Blockchain Tethered AI

Spis treści ebooka

• Preface
  • Why Does AI Need to Be Tethered?
  • What You Will Learn
  • Why We Wrote This Book
  • A Note to Future Generations
  • Summary
  • Conventions Used in This Book
  • Using Code Examples
  • OReilly Online Learning
  • How to Contact Us
  • Acknowledgements
• 1. Why Build a Blockchain Truth Machine for AI?
  • Dissecting AIs Trust Deficit
  • Machine Learning Concerns
    • Opaque Box Algorithms
    • Genetic Algorithms
    • Data Quality, Outliers, and Edge Cases
    • Supervised Versus Unsupervised ML
    • Reinforcement Learning and Deep Learning
    • Program Synthesis
      • Auto-complete
      • Smart Compose
      • Codex
      • Copilot
      • Microsoft AI helper for Minecraft
      • Controlling program synthesis
    • Superintelligent Agents
    • Technological Singularity
  • Attacks and Failures
    • Model/Data Drift
    • Adversarial Data Attacks
    • Risk and Liability
  • Blockchain as an AI Tether
    • Enterprise Blockchain
    • Distributed, Linked Blocks
    • Trust and Transparency
    • Defining Your Use Case
      • Touchpoints
      • Participants
      • Assets
      • Transactions
      • Smart contracts and business logic
    • Audit Trail
    • Local Memory Bank
    • Shared Memory Bank
    • Four Controls
    • Case Study: Oracle AIoT and Blockchain
  • Whats Next?
• 2. Blockchain Controls for AI
  • Four Blockchain Controls
  • Blockchain Control 1: Pre-establishing Identity and Workflow Criteria for People and Systems
    • Establishing Identity
      • Digital certificates
      • Public and private keys
      • Certificate authorities (CAs)
      • Certificate revocation lists (CRLs)
      • Membership Service Provider (MSP)
    • Predetermining Workflow Among Participants
      • ML pipeline and MLOps
      • Data cleaning and bias reduction
  • Blockchain Control 2: Distributing Tamper-Evident Verification
    • Using Crypto Anchors to Verify Data Sets, Models, and Pipelines
    • Using Blockchain to Detect Common AI Hacks
    • Understanding Federated Learning and Blockchain
    • Understanding Model Marketplaces
  • Blockchain Control 3: Governing, Instructing, and Inhibiting Intelligent Agents
    • Establishing a Governance Group
    • Implementing On-Chain Governance
    • Developing Compliant Intelligent Agents
  • Blockchain Control 4: Showing Authenticity Through User-Viewable Provenance
    • Deciding Whether to Trust AI
  • Summary
• 3. User Interfaces
  • Design Thinking
    • Web Interfaces
    • Blockchain Tethered AI User Interfaces
    • BTA User Mockups
      • Super admin
      • Organization admin
      • AI engineer
      • MLOps engineer
      • Stakeholders
    • Functionality
    • Traceability and Transparency
      • AI supply chain
      • Hyperledger Explorer
    • Smartphone and Tablet Apps
    • Email and Text Notifications
    • Spreadsheets
  • Third-Party Systems
    • Working with APIs
    • Integrated Hardware
    • Third-Party Services and Tools
  • System Security
    • AI Security
    • Database Security
    • Blockchain Security
    • Additional Security
  • Summary
• 4. Planning Your BTA
  • BTA Architecture
  • Sample Model
    • AI Factsheet: Traffic Signs Detection Model
    • How the Model Works
  • Tethering the Model
  • Subscribing
  • Controlling Access
    • Organization Units
    • Staffings
    • Users
      • Super admin
      • Organization admin
      • AI engineer
      • MLOps engineer
      • Stakeholder
  • Analyzing the Use Case
    • Participants
    • Assets
    • Transactions
    • Smart Contracts
    • Audit Trail
  • Summary
• 5. Running Your Model
  • Exercise: Oracle Cloud Setup
    • Creating a Cloud Provider Account
    • Creating a Compartment
    • Creating a Bucket
    • Creating a Pre-authenticated Request
    • Creating Oracle Groups
    • Creating IDCS Groups
    • Mapping Oracle Groups
    • Creating a Policy
    • Generating a Secret Key
  • Exercise: Building and Training a Model
    • Exploring the Model Repository
    • Installing Python and PyTorch
    • Starting the Notebook
    • Configuring Boto3
    • Running Your Notebook
    • Checking the Bucket
  • Optimizing Hyperparameters
    • Learning Rate for Training a Neural Network
    • Number of Training Epochs Used
    • Size of the Training Batches
    • Size of the Hidden Layers
  • Understanding Metrics
    • Accuracy
    • Loss
    • Precision
    • Recall
    • F1 Score
  • Summary
• 6. Instantiating Your Blockchain
  • Exercise: Setting Up Hyperledger Fabric
    • Installing Node.js, npm, and NestJS
    • Understanding Hyperledger Fabric 2.0 Required Nodes
    • Installing, Configuring, and Launching the Blockchain
      • Installing Hyperledger Fabric binaries
      • Generating certificate files
      • Generating the genesis block for the orderer peer
      • Generating channel configuration files
      • Generating anchor peer configuration files
      • Running the blockchain nodes
      • Starting Docker
  • Creating and Joining Channels
    • Creating Channels
    • Joining Channels
    • Configuring Anchor Peers
  • Using Chaincodes
    • Understanding Response Struct
    • Using GetTxDateTime
    • Project (project)
    • Model Version (model-version)
    • Model Review (model-review)
      • Using modelReview struct
      • Using GetModelReviewHistory
      • Using ModelReviewHistory struct
      • Using storeModelReview
    • Model Artifact (model-artifact)
    • Model Experiment (model-experiment)
  • Setting Up the Blockchain Connector
  • Creating Multiple Blockchain Connectors
  • Setting Up the Oracle Connector
    • Configuring Your env File with Your OCI Variables
      • OBC_ADMIN_HOST
      • AUTHORIZATION_TOKEN
      • OBC_ADMIN_USERNAME and OBC_ADMIN_PASSWORD
      • OBC_ADMIN_SCOPE
      • REDIS_HOST and REDIS_PORT
      • APP_PORT
      • API_AUTHORIZATION_TOKEN
    • Starting the Oracle Connector
  • More About Integrating Blockchain and the Application Layer
    • Blockchain Connector
    • query
    • OC User Service
    • OC Group
  • Summary
• 7. Preparing Your BTA
  • Exercise: Installing and Launching Your BTA
    • Installing the BTA Backend
    • Understanding Your BTA Backends env File
    • Understanding Your environment.ts File
    • Launching the BTA Frontend
  • Exercise: Creating Users and Permissions
    • Using MailCatcher
    • Configuring the Super Admin
    • Creating a New Subscription Account in Your BTA
    • Configuring Organization Admins Node
    • Configuring Organization Admins Channel
    • Verifying the Subscription
    • Activating Your Organization Admin
    • Configuring Access for Your AI Team
      • Configuring user nodes
      • Configuring a channel for users
      • Creating an organization unit
      • Creating staffings
      • Adding a bucket URL
      • Creating users
  • Summary
• 8. Using Your BTA
  • Exercise: Recording Critical AI Touchpoints to Blockchain
    • Adding a New Project
    • Adding a New Version
    • Understanding How Training and Testing Data Use Blockchain
    • Understanding How Models and Algorithms Use Blockchain
    • Understanding How Inputs and Outputs Use Blockchain
    • Understanding How Performance Metrics Use Blockchain
    • Understanding How New Model Versions Use Blockchain
    • Understanding How the Uploads Work
    • Reviewing and Approving the Model
    • Adding AIs Purpose and Intended Domain
  • Exercise: Auditing Your BTA
    • Tracking Your Models Training and Test Data Sets
    • Tracing Your Inputs and Outputs
    • Verifying Performance Metrics
    • Tracing Identity of People and AI Systems
    • Tracking and Tracing Model Development
    • Identifying Tampering
    • Reversing Your Blockchain Tethered Model
    • Checking the Training Data Sets
    • Checking the Algorithms
    • Retraining the Model
  • Summary
• Index

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