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.

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

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)

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

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

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.

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

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?

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