Quantum Computing Lecture 3: Application

Mountain View CA, July 28, 2020
Slides: http://slideshare.net/LaBlogga
Quantum Computing
Lecture 3: Application
Melanie Swan
“Living things are made of atoms according to the laws of
physics, and the laws of physics present no barrier to
reducing the size of computers until bits are the size of
atoms and quantum behavior holds sway”
— Richard P. Feynman (1985)

28 July 2020
B/CI Cloudmind 1
 A brain is a Merkle forest of ideas
 A group of Merkle trees, each calling
an arbitrarily-large thought trajectory
 Brain DAC II: IPLD for the Brain
 Thought content compatibility through
multi-hash protocols and Merkle roots
 Blockchain overlay realizes B/CI
cloudminds through secure thought
interoperability between minds
 IPLD is an overlay for the web
 IPLD for the Brain is an overlay for
cloudminds
IPLD for the Brain
IPLD for the Brain Overview

28 July 2020
B/CI Cloudmind
Theoretical Model of Quantum Reality
 Quantum reality is information-theoretic and computable
 Lecture 1: Quantum Computing basics (hardware)
 Lecture 2: Advanced concepts (control software between
macroscale reality and quantum microstates)
 Lecture 3: Speculative application (B/CI neuronanorobot network)
2

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B/CI Cloudmind
 Agenda
 Part 1: Neuroscience Basics
 The Brain
 Neural Signaling
 Part 2: Nanorobots
 Medical Nanorobots
 Neuronanorobots
 Neurocurrencies
 Part 3: B/CI Neuronanorobot Network
 BioBlockchain Neuroeconomy
 IPLD for the Brain
 Conclusion
3
Quantum Computing
3. Application

28 July 2020
B/CI Cloudmind
The Brain
4
Source: DeFelipe, J. (2010). From the connectome to the synaptome: an epic love story. Science. 330:1198–1201.
 The bulk properties of the brain remain elusive
Human brain connectivity:
diffusion tensor imaging of the
human brain obtained from 3-
tesla MRI sequences (2010)
A drawing showing
two nerve cells from
the spinal cord of the
ox (Gerlach, 1872)
1872 2010

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B/CI Cloudmind
Inspiration
5
Source: Davies, P. (2019). The Demon in the Machine.
 What is Life?
 How do the hardware and the
software of life go together?
 Information technology approach
(Davies, 2019)
 Software
 Physics as information theory,
instructions, and computability
 Hardware
 Physics as matter, forces, and energy

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B/CI Cloudmind 6
BCI Technologies
 BCI technology platforms and functionality
 Existing core technology: BCI (Brain-Computer Interface)
 A wired brain and an external device, using electrical brain
waves (EEG) to control computer cursors or neuroprosthetics
 220,000 cochlear implants worldwide as of 2010 (NIH)
 Proposed technology: B/CI (Brain/Cloud Interface)
 Safely connect the human brain with the internet cloud with an
on-board ecosystem of neuronanorobots (medical nanorobots
designed to operate in the brain)
BCI Technologies Functionality
Core BCI (brain-computer inferface) Prosthetic limb and cursor control
Cloudmind B/CI (brain/cloud interface)
(individual and group)
Productivity, well-being, and enjoyment
B/CI Source: Martins et al. Human Brain/Cloud Interface. Front. Neurosci, 13(112):1-24, 2019.

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B/CI Cloudmind 7
B/CI Cloudmind
 Cloudmind: one or more minds connected to the cloud
 An individual mind operating on the internet
 Multiple human and machine minds collaborating
 ‘Mind’ generally denotes an entity with processing capability
(not necessarily a biological mind that is conscious)
 Minds are interfaced to the internet cloud through the
B/CI (network of neuronanorobots)
 B/CIs could allow individuals to be more highly connectable not
only to communications networks but also to other minds,
enabling new kinds of learning and interaction
 Individual and group cloudminds could pursue various
productivity, well-being, and enjoyment activities
Sources: Swan, M. The Future of Brain-Computer Interfaces: Blockchaining Your Way into a Cloudmind. Journal of Evolution and
Technology 26(2), 2016. Swan, M. Transhuman Crypto Cloudminds. The Transhuman Handbook. Springer. Pp. 513-527, 2019.

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B/CI Cloudmind 8
B/CIs (brain/cloud interface technologies) are a
next-generation technology needed
1. (short-term) to cope with the modern reality of
science and technology outpacing biology
2. (long-term) to enable new physical and mental
resource coordination capabilities to evolve
towards a Kardashev-plus society (marshalling
tangible and intangible resources on a beyond-
planetary basis)
Thesis

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B/CI Cloudmind 9
Kardashev-plus Society
 Large-scale vision for societal advance
 Kardashev levels based on the amount of energy marshalled
 Current estimate of human progress
 Type 0.7 civilization (Kaku, 2018)
 Type 1 (100 years) if energy consumption increases 3%/year
 Kardashev-plus society
 Extending Kardashev’s vision, marshal all resources, tangible
and intangible, mental and physical, not only energy as a
central resource, for society’s long-term flourishing
Civilization Energy Marshalling Energy Consumption
Type I: Planetary
Civilization
Use all the energy of the sunlight that
falls on that planet
1016 W ≈4×1019 erg/sec (4×1012 watts)
Type II: Stellar Civilization Use all the energy that the sun
produces
1026 W ≈4×1033 erg/sec (4×1026 watts)
Luminosity of the Sun
Type III: Galactic
Civilization
Use the energy of the entire galaxy 1036 W ≈4×1044 erg/sec (4×1037 watts)
Luminosity of the Milky Way
Note: The erg (Greek ergon: work, task) is a unit of energy equal to 10-7 joules in the centimeter-gram-second system of units.
Erg/sec is a unit of energy or work per second

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B/CI Cloudmind 10
B/CI Neuronanorobot Network Realization
1. Hardware platform
 Quantum computing
2. Control software
 Holographic control theory (based on
the AdS/CFT correspondence) as a
universal mechanism to orchestrate
macroscale-quantum domains
 Here, lever for macroscale control of
the quantum computing cloud
environment for B/CI
3. Application software
Modeling Quantum Reality
 Bio-blockchain neuroeconomy as the operating
software of the in-brain B/CI neuronanorobot network

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B/CI Cloudmind
Quantum Computing and Neuroscience
 3D representation: 3D brain suited to analogous 3D
representation in quantum computing models
 Hodgkin-Huxley model (1963)
 Conduction of the electrical impulse through the axon
 Basis for models of neural signaling
 Neuromorphic quantum version of Hodgkin-Huxley
 Implement the three ion channels of the axon
 Potassium, sodium, chloride
 Signal source and output
 Execution: memristors, resistors, capacitor
 Implication: generic model for constructing
neuron networks with quantum state inputs
11
Source: Gonzalez-Raya, T., Solano, E. & Sanz, M. Quantized Three-Ion-Channel Neuron Model for Neural Action Potentials,
arXiv:1906.07570v2 [q-bio.NC], 2020.

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B/CI Cloudmind
 Agenda
 The Brain
 Neuronanorobots
 Neurocurrencies
 Conclusion
12
Quantum Computing
3. Application

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B/CI Cloudmind 13
Human Brain
86 billion Neurons and 200 trillion Synapses
 Size of neural cell populations in the brain
 Avogadro’s number: ~a trillion trillion, used to measure
molecular volumes in biology and chemistry
 A quantum computer with 79 entangled qubits (systems
currently have 20 qubits) has an Avogadro number of states
 2n scaling: 9-qubit system (29) represents 512 states
 Avogadro number of transactions processed by neural system
Entity Size Estimate
Neurons 86 x 109 86,000,000,000 86 billion
Cerebellum (80%) 69 x 109 69,030,000,000 69 billion
Cerebral cortex (19%) 16 x 109 16,340,000,000 16 billion
Glial cells 86 x 109 86,000,000,000 86 billion
Synapses 2.42 x 1014 242,000,000,000,000 240 trillion
Avogadro’s number 6 x 1023 600,000,000,000,000,000,000,000 0.6 trillion x 1 trillion
Source: Martins et al. Human Brain/Cloud Interface. Front. Neurosci, 13(112):1-24, 2019.

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B/CI Cloudmind 14
Neurons, Synapses, and Glial Cells
 Neuron: electrically-excitable cell that communicates
with other cells by sending a signal called an action
potential across synapses (specialized connections)
 Comprised of a cell body (soma), a long thin axon insulated
by a myelin sheath for outbound signaling, and multiple
dendrites for receiving inbound signals
 Glial cells: non-neuronal cells
 Insulate neurons from each other, facilitate signaling, supply
nutrients, recycle neurotransmitters

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B/CI Cloudmind
State-of-the-art: Connectome Mapping
15
Source: Wang et al. The Allen Mouse Brain Common Coordinate Framework: A 3D Reference Atlas. Cell 181:1-18, 2020.
 Allen Mouse Brain Atlas (2020)
 3D mapping of the mouse brain at single cell resolution

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B/CI Cloudmind
Functional Map of Neuronal Connections
16
Source: Cook, Steven J. et al. Whole-animal connectomes of both Caenorhabditis elegans sexes. Nature. (571):63-89, 2019.
 C. elegans motor neurons (2019)
 Functional connections of motor neurons

28 July 2020
B/CI Cloudmind
 Agenda
 The Brain
 Neuronanorobots
 Neurocurrencies
 Conclusion
17
Quantum Computing
3. Application

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B/CI Cloudmind 18
Neural Signaling
 Neurons send and receive signals
 To send a signal, an axon transmits
information from the neuron to neighboring neurons
 To receive a signal, a neuron’s dendrites receive information
sent by the axons of other neurons
 Neuronal signaling is both electrical and chemical
 Electrical: Axons transmit electrical pulses called action
potentials which travel along the axon like a wave
 Action potential is a short electrical pulse that is 0.1 V in
amplitude and lasts for one millisecond
 The action potential is sent along the axon to the axon
terminals in the synaptic nerve endings, from which the axon
contacts the dendrites of other neurons
Source: Nicholls et al. From Neuron to Brain 5th Edition. Sunderland MA: Sinauer Associates, Inc., 2012.

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B/CI Cloudmind 19
Neural Signaling
 Synapses
 Pre-synaptic terminal on the outbound neuron
 Post-synaptic terminal on receiving neuron dendrites
 Synaptic cleft (20 nm gap between them)
 Chemical: Electrical action potential transmitted along
the axons cannot bridge the synaptic cleft
 Converted for transmission across the synaptic cleft between
one neuron’s axon and another’s dendrites into chemical
messengers called neurotransmitters
 Chemical neurotransmitters are stored in vesicles (spherical
bags) in the synaptic terminal at the nerve ending to be
available for release across the synaptic junction

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B/CI Cloudmind 20
Neural Signaling
 Pre-synaptic terminal
 Arrival of an electrical action potential
 Voltage-gated calcium channels open
 Disgorge calcium into the terminal bulb
 Synaptic cleft
 Calcium triggers synaptic terminal-based vesicles to
release neurotransmitters into the synaptic cleft
 Neurotransmitter diffuses across the gap in less than
a millisecond
 Post-synaptic terminal
 Neurotransmitter activates membrane receptors in
the dendrites of the receiving neuron
Source: Shepherd, G.M. The Synaptic Organization of the Brain. An Introduction. New York: Oxford University Press, 1974.

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B/CI Cloudmind
Complex interworking of neurotransmitters
Neuromodulator Receptor Cycle
 Autonomous processes
 Lateral mobility and allostery
(local recycling) suggest a
new understanding of
presynaptic inhibition
neuromodulation
 MOR opioid receptors
 Diffusely distributed and
laterally mobile across the
axon surface
 Recycle locally, separate
behavior from the synaptic
vesicle cycle
21
Source: Jullie et al., (2019). A Discrete Presynaptic Vesicle Cycle for Neuromodulator Receptors. Neuron.
MOR (mu-type opioid receptor): a family A GPCR that
mediates presynaptic inhibition and postsynaptic
neuromodulatory effects of opioid peptides and is a
target of clinically important opioid analgesic drugs

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B/CI Cloudmind
Information Encoding in Neural Signaling
22
Source: Steinbrecher, G.R. et al., (2019). Quantum Optical Neural Networks. npj Quantum Information. 5(60):1-9.
 Signal processing problem
 Experimental data of neural spikes (signals)
 Theoretical models propose different ideas about
how the brain is encoding information with signals
1. Rate coding
2. Firing time with regard to a reference signal (e.g. a background
oscillation)
3.
4.
Simultaneous firing of
several neurons as a
token of information
Relative timing of spikes
(the neuron that fires first
conveys a more
important signal)

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B/CI Cloudmind
 Agenda
 The Brain
 Neuronanorobots
 Neurocurrencies
 Conclusion
23
Quantum Computing
3. Application

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B/CI Cloudmind 24
Nanorobot size: ~1,000 nm
 Size of biological entities and medical nanorobots
Entity Size (microns) Size (nm)
Human Body and Circulatory System
Human hair 100 microns (17-181 µm range) 100,000 nm
Red blood cell 7 microns 7,000 nm
Smallest capillaries 3 microns 3,000 nm
Medical Nanorobots
Clottocytes (artificial platelets) 2 microns 2,000 nm
Microbivores (artificial phagocytes) 3.4 microns 3,400 nm
Respirocytes (artificial red blood cells) 2-3 microns 2,000-3,000 nm
Chromallocytes (chromatic replacement) 5 microns 5,000 nm
Vasculoids (cell transporter boxcar) 100 x 6 microns 100,000 x 6,000 nm
Nanorobot components 1-10 nm
Vascular Cartographic Scanning Nanodevice
(for connectome mapping)
1 micron 1,000 nm
Source: Freitas Jr., Robert A. 2000, 2005, 2012, http://www.imm.org

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B/CI Cloudmind
Respirocytes (artificial red blood cells)
25
Source: Freitas, R.A. Jr. (2016). The Alzheimer Protocols: A Nanorobotic Cure for Alzheimer’s Disease and Related
Neurodegenerative Conditions. IMM Report No. 48, June 2016. http://www.imm.org/Reports/rep048.pdf. (artwork by Forrest Bishop)
 Bloodborne device made of 18 billion
precisely arranged atoms
 Spherical 1-micron diamondoid (min size)
 Onboard pressure tanks holding 3 billion oxygen (O2)
and carbon dioxide (CO2) molecules
 Active pumpingvia glucose oxidation
 Mimics the action of natural
hemoglobin(Hb)-filled red blood cells
 Oxygen pumped out of the device by
molecular sorting rotors
 Carbon dioxide pumped in
 Lung-based exchange of
oxygen and carbon dioxide
through blood circulation

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B/CI Cloudmind
Microbivores (artificial immune cells)
26
Microbivore captures and engulfs a microbe
Neurodegenerative Conditions. IMM Report No. 48, June 2016. http://www.imm.org/Reports/rep048.pdf. (artwork by Forrest Bishop)
 Oblate spheroidal device (diamond and sapphire)
 3.4 microns in diameter x 2.0 microns in diameter
 610 billion precisely arranged structural atoms in a
gross geometric volume of 12.1 micron3 and a dry
mass of 12.2 picograms
 Extend capacity of white blood cells
 Phagocytose and kill microbial invaders in the
bloodstream
 Faster than antibiotics

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B/CI Cloudmind
Chromallocyte (chromosome replacement)
27
Cell nucleus
 Lozenge-shaped device
 5.05 microns in length (69 micron3 in
volume)
 Consumes 50-200 pW of power
(normal) and 1000 pW power (burst;
out-messaging during treatment)
 Chromosome replacement therapy
 Replace chromatin contents of a living
cell nucleus with a pre-synthesized
copy of chromosomes
 Estimated 3 hour chromosome
replacement therapy clinically
performed by professionals
Neurodegenerative Conditions. IMM Report No. 48, June 2016. http://www.imm.org/Reports/rep048.pdf. (images by E-spaces)
Chromatic replacement
Chromallocyte docking

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B/CI Cloudmind
 Agenda
 The Brain
 Neuronanorobots
 Neurocurrencies
 Conclusion
28
Quantum Computing
3. Application

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B/CI Cloudmind
Neuronanorobots
 Three species of neuronanorobots
correspond to the different phases
of neural signaling
 Axonal endoneurobots
 Align with the axon’s transmission of
the electrical action potential
 Synaptobots
 Aid in signal transmission across the
synaptic cleft between neurons
 Gliabots
 Support the glial cells that facilitate
neural signaling
29
Source: Martins et al. Human Brain/Cloud Interface. Front. Neurosci, 13(112):1-24, 2019.
Axonal
endoneurobot
Gliabot Synaptobot
Gliabots
Synaptobots

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B/CI Cloudmind 30
Neuronanorobots
 B/CI comprised of neuronanorobots to instantiate and
enhance neural signaling
 Neural cells and neuronanorobot complements
 Axonal endoneurobot corresponds to axons
 Synaptobot relates to synapses
 Gliabot linked to glial cells
Neural Cells Function Neuronanorobot
Complement
Number of Nanorobots
Neurons
Axon beginning (cell body) Send signal Axonal
endoneurobot
1/neuron 86 billion
Axon ending (pre-synaptic terminal) Send signal Synaptobot ~2300/neuron 200 trillion
Dendrite (post-synaptic terminal) Receive signal
Glial cells Facilitate signal Gliabot 1/neuron 86 billion
Axonal endoneurobot Gliabot Synaptobot

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B/CI Cloudmind 31
B/CI is a Network of Neuronanorobots
 The B/CI is comprised of neuronanorobots, medical
nanorobots designed to operate in the brain
 Medical nanorobots are nanoscale molecular
machines (1 x 10-9 m) that complement native cells
and perform medically-related tasks in the body
 Patrol the body for health monitoring and intervention
 An on-board ecosystem similar to the microbiome
 Standard proposed medical nanorobots
 Respirocytes (artificial red blood cells)
 Clottocytes (artificial platelets)
 Microbivores (artificial phagocytes)
Source: Freitas Jr., Robert A. 2000, 2005, 2012, http://www.imm.org.

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B/CI Cloudmind 32
Size of Neuronanorobots
Human Cell Size Estimate Neuronanorobot Size Estimate
Red blood cell 7,000 nm Basic nanorobot 1,000 nm
Neuron (cell body) 10,000-25,000 nm Axonal
endoneurobot
1,000 nm
Synapse
Pre-synaptic terminal 100-1,000 nm3 Synaptobot 30-300 nm
Synaptic cleft 20 nm Synaptobot 5-10 nm
Post-synaptic terminal 100-1,000 nm3 Synaptobot 30-300 nm
Glial cell (microglia) 15,000-30,000 nm Gliabot 1,000 nm
 Axonal endoneurobot and gliabot could be analogous
in size to other nanorobots, about 1,000 nm
 Synaptobot is much smaller, 30-300 nm if housed in
synaptic terminals, and smaller still if located in the
synaptic cleft, perhaps 5-10 nm (nanorobot part size)

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B/CI Cloudmind 33
Aim of B/CI Neuronanorobot Network
 Map, Monitor, Cure, and Enhance Neural Activity
 Example: neuronanorobots provide directed electrical
stimulus to the brain to dissolve blood clots using ultrasound
B/CI Function Objectives and Tasks
1 Map Connectome mapping of brain to create a wiring diagram of the structural and
functional information of the brain in proper temporal and spatial resolution
2 Monitor Direct monitoring, tracking, and reporting concerning the brain’s 86 billion
neurons and 200 trillion synapses; daily health check, alerts
3 Cure Acute and chronic disease response, restoring lost or damaged functionality (due
to senescence, stroke, or neurodegenerative disease)
4 Enhance Enhance neural activity related to learning, attention, and memory
Source: Marosfoi et al. Shear-Activated Nanoparticle Aggregates Combined with Temporary Endovascular Bypass to Treat Large
Vessel Occlusion. Stroke 46(12), 3507-13, 2015.

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B/CI Cloudmind 34
Neurocurrencies
 Neural cells and neuronanorobots have “neurocurrency”
balances by which they execute transactions
Neurocurrencies ($NC) Neuronanorobot
Category Resource Axonal endoneurobot Synaptobot Gliabot
Electricity Voltage X X
Polarization X
Action Potential X
Resting Potential X
Ion Sodium (Na+) X
Potassium (K+) X
Calcium (Ca2+) X
Chloride (Cl-) X
Neurotransmitter
(Nx)
Glutamate (excitatory) X X
GABA (inhibitory) X X
Fuel Glucose (ATP) X X X
Oxygen (ATP) X X X

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B/CI Cloudmind 35
Representative Neurocurrencies
 Resources used to perform a neural
function by a neural cell or a neuronanorobot
1. Electricity and ions
 Electricity: voltage, polarization, action potential
 Ions (atoms stripped of one electron): Sodium (Na+),
Potassium (K+), Calcium (Ca2+), Chloride (Cl-)
2. Neurotransmitters (200 total)
 90% glutamate (excitatory) and GABA (inhibitory)
 Acetylcholine (increase probability of pre-synaptic
neurotransmitter release), dopamine, norepinephrine,
histamine, serotonin, epinephrine
3. Fuel
 Produce ATP from oxygen and glucose

28 July 2020
B/CI Cloudmind
 Agenda
 The Brain
 Neuronanorobots
 Neurocurrencies
 Conclusion
36
Quantum Computing
3. Application

28 July 2020
B/CI Cloudmind
Bio-blockchain Neuroeconomy
 B/CI realization
 Control software and operating software
 Control software
 Holographic control mechanism between human
controllers and B/CI
 Coordinate between the B/CI neuronanorobot network
with data collected and computed in quantum
mechanical form, and its abstraction for practical use
by human administrators at the macroscale
 Operating software
 Blockchain for the operating software of the B/CI
neuronanorobot network
37

28 July 2020
B/CI Cloudmind
 Bio-blockchain (blockchain deployed in a biological
setting) as the B/CI neuronanorobot network
operating software
 Economic design principles
 Multi-agent goal-directed behavior coordination
 Blockchain transaction-logging system
 Neuronanorobots carry out neurocurrency-based operations
 Top-level Merkle root calls entire underlying data structure
 Security via cryotographic features inherent to blockchains
 Real-time transaction confirmation
 Computational verification (zero-knowledge proof technology)
38

28 July 2020
B/CI Cloudmind
 Transaction-heavy, network-based,
automated smart network technology
 Orchestrate particle-many fleet units
 Seamlessly register an arbitrarily-large number of participants
and possibly execute an arbitrarily-large number of transactions
 Multi-currency environment (neurocurrencies)
 Modular system that can easily scale in B/CI cloudmind
implementation from individuals to groups
 Same transaction-logging and security features are relevant to
group cloudminds for intellectual property tracking, credit
assignment, and privacy protection as for individual cloudminds
39
Image Source: Helmstaedter M, Briggman KL, Denk W. High-accuracy neurite reconstruction for high-throughput neuroanatomy.
Nat Neurosci. 2011 Jul 10;14(8):1081-8
Neurite reconstruction

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B/CI Cloudmind 40
Blockchain Neuroeconomy: Tech Specs
 B/CI transaction system that instantiates particle-
many fleet units (neuronanorobots) and their activity
 86 billion axonal endoneurobots, 86 billion gliabots, 200
trillion synaptobots, and their activity, which may exceed one
transaction per second per unit
 Contemporary transaction system analysis of
transactions-per-second (TPS)
Neuronanorobot Class Number of Neuronanorobots Number of Transactions (total)
Axonal endoneurobot 86 billion 1 per/second or more x 86 billion
Synaptobot 86 billion x 2300 = 200 trillion 1 per/second or more x 200 trillion
Gliabot 86 billion 1 per/second or more x 86 billion
Transaction System Average TPS Peak TPS Year
1 Visa 2,000 24,000 2011
2 Alipay (China) 120,000 175,000 2017
3 Facebook 175,000 N/A 2017
4 World’s largest banks 100,000 N/A 2020

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B/CI Cloudmind 41
Neurocurrencies by Neuronanorobot type
 B/CI applications by traffic type and ledger units
 B/CI applications by traffic type with the relevant
neurocurrency ledger units in which the transactions might
be denominated, tracked, and exchanged
Application Class Application Functionality Traffic Type Ledger Unit
Core BCI
Neuroprosthetics Control Actuation EEG signal Microvolts
Cursor control Communication Actuation EEG signal Microvolts
Cloudmind B/CI
Map Connectome
Functional
mapping
IP, 3D point
cloud
MB, SLAM
Monitor
Data upload,
backup, alerts
Security, privacy
IP: HTTP
POST/GET
MB, SLAs
Cure
Intervention
delivery
Disease cure,
rejuvenation
Electricity, Mcg
Millivolts (mV),
millimoles (mM)
Enhance
Direct neural
transfer
Augmentation
IP: HTTP
POST/GET
MB

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B/CI Cloudmind 42
Neuronanorobot Communication
 Neuronanorobot communications
 Cloud, B/CI network, neural cells, other nanorobots
Neuronanorobot Communication Traffic Type Activity
1 To the cloud (two-way) IP HTTP POST/GET
2 To other neuronanorobots IP & Neurocurrency
Messaging, resource balancing,
group coordination
3 To neural cells Neurocurrency
Neurotransmitter delivery,
polarization, voltage-gating
Neuronanorobot Traffic Type Neurocurrency Ledger Unit
Axonal endoneurobot Electricity Electricity, Ions Millivolts (mV)
Synaptobot Neurotransmitter Neurotransmitter Millimoles (mM)
Gliabot Neurotransmitter Neurotransmitter Millimoles (mM)

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B/CI Cloudmind 43
Biomimetic design principles
Neural Lightning Network
 Blockchain overlays: Lightning Network
 Parties pre-contract to automatically rebalance accounts
 Dynaminc smart routing, traffic shaping, security
 Glial cell neurotransmitter recycling operation
 Analogous to payment channel rebalancing in blockchains
 B/CI neuronanorobt payment channel system
 Neuronanorobots contract with each other and the B/CI
network per standard opertating smart contracts
 Blockchain-based smart contracts orchestrate daily operations
 Smart contracts enact dynamic resource rebalancing
 Automated neurocurrency replenishment mechanism
 Secure audit-log, tracking, budgeting system

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B/CI Cloudmind 44
Biomimetic design principles
Multi-agent Coordination Application
 Harness the group coordination feature
built into neural signaling
 B/CI network could similarly encourage
and reward multi-agent behavior
 Example: distribute serotonin balances
could be distributed to neuronanorobots
 Group goal: improve synaptic release of
serotonin in signaling
 Macroscale result: reduce depression
 Practical benefit: decrease side effects of
prescription drugs with the more granular
native activation of neurotransmitters
Nano-CT scanner
(50-500 nm resolution)
Image Source: Freitas, R.A. Jr. (2016). The Alzheimer Protocols: A Nanorobotic Cure for Alzheimer’s Disease and Related
Neurodegenerative Conditions. IMM Report No. 48, June 2016. http://www.imm.org/Reports/rep048.pdf.

28 July 2020
B/CI Cloudmind
 Agenda
 The Brain
 Neuronanorobots
 Neurocurrencies
 Conclusion
45
Quantum Computing
3. Application

28 July 2020
B/CI Cloudmind 46
Measuring B/CI Success
 B/CI aim: productivity, well-being, and enjoyment
 Maslow’s hierarchy of needs
 Maslow 1 food, water, warmth, sleep, sex, and security
 Maslow 2 belonging, acknowledgement, and love
 Maslow 3 achievement, creativity, realization of potential
 “Beyond-Maslow” advance
 Scientific advance, new forms of learning, the cloudmind itself
as a platform for intelligence development
Maslow Tiers Objective B/CI Measure
Maslow 1 Physiological survival Energy, glucose, oxygen, ATP
Maslow 2 Psychological well-being Neurotransmitter balances
Maslow 3 Self-actualization Ideas, neurotransmitters, energy
Beyond-Maslow New levels of achievement Ideas, new cloudmind design

28 July 2020
B/CI Cloudmind 47
Peak Performance Cloudminds
 Instantiating well-formed groups
 Forming-storming-norming-performing (Tuckman, 1965)
 Group individuation (Simondon, 2005)
 Transparent decision making (Kashtan, 2014)
 Overcoming barriers to large-group collaboration
 The three “C”s
 Credit assignment: track seamlessly with blockchains
 Coordination: multi-thread human capacity into a coherent
whole with “mission control” type participation of experts
 Communication: reduce misunderstanding to an
interoperability issue in the digital thought environment

28 July 2020
B/CI Cloudmind 48
Thought Interoperability
 Digital environment of
B/CI cloudminds
 Log activity for credit-assignment and privacy protection
 Enforce format compatibility
 No transaction can enter the B/CI system without
being in a compliant format
 Implication: ideas brought into greater alignment from the
beginning based on the way that they are presented
 Formatting standards produce interoperability
 Reduce the possibility of misunderstanding
 Improve the ability to collaborate ideas

28 July 2020
B/CI Cloudmind 49
Merkle Root Data Structures
 A Merkle root is a top-level hash (64-character code)
that calls an entire underlying data structure
 Example: One top-level Merkle root calls the entire
Bitcoin blockchain data structure of all transactions
 636,000 transaction blocks (each with a few thousand
transactions) since inception (Jan 2009) as of Jun 2020
 Implication: one top-level Merkle root can call entire
data corpora
 All Github code, all Pubmed publications
 All human knowledge (digitally encoded)
 An entire brain or cloudmind (brain of brains)
Source: btc.com (Bitcoin transaction blocks)

28 July 2020
B/CI Cloudmind 50
IPLD (InterPlanetary hash-Linked Data structure)
 IPLD: data standard for digital corpora
 An internet-wide file system in order to access
compatibly-addressed content
 The data standard calls content in any internet-
based data structure (e.g. Github, Pubmed)
 URL links are hashed for data security and to
provide the interoperable format
 Other Protocol Labs projects
 IPFS (InterPlanetary File System)
 Zero-knowledge proofs of time and space
 Proof of providing storage resources
 A certain amount of space for a certain amount of time
 Proofs denominated in computational complexity
Sources: Protocol Labs; Bear, G. (1985). Eon; Wright, J.C. (2012). The Hermetic Millenia.
Call the entirety of
the world’s
knowledge with one
Merkle root; a “data
pillar” (Bear, 1985)
with “library smarts,
datasphere smarts”
(Wright, 2012)

28 July 2020
B/CI Cloudmind 51
IPLD for the Brain
Source: Swan, M. (2015). Blockchain thinking: The brain as a DAC (decentralized autonomous corporation). Technology and Society
Magazine 34(4):41-52
 A brain is a Merkle forest of ideas
 A group of Merkle trees, each calling an
arbitrarily-large thought trajectory
 Brain DAC II: IPLD for the Brain
 Thought content compatibility through
multi-hash protocols and Merkle roots
 Blockchain overlay realizes B/CI
cloudminds through secure thought
interoperability between minds
 IPLD is an overlay for the web; IPLD for
the Brain is an overlay for cloudminds
 Brain DAC I
 Instantiate thinking in a blockchain
IPLD for the Brain

28 July 2020
B/CI Cloudmind
 Agenda
 The Brain
 Neuronanorobots
 Neurocurrencies
 Conclusion
52
Quantum Computing
3. Application

28 July 2020
B/CI Cloudmind 53
Risks and Limitations
 “No neural dust without neural trust”
 B/CI platform non-starter if cannot develop sufficient user
trust in the platform; phased migration with roll-back
 Hardware trust: nature’s quantum security principles
 Software trust: blockchain cryptographic features
 B/CI is a speculative technology without immediate
practical development possibilities
 Technical: neuron firing rate 4 x second x 86 billion neurons
 Feasible: unpalatability of implanted nanorobots in brain
 Proposals are ill-founded, infeasible, or inaccurate
 Arrival sequence of advanced technologies
 Non-invasive digital brain copies become possible first

28 July 2020
B/CI Cloudmind 54
Conclusion
 The B/CI is a technical platform for the brain
 Aim: enact more meaningful, rewarding, fulfilling lives
 Quantum computing
 Direct mapping from real-life to computational representation
 Nature’s built-in quantum mechanical security features
 Key application: neural networks and machine learning
 Holographic control theory (AdS/CFT correspondence)
 Universal control lever between macroscale-quantum domains
 Gauge theory (gauge-gravity duality) subatomic processing
 IPLD for the Brain Bio-blockchain
 Top-level Merkle root calls entire underlying data structure
 Computational verification (zero-knowledge proof technology)

28 July 2020
B/CI Cloudmind 55
B/CIs (brain/cloud interface technologies) are a
next-generation technology needed
1. (short-term) to cope with the modern reality of
science and technology outpacing biology
2. (long-term) to enable new physical and mental
resource coordination capabilities to evolve
towards a Kardashev-plus society (marshalling
tangible and intangible resources on a beyond-
planetary basis)
Thesis

28 July 2020
B/CI Cloudmind
Theoretical Model of Quantum Reality
 Quantum reality is information-theoretic and computable
 Lecture 1: Quantum Computing basics (hardware)
 Lecture 2: Advanced concepts (control software between
macroscale reality and quantum microstates)
 Lecture 3: Application (B/CI neuronanorobot network)
56

Mountain View CA, July 28, 2020
Slides: http://slideshare.net/LaBlogga
Quantum Computing
Lecture 3: Application
Melanie Swan
Thank you!
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Quantum Computing Lecture 3: Application

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Quantum Computing Lecture 3: Application