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How AI benefits from Blockchain and Game Theory with Scalable Censorship-resistant Consensus

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A talk given at North Star AI conference 2018 by Dr Maxim Orlovsky uncovers technical details of the possible intersections between AI and blockchain technologies. In particular – how blockchain and our Pandora Boxchain project can help solve Byzantine fault tolerance problem in autonomous multi-agent environments and decrease strategic risks coming from the emerging artificial intelligence

How AI benefits from Blockchain and Game Theory with Scalable Censorship-resistant Consensus

  1. 1. How AI benefits from Blockchain and Game Theory with 
 Scalable Censorship-resistant Consensus dr. Maxim Orlovsky & Pandora Foundation Team
  2. 2. Multi-agent systems • AI is not singular – it is multi-agent:
 autonomous vehicles, IoT, mobiles, etc. • At some point in future(?)
 agents will become interacting. • Multiple V2V, V2E, E2E protocols will evolve,
 which will face byzantine faults
 and multiple security issues
  3. 3. Imagefromsitewww.artlebedev.ru
  4. 4. Distributed Systems &
 Byzantine Fault Tolerance • The Byzantine General’s Problem was first proposed by Lamport,
 Shostak, and Pease in 1982. • A problem of making a reliable system from unreliable parts
 (Ethan Buchman, Cosmos Network) • From 1982 to 1999, no one had invented a solution for the problem • Non-blockchain based solutions (Paxos, Raft, DLS, BPFT) had limited
 fault-tolerance and were used in trusted setups (space communications etc). • Bitcoin opened a way to enhance byzantine tolerance due to economical stimuli and game theory. It gave rise to other blockchain technologies.
  5. 5. Blockchain:
 Distributed Ledger Technology (DLT) • Trusted Persistent Data Records • Inside Trustless Environments • Without Central Governance • Secured By Economic Incentives
  6. 6. Blockchain Key Parameters • Security: (sometimes called “immutability“ or “persistence“):
 past history does not change. 
 Leads to audibility and accountability • Liveness: availability to post new transactions
 Liveness intrinsically means censorship-resistance • Blockchain-based distributed systems achieve these qualities by following the same consensus protocol • Non-faulty behavior is supported by 
 economic incentives (like mining rewards)
  7. 7. Blockchain • Replicative state machine 
 (type of distributed database) + asymmetric cryptography (accountability) + ordered immutable set
 of historical state changes (audibility)
  8. 8. Consensus Protocol • Required for public blockchains 
 (”private/federated blockchain” is an oxymoron) • Adds rules by which distributed parts of replicative state machine reaches consensus on the current state • Achieves that by adding economic incentives for participants following the protocol utilizing specially-designed game theory settings (cryptocurrency)
  9. 9. Blockchain + Consensus Results: • Solution to byzantine generals problems
 (no other way to solve it) • i.e. appearance of trust in trustless environments (due to accountability and audibility)
  10. 10. Technology • Distributed database (ledger) • Distributed computations (state changes), 
 Turing-complete OR incomplete • Peer-to-peer mesh network • Cryptographically secured Economics • Multiagent economy • Game theory • Free open market • Non-state decentralized economies linked to particular types of resources or businesses BLOCKCHAIN
  11. 11. Block data Block = Block { header :: BlockHeader , blockSize :: Int , transactionCount :: Int , transactions :: [Transaction] } data BlockHeader = BlockHeader { version :: Int
 , prevBlockHeader :: Hash32 , merkleRoot :: Hash32 , timestamp :: Int32 , ... } Hash of Previous Block Header Merkle Root Block 1 Transactions Block 1 Header Hash of Previous Block Header Merkle Root Block 1 Transactions Block 2 Header
  12. 12. Smart Contracts • Proposed by Nick Szabo much before blockchain • Can automate multi-agent AI-based systems • Used since bitcoin in most of blockchains to automate state transition changes according to some rules • Turing-incomplete & Turing-complete
  13. 13. Turing-incomplete • Bitcoin (multisigs, lightning, sidechains) and bitcoin clones • Limited functionality
 (but robust and easily formally verified)
  14. 14. Bitcoin Smart Contract <expiry time> OP_CHECKLOCKTIMEVERIFY OP_DROP OP_DUP OP_HASH160 <pubKeyHash> OP_EQUALVERIFY OP_CHECKSIG <sig> <pubKey>
  15. 15. Turing-complete • Ethereum & Ethereum Classic, Rootstock 
 (all EVM-based) • Highly-vulnerable • ”Single-threaded”, unscalable:
 all computations are repeated by each node
  16. 16. EVM Smart Contract on Solidity library StateMachineLib { struct StateMachine { bool initialized; uint8 currentState; mapping(uint8 => uint8[]) transitionTable; } function transitionToState(StateMachine storage _machine, uint8 _newState) internal { // Checking if the state transition is allowed bool transitionAllowed = false; uint8[] storage allowedStates = _machine.transitionTable[uint8(_machine.currentState)]; for (uint no = 0; no < allowedStates.length; no++) { if (allowedStates[no] == _newState) { transitionAllowed = true; } } require(transitionAllowed == true); } ...
  17. 17. Problems Why blockchains didn’t conquer the world
  18. 18. Consensus How to define who has the right to sign
 a new block of state changes (transactions)? Randomness • Physical process:
 PoW – energy-consuming • On-chain randomness:
 early PoS – predictable • Off-chain randomness:
 PoS with oracles – centralised Agreement • BFT-algorithms (since 1980):
 PoS – vulnerable • Delegation/voting:
 dPoS – centralised • Most have problems with finality (probabilistic at most)
  19. 19. Smart Contracts • ‘Single-threaded’ global computing 
 (scalability) • Consensus depends on contract correctness • Value depends on contract correctness • Rich contracts can’t be truly formally verified
  20. 20. Non-solutions:
 objectives are substituted by means • Blockchain is neither self-aim nor any kind of distributed technology • “Blockchain” without cryptocurrency:
 no economical incentives layer ->
 no protection from not following consensus • Private/Federative “blockchain”:
 just a distributed DB with unnecessary computational burden.
 no true liveness and security • Such “blockchains” are just a word
 for PR/marketing/funding purposes
  21. 21. Prometheus: Hybrid Consensus for AI • Smart contracts extended to generic computing (suitable for AI models) that can run in parallel in trustless decentralised network • Computing results are proved by specially-designed PoW consensus • Value transferred by independent PoS-consensus • Randomness is created by computing actual models on actual data (decentralised oracle)
  22. 22. Proof of Reputation (using reputation) Validators Proof of Computing Work (producing reputation) Full Node Workers Verifiers Arbiters Reputation level increase Computing work /
 reward ratio increase
  23. 23. Prometheus Layers Proof of Cognitive Work: 
 P2P state channels
 with Nash equilibrium achieved only for 
 a correct AI model training/inference 
 Poseidon Proof of Reputation Blockchain: 
 State Machine/Settlement Layer with 
 three-tier scalability • blockchain – Hyperion • sidechains – Talassa • state channels – Tethys
  24. 24. Poseidon • Tasks (AI model training/inference) is split in batches. Each batch computed in parallel by some Workers. • Each task & batch is verified by three Verifier (using testing set for training or repeating 10% of random samples for inference). • Both Workers & Verifiers have stake, 
 Verifiers additionally have reputation. • If Verifiers confirm computing then task is complete 
 Worker and Verifiers get paid + Workers get mining reward https://github.com/pandoraboxchain/pyrrha-consensus
  25. 25. Poseidon Arbitration • If result is not confirmed then Worker either
 can be penaltised with its stake OR it can apply for Arbitration • There are two-tier Arbitration procedure which provably leads to correct result. 
 Nodes found faulty are penaltised with stake/reputation and correct nodes are rewarded with reputation & paid. • This leads to Nash equilibrium without repeating all computations on each node of the network.
  26. 26. Hyperion: replicative state machine for settlements of Poseidon computing • Randomness is taken from PoCW • No Turing-complete computing • Provable finality & security • Liveness and censorship-resistance • Three-tier scalability 
 (blockchain, sidechains, state channels)
  27. 27. Imagefromsitewww.artlebedev.ru
  28. 28. MALICIOUS AGENT
 DETECTION IN AUTONOMOUS 
 AI-DOMINATED SYSTEMS
  29. 29. Other Key Properties Unique: • Censorship resistance • Zero governance • Scalability • Hybrid consensus with PoS/PoW model Common: • Open markets for models, big data and computing power • Economic incentives for participants • Zero-knowledge
  30. 30. What Pandora Boxchain 
 will also give AI? • Privacy & zero knowledge:
 fixing “loss of privacy” problem • Free, open markets (models, big data, computing power): enabling faster progress and fair rewards • Mitigating strategic risks from AI
 with game theory, economics & byzantine fault tolerance –instead of “ethics” which would not work
  31. 31. The Solution Instead of: AI regulations Big data regulations AI “Kill switch” “Azimov laws” Use: Economic incentives Zero knowledge Game theory Audibility & accountability Blockchain
  32. 32. Maxim Orlovsky PhD, MD orlovsky@pandora.foundation /pandoraboxchain github.com/pandoraboxchain Special thanks to Dmitry Litvinov for the presentation design & Pandora Foundation Team www.pandoraboxchain.ai
  33. 33. … one more thing
  34. 34. A bit of futurism
  35. 35. AI Today: Limited Progress Engineering over science –
 lack of new scientific paradigms: • Practical progress comes from computational resources and big data • CNN, Deep learning, Reinforcement learning, AGN etc represent engineering innovations
  36. 36. New Directions Engineering: • Multi-agent systems • Distributed/ decentralised systems • New biologically- inspired cognitive architectures Science: • Game theory • Byzantine fault tolerance • Complexity science
  37. 37. ⊂ Blockchain Engineering: • Multi-agent systems • Distributed/ decentralised systems • New biologically- inspired cognitive architectures Science: • Game theory • Byzantine fault tolerance • Complexity science
  38. 38. happens when
 selection acts
 on a diverging population while modern neuronets are singular Evolution
  39. 39. •species exchanges genes via viruses •cells emit chemical and electric signals •animals communicate via mimics and emotions •humans — via language Information transfer: What about #AI?
  40. 40. requires
 Consensus
 Persistence
 Liveness Information transfer:
  41. 41. •DNA translation will be the same for bacteria as for a human being •written text is understood in the same way by all native speakers Consensus: each agent gets the same sense of a signal as others
  42. 42. •DNA in chromosomes do not change during the live of the most cells •Egyptian hieroglyphs could still be understood by researchers Persistence: the sense of the signal does not diminish with time
  43. 43. Is perfect both for consensus and persistence rendering multi-agent #AI
 as an evolving self-organized system BLOCKCHAIN:
  • SloanWang

    Jul. 15, 2018
  • pandoraboxchain

    Jul. 12, 2018
  • xwrockbay

    Apr. 26, 2018
  • azzot

    Apr. 4, 2018

A talk given at North Star AI conference 2018 by Dr Maxim Orlovsky uncovers technical details of the possible intersections between AI and blockchain technologies. In particular – how blockchain and our Pandora Boxchain project can help solve Byzantine fault tolerance problem in autonomous multi-agent environments and decrease strategic risks coming from the emerging artificial intelligence

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