) ahumanoid robot or a biological body, replacing its brain.
Whole brain emulation is discussed as a “logical endpoint” of the topical computational neuroscience and neuroinformatics fields, both about brain simulation for medical research purposes. It is discussed in artificial intelligence research publications as an approach to strong AI. Among futurists and within thetranshumanist movement it is an important proposed life extensiontechnology, originally suggested in biomedical literature in 1971.It is a central conceptual feature of numerous science fiction novels and films.
Whole brain emulation is considered by some scientists as a theoretical and futuristic but possible technology, although mainstream research funders remain skeptical. Several contradictory and already passed attempts have been made during the years to predict when whole human brain emulation can be achieved. Substantial mainstream research and development are however being done in relevant areas including development of faster super computers, virtual reality, brain-computer interfaces, animalbrain mapping and simulation, and information extraction from dynamically functioning brains.
The question whether an emulated brain can be a human mind is debated by philosophers, and may be contradicted by the dualisticview of the human mind that is common in many religions.
2 Theoretical benefits
2.3 Multiple/parallel existence
3.1 Bekenstein bound
3.2 Computational issues
3.3 Philosophical issues
3.3.1 Copying vs. moving
3.4 Legal and economical issues
4 Relevant technologies and techniques
4.1 Simulation model scale
4.2 Scanning and mapping scale of an individual
4.3 Serial sectioning
4.4 Brain imaging
4.5 Brain-computer interfaces
5 Current research
6 Mind uploading in science fiction
7 Mind uploading advocates and critics
8 See also
10 External links
Neuron anatomical model
Simple artificial neural network
The human brain contains about 100 billion nerve cells calledneurons, each individually linked to other neurons by way of connectors called axons and dendrites. Signals at the junctures (synapses) of these connections are transmitted by the release anddetection of chemicals known as neurotransmitters. The established neuroscientific consensus is that the human mind is largely an emergent property of the information processing of thisneural network.
Importantly, many leading neuroscientists have stated they believe important functions performed by the mind, such as learning, memory, and consciousness, are due to purely physical and electrochemical processes in the brain and are governed by applicable laws. For example, Christof Koch and Giulio Tononiwrote in IEEE Spectrum:
“Consciousness is part of the natural world. It depends, we believe, only on mathematics and logic and on the imperfectly known laws of physics, chemistry, and biology; it does not arise from some magical or otherworldly quality.”
The concept of mind uploading is based on this mechanistic view of the mind, and denies the vitalist view of human life and consciousness.
Many eminent computer scientists and neuroscientists have predicted that computers will be capable of thought and even attain consciousness, including Koch and Tononi, Douglas Hofstadter, Jeff Hawkins, Marvin Minsky, Randal A. Koene, and Rodolfo Llinas.
Such a machine intelligence capability might provide a computational substrate necessary for uploading.
However, even though uploading is dependent upon such a general capability it is conceptually distinct from general forms of AI in that it results from dynamic reanimation of information derived from a specific human mind so that the mind retains a sense of historical identity (other forms are possible but would compromise or eliminate the life-extension feature generally associated with uploading). The transferred and reanimated information would become a form ofartificial intelligence, sometimes called an infomorph or “noömorph.”
Even if uploading is theoretically possible, the amount of storage and computational power required are difficult to predict. Nevertheless, many theorists have presented models of the brain and have established a range of estimates of the amount of computing power needed for partial and complete simulations (citations needed for Boahen, Modha, Izhikevich, Bostrom and Sandberg, others). Using these models, some have estimated that uploading may become possible within decades if trends such as Moore’s Law continue.
The prospect of uploading human consciousness in this manner raises many philosophical questions involving identity, individuality and the soul, as well as numerous problems of medical ethics and morality of the process.
 Theoretical benefits
A computer-based intelligence such as an upload could potentially think much faster than a human even if it was no more intelligent. Human neurons exchange electrochemical signals with a maximum speed of about 150 meters per second, whereas the speed of lightis about 300 million meters per second, about two million times faster. Also, neurons can generate a maximum of about 200 action potentials or “spikes” per second, whereas the number of signals per second in modern computer chips is about 2 GHz (about ten million times greater) and continually increasing. So even if the computer components responsible for simulating a brain were not significantly smaller than a biological brain, and even if the temperature of these components was not significantly lower, Eliezer Yudkowsky of theSingularity Institute for Artificial Intelligence calculates that a simulated brain could run about 1 million times faster than a real brain, experiencing about a year of subjective time in only 31 seconds of real time.
Main article: Digital immortality
In theory, if the information and processes of the mind can be disassociated from the biological body, they are no longer tied to the individual limits and lifespan of that body. Furthermore, information within a brain could be partly or wholly copied or transferred to one or more other substrates (including digital storage or another brain), thereby reducing or eliminating mortality risk. This general proposal appears to have been first made in the biomedical literature in 1971 by renowned University of Washington biogerontologist George M. Martin.
 Multiple/parallel existence
Another concept explored in, is the idea of more than one running “copy” of a human mind existing at once. Such copies could potentially allow an “individual” to experience many things at once, and later integrate the experiences of all copies into a central mentality at some point in the future, effectively allowing a single sentient being to “be many places at once” and “do many things at once”; this concept has been explored in fiction. Such partial and complete copies of a sentient being raise interesting questions regarding identity and individuality.
 Bekenstein bound
The Bekenstein bound is an upper limit on information that can be contained within a given finite region of space which has a finite amount of energy or, conversely, the maximum amount of information required to perfectly describe a given physical system down to the quantum level.
An average human brain has a weight of 1.5 kg and a volume of 1260 cm3. The energy (E = m·c2) will be 1.34813·1017 J and if the brain is approximate to a sphere then the radius (V = 4·π·r3/3) will be 6.70030·10-2 m.
The Bekenstein bound (I ≤ 2·π·r·Eħ·c·ln 2) will be 2.58991·1042 bitand represent the maximum information needed to perfectly recreate the average human brain down to the quantum level. This implies that the number of different states (Ω=2I) of the human brain (and of the mind if the physicalism is true) is at most 107.79640·1041.
 Computational issues
Futurist Ray Kurzweil‘s projected supercomputer processing power based on Moore’s law exponential development of computer capacity. Here the computational capacity doubling time is assumed to be 1.2 years.
Regardless of the techniques used to capture or recreate the function of a human mind, the processing demands are likely to be immense, due to the large number of neurons in the human brain along with the considerable complexity of each neuron.
Henry Markram, lead researcher of the “Blue Brain Project”, has stated that “it is not [their] goal to build an intelligent neural network”, based solely on the computational demands such a project would have.
It will be very difficult because, in the brain, every molecule is a powerful computer and we would need to simulate the structure and function of trillions upon trillions of molecules as well as all the rules that govern how they interact. You would literally need computers that are trillions of times bigger and faster than anything existing today.
Advocates of mind uploading point to Moore’s law to support the notion that the necessary computing power may become available within a few decades. However, the actual computational requirements for running an uploaded human mind are very difficult to quantify, potentially rendering such an argument specious.
 Philosophical issues
 Copying vs. moving
Another philosophical issue with mind uploading is whether an uploaded mind is really the “same” sentience, or simply an exact copy with the same memories and personality; or, indeed, what the difference could be between such a copy and the original (see theSwampman thought experiment). This issue is especially complex if the original remains essentially unchanged by the procedure, thereby resulting in an obvious copy which could potentially have rights separate from the unaltered, obvious original.
Most projected brain scanning technologies, such as serial sectioning of the brain, would necessarily be destructive, and the original brain would not survive the brain scanning procedure. But if it can be kept intact, the computer-based consciousness could be a copy of the still-living biological person. It is in that case implicit that copying a consciousness could be as feasible as literally moving it into one or several copies, since these technologies generally involve simulation of a human brain in a computer of some sort, and digital files such as computer programs can be copied precisely. It is usually assumed that once the versions are exposed to different sensory inputs, their experiences would begin to diverge, but all their memories up until the moment of the copying would remain the same.
The problem is made even more serious by the possibility of creating a potentially infinite number of initially identical copies of the original person, which would of course all exist simultaneously as distinct beings. The most parsimonious view of this phenomenon is that the two (or more) minds would share memories of their past but from the point of duplication would simply be distinct minds (although this is complicated by merging). Many complex variations are possible.
Depending on computational capacity, the simulation may run at slower or faster simulation time as compared to the elapsed physical time, resulting in that the simulated mind would perceive that the physical world is running in slow motion or fast motion respectively, while biological persons will see the simulated mind in fast or slow motion respectively.
A brain simulation can be started, paused, backed-up and rerun from a saved backup state at any time. The simulated mind would in the latter case forget everything that has happened after the instant of backup, and perhaps not even be aware that it is repeating itself. An older version of a simulated mind may meet a younger version and share experiences with it.
 Legal and economical issues
See also: Ship of Theseus
The only limited resources in a simulated world are computational resources, meaning simulation speed, and intellectual properties. In a simulated society, rich simulated minds may pay for faster simulation time than others.
It may be difficult for authorities to supervise that human rights are not threatened in any computer in the world. It might for example be tempting for social science researchers to expose simulated minds, or whole isolated societies of simulated minds, to controlled experiments, where many copies of the same minds, or repeated reruns of the same simulation, are exposed to different test
EURON: European Robotics research Network
“EURON is a shorthand for “EUropean RObotics research Network”. It is the community of more than 225 academic and industrial groups in Europe with a common interest in doing advanced research and development to make better robots.”
The Network brings together researchers and commercial companies working on artificial perception systems to model neuronal functions and cognitive processes, to optimize existing learning algorithms and to realize intelligent artificial systems.
Cyberhand is a project funded by EU Future Emerging Technology Program robotic hand for replacement of lost limbs. The hand is designed to respond to signals from the human nervous system.
BBP is a massive cooperative project of EPFL (Switzwerland) and IBM. It uses IBMs super computer Blue Gene to through reverse engineering copy the whole human brain.
The Berlin Brain Computer Interface (BBCI) is a collaboration between German researchers to develop BCI technology for commercial and medical uses.
A 7 million euros EC-funded collaboration among 15 different laboratories in 7 countries for the purpose of developing virtual reality environments with BCI applications.
SMARTER THAN YOU THINK
Aiming to Learn as We Do, a Machine Teaches Itself
By STEVE LOHR
Published: October 4, 2010
Give a computer a task that can be crisply defined — win at chess, predict the weather — and the machine bests humans nearly every time. Yet when problems are nuanced or ambiguous, or require combining varied sources of information, computers are no match for human intelligence.
Few challenges in computing loom larger than unraveling semantics, understanding the meaning of language. One reason is that the meaning of words and phrases hinges not only on their context, but also on background knowledge that humans learn over years, day after day.
Since the start of the year, a team of researchers atCarnegie Mellon University — supported by grants from the Defense Advanced Research Projects Agency andGoogle, and tapping into a research supercomputing cluster provided by Yahoo — has been fine-tuning a computer system that is trying to master semantics by learning more like a human. Its beating hardware heart is a sleek, silver-gray computer — calculating 24 hours a day, seven days a week — that resides in a basement computer center at the university, in Pittsburgh. The computer was primed by the researchers with some basic knowledge in various categories and set loose on the Web with a mission to teach itself.
“For all the advances in computer science, we still don’t have a computer that can learn as humans do, cumulatively, over the long term,” said the team’s leader, Tom M. Mitchell, a computer scientist and chairman of the machine learning department.
The Never-Ending Language Learning system, or NELL, has made an impressive showing so far. NELL scans hundreds of millions of Web pages for text patterns that it uses to learn facts, 390,000 to date, with an estimated accuracy of 87 percent. These facts are grouped into semantic categories — cities, companies, sports teams, actors, universities, plants and 274 others. The category facts are things like “San Francisco is a city” and “sunflower is a plant.”
NELL also learns facts that are relations between members of two categories. For example, Peyton Manning is a football player (category). The Indianapolis Colts is a football team (category). By scanning text patterns, NELL can infer with a high probability that Peyton Manning plays for the Indianapolis Colts — even if it has never read that Mr. Manning plays for the Colts. “Plays for” is a relation, and there are 280 kinds of relations. The number of categories and relations has more than doubled since earlier this year, and will steadily expand.
The learned facts are continuously added to NELL’s growing database, which the researchers call a “knowledge base.” A larger pool of facts, Dr. Mitchell says, will help refine NELL’s learning algorithms so that it finds facts on the Web more accurately and more efficiently over time.
NELL is one project in a widening field of research and investment aimed at enabling computers to better understand the meaning of language. Many of these efforts tap the Web as a rich trove of text to assemble structured ontologies — formal descriptions of concepts and relationships — to help computers mimic human understanding. The ideal has been discussed for years, and more than a decade ago Sir Tim Berners-Lee, who invented the underlying software for the World Wide Web, sketched his vision of a “semantic Web.”
Today, ever-faster computers, an explosion of Web data and improved software techniques are opening the door to rapid progress. Scientists at universities, government labs, Google, Microsoft, I.B.M. and elsewhere are pursuing breakthroughs, along somewhat different paths.
For example, I.B.M.’s “question answering” machine, Watson, shows remarkable semantic understanding in fields like history, literature and sports as it plays the quiz show “Jeopardy!” Google Squared, a research project at the Internet search giant, demonstrates ample grasp of semantic categories as it finds and presents information from around the Web on search topics like “U.S. presidents” and “cheeses.”
Still, artificial intelligence experts agree that the Carnegie Mellon approach is innovative. Many semantic learning systems, they note, are more passive learners, largely hand-crafted by human programmers, while NELL is highly automated. “What’s exciting and significant about it is the continuous learning, as if NELL is exercising curiosity on its own, with little human help,” said Oren Etzioni, a computer scientist at the University of Washington, who leads a project called TextRunner, which reads the Web to extract facts.
Computers that understand language, experts say, promise a big payoff someday. The potential applications range from smarter search (supplying natural-language answers to search queries, not just links to Web pages) to virtual personal assistants that can reply to questions in specific disciplines or activities like health, education, travel and shopping.
“The technology is really maturing, and will increasingly be used to gain understanding,” said Alfred Spector, vice president of research for Google. “We’re on the verge now in this semantic world.”
With NELL, the researchers built a base of knowledge, seeding each kind of category or relation with 10 to 15 examples that are true. In the category for emotions, for example: “Anger is an emotion.” “Bliss is an emotion.” And about a dozen more.
-ORGANIZATIONS CONCERNED WITH ILLEGAL EXPERIMENTATION AND-
Committee on the Public Understanding of Science
The Royal Society
6-9 Carlton House Terrace
Fax +44 (0)20 7839 5561
Federation of American Scientists
1717 K St., NW Suite 209
Washington, DC 20036
The Lay Institute
Nick Begich, Executive Director
Mind Justice 46
Cheryl Welsh, Executive Director
The Stockholm International Peace Research Institute
9 SE-169 70
Phone: +46-8-655 97 00
Fax: +46-8-655 97 33
Sunshine Project Germany
The Sunshine Project
Phone: +49 40 431 88 001
Fax: +49 40 67 50 39 88
Introducing Transcranial Magnetic Stimulation (TMS) and its Property of Causal Inference in
Investigation Brain-Function Relationships
Dennis J. L. G. Schutter, Jack Van Honk and Jaak Panksepp
Journal of Cognitive Liberties
Center for Cognitive Liberties and Ethics
The Mind Has No Firewall”
Parameters, spring 1998, pp. 84-92.
Timothy L. Thomas
National Defense University
National War College, CDR Debra O’Maddrell 48
Therapeutic Application of repetitive Tran cranial magnetic stimulation: A Review
Eric M. Wasserman and Sarah H. Lasanby
The best laid plans…
Interview with Dr. Randal A. Koene on the Sunday Evening Update of Imminst.org (October 25, 2009)
“Randal Koene on Whole Brain Emulation” at davidorban.com
AGI-08 discussion session on Neural Network and Brain Modeling chaired by Dr. Randal Koene
Whole Brain Emulation Workshop
Brain emulation, the possible future one-to-one modelling of the function of the human brain, is academically interesting and important for several reasons:
- Brain emulation would itself be a test of many ideas in the philosophy of mind and philosophy of identity, or provide a novel context for thinking about such ideas.
- It may represent a radical form of human enhancement different from other forms.
- Brain emulation is the logical endpoint of computational neuroscience’s attempts to accurately model neurons and brain systems.
- Brain emulation would help understand the brain, both in the lead-up to successful emulation and afterwards by providing a perfect test bed for neuroscience experimentation and study.
- Neuromorphic engineering based on partial results would be useful in a number of applications such as pattern recognition, AI and brain-computer interfaces.
- As a research goal it might be a strong vision to stimulate computational neuroscience.
- As a case of future studies it represents a case where a radical future possibility can be examined in the light of current knowledge.
- The economic impact of copyable brains would be immense, and have profound societal consequences.
- If brain emulation of particular brains is possible and affordable, and if the concerns of individual identity can be met, such emulation would enable backup copies and “digital immortality”.
Resources: Brain Emulation Roadmap
Pacemaker for Your Brain: Brain-to-Computer Chip Revolutionizes Neurological Therapy
ScienceDaily (June 29, 2010) — By stimulating certain areas of the brain,,,