Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Quantum Computing Lecture 3: Application
1. 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)
2. 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
3. 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
4. 28 July 2020
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
5. 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
6. 28 July 2020
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
7. 28 July 2020
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.
8. 28 July 2020
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.
9. 28 July 2020
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
10. 28 July 2020
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
11. 28 July 2020
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
12. 28 July 2020
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.
13. 28 July 2020
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
12
Quantum Computing
3. Application
14. 28 July 2020
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.
15. 28 July 2020
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
16. 28 July 2020
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
17. 28 July 2020
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
18. 28 July 2020
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
17
Quantum Computing
3. Application
19. 28 July 2020
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.
20. 28 July 2020
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
21. 28 July 2020
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.
22. 28 July 2020
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
23. 28 July 2020
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)
24. 28 July 2020
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
23
Quantum Computing
3. Application
25. 28 July 2020
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
26. 28 July 2020
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
27. 28 July 2020
B/CI Cloudmind
Microbivores (artificial immune cells)
26
Microbivore captures and engulfs a microbe
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)
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
28. 28 July 2020
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
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. (images by E-spaces)
Chromatic replacement
Chromallocyte docking
29. 28 July 2020
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
28
Quantum Computing
3. Application
30. 28 July 2020
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
31. 28 July 2020
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
32. 28 July 2020
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.
33. 28 July 2020
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)
34. 28 July 2020
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.
35. 28 July 2020
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
36. 28 July 2020
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
37. 28 July 2020
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
36
Quantum Computing
3. Application
38. 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
39. 28 July 2020
B/CI Cloudmind
Bio-blockchain Neuroeconomy
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
IPLD for the Brain
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
40. 28 July 2020
B/CI Cloudmind
Bio-blockchain Neuroeconomy
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
41. 28 July 2020
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
42. 28 July 2020
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
43. 28 July 2020
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)
44. 28 July 2020
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
45. 28 July 2020
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.
46. 28 July 2020
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
45
Quantum Computing
3. Application
47. 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
48. 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
IPLD for the Brain
49. 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
50. 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)
51. 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)
52. 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
53. 28 July 2020
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
52
Quantum Computing
3. Application
54. 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
55. 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)
56. 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
57. 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
58. Mountain View CA, July 28, 2020
Slides: http://slideshare.net/LaBlogga
Quantum Computing
Lecture 3: Application
Melanie Swan
Thank you!
Questions?