Blockchain Tethered AI - Helion

ebook

Autor: Karen Kilroy, Lynn Riley, Deepak Bhatta
ISBN: 9781098130510
stron: 306, Format: ebook
Data wydania: 2023-02-13
Księgarnia: Helion

Cena książki: 271,15 zł (poprzednio: 319,00 zł)
Oszczędzasz: 15% (-47,85 zł)

Osoby, które kupiły tę książkę, wybierały także »

Remove your doubts about AI and explore how this technology can be future-proofed using blockchain's smart contracts and tamper-evident ledgers. With this practical book, system architects, software engineers, and systems solution specialists will learn how enterprise blockchain provides permanent provenance of AI, removes the mystery, and allows you to validate AI before it's ever used.

Authors Karen Kilroy, Lynn Riley, and Deepak Bhatta explain that AI's ability to change itself through program synthesis could take the technology beyond human control. With this book, you'll learn an efficient way to solve this problem by building simple blockchain controls for verifying, tracking, tracing, auditing, and even reversing AI. Blockchain tethered AI interweaves the MLOps process with blockchain so that an MLOps system requires blockchain to function, which in turn tethers AI. This guide shows you how.

You will:

Learn how to create and power AI marketplaces with blockchain
Understand why and how to implement on-chain AI governance
Control AI by learning methods to tether it to blockchain networks
Use blockchain crypto anchors to detect common AI hacks
Learn methods for reversing tethered AI

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Spis treści

Blockchain Tethered AI eBook -- spis treści

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