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PUBLISHER: Communications Industry Researchers (CIR) | PRODUCT CODE: 1815977

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PUBLISHER: Communications Industry Researchers (CIR) | PRODUCT CODE: 1815977

CIR Guide to New Technologies for the AI Data Center

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This report provides the competitive intelligence on AI data center technology that you cannot find anywhere else. Professionals in business, government, academia and in the investment community will use this report to improve product planning and marketing. We believe that this 100-page report will be the go-to resource for everyone seeking the CIR's latest opinion and analysis of the AI data center sector sector.

Table of Contents

Chapter 1: Understanding Data Centers

  • 1.1. An Introduction to Data Centers
  • 1.2. About CIR
  • 1.3. An AI Market Overview
  • 1.4. What is an AI Data Center?
  • WHAT TO DO NOW

Chapter 2: Servers and Processors

  • 2.1. Introduction
  • 2.2. What Is an AI Server?
    • 2.2.1. Rethinking Servers
  • 2.3. AI Processors
    • 2.3.1. AI Chip Makers
  • WHAT TO DO NOW

Chapter 3: Networks and Interconnects In AI Data Centers

  • 3.1. Introduction
  • 3.2. Traffic Patterns in AI Data Centers
    • 3.2.1. Networking in the Data Center: Resilient, Reliable and Secure
  • 3.3. Ultra Ethernet vs. CPO: The Future of AI Data Center Interconnects
    • 3.3.1. CPO in the AI Data Center: The Latest Announcements
    • 3.3.2. Alternatives to CPO
  • 3.4. Dawn of the Quantum Data Center
  • 3.5. AI, the Internet and Other Networks
  • WHAT TO DO NOW

Chapter 4: Data Storage In AI Data Centers

  • 4.1. Introduction
  • 4.2. AI and Data Lakes
  • 4.3. The Role of Object Storage
  • 4.4. NVMe SSDs
  • 4.5. Hierarchical Storage Management (HSM)
  • 4.6. Storage for Training
  • WHAT TO DO NOW

Chapter 5: Power and Cooling for AI Data Centers

  • 5.1. Future Power for the AI Data Center
  • 5.2. The Monster is Coming and What to do About It
  • 5.3. The Future of Cooling AI Data Centers
    • 5.3.1. Evolution of Liquid Cooling
    • 5.3.2. Liquid Immersion Cooling
    • 5.3.3. Microconvective Cooling
    • 5.3.4. Direct-to-Chip- Cooling
    • 5.3.5. Microchannel Cooling
    • 5.3.6. Oil Cooling
  • WHAT TO DO NOW

Chapter 6: Policy Considerations

  • 6.1. United States
    • 6.1.1. The Biden Executive Order
  • 6.2. Trump and AI
  • 6.3. Safety and Security in AI
    • 6.3.1. The Threat from Emergent Intelligence
  • 6.4. AI Regulation in Other Countries
  • ABOUT THE AUTHOR

List of Exhibits

  • Exhibit 1-1: AI Data Centers Built by Year: 2025 to 2034
  • Exhibit 1-2: Types of AI Data Centers in 2025
  • Exhibit 1-3: Selected Sources of AI Product/Technology Innovation
  • Exhibit 1-4: Worldwide AI Data Center Markets
  • Exhibit 1-5: Key Characteristics of AI Data Centers
  • Exhibit 2-1: AI Chip Types
  • Exhibit 2-2: AI Chip Players (Alphabetical Order)
  • Exhibit 3-1: Quantum Computer Companies with Data Center Machines
  • Exhibit 3-2: Opportunities for AI in the Internet/Web Networks
  • Exhibit 5-1: Power Solutions Proposed for AI Data Centers: What to Expect 2026

Table of Contents

Chapter 1: Understanding Data Centers

  • 1.1. An Introduction to Data Centers
  • 1.2. About CIR
  • 1.3. An AI Market Overview
  • 1.4. What is an AI Data Center?
  • WHAT TO DO NOW

Chapter 2: Servers and Processors

  • 2.1. Introduction
  • 2.2. What Is an AI Server?
    • 2.2.1. Rethinking Servers
  • 2.3. AI Processors
    • 2.3.1. AI Chip Makers
  • WHAT TO DO NOW

Chapter 3: Networks and Interconnects In AI Data Centers

  • 3.1. Introduction
  • 3.2. Traffic Patterns in AI Data Centers
    • 3.2.1. Networking in the Data Center: Resilient, Reliable and Secure
  • 3.3. Ultra Ethernet vs. CPO: The Future of AI Data Center Interconnects
    • 3.3.1. CPO in the AI Data Center: The Latest Announcements
    • 3.3.2. Alternatives to CPO
  • 3.4. Dawn of the Quantum Data Center
  • 3.5. AI, the Internet and Other Networks
  • WHAT TO DO NOW

Chapter 4: Data Storage In AI Data Centers

  • 4.1. Introduction
  • 4.2. AI and Data Lakes
  • 4.3. The Role of Object Storage
  • 4.4. NVMe SSDs
  • 4.5. Hierarchical Storage Management (HSM)
  • 4.6. Storage for Training
  • WHAT TO DO NOW

Chapter 5: Power and Cooling for AI Data Centers

  • 5.1. Future Power for the AI Data Center
  • 5.2. The Monster is Coming and What to do About It
  • 5.3. The Future of Cooling AI Data Centers
    • 5.3.1. Evolution of Liquid Cooling
    • 5.3.2. Liquid Immersion Cooling
    • 5.3.3. Microconvective Cooling
    • 5.3.4. Direct-to-Chip- Cooling
    • 5.3.5. Microchannel Cooling
    • 5.3.6. Oil Cooling
  • WHAT TO DO NOW

Chapter 6: Policy Considerations

  • 6.1. United States
    • 6.1.1. The Biden Executive Order
  • 6.2. Trump and AI
  • 6.3. Safety and Security in AI
    • 6.3.1. The Threat from Emergent Intelligence
  • 6.4. AI Regulation in Other Countries
  • ABOUT THE AUTHOR

List of Exhibits

  • Exhibit 1-1: AI Data Centers Built by Year: 2025 to 2034
  • Exhibit 1-2: Types of AI Data Centers in 2025
  • Exhibit 1-3: Selected Sources of AI Product/Technology Innovation
  • Exhibit 1-4: Worldwide AI Data Center Markets
  • Exhibit 1-5: Key Characteristics of AI Data Centers
  • Exhibit 2-1: AI Chip Types
  • Exhibit 2-2: AI Chip Players (Alphabetical Order)
  • Exhibit 3-1: Quantum Computer Companies with Data Center Machines
  • Exhibit 3-2: Opportunities for AI in the Internet/Web Networks
  • Exhibit 5-1: Power Solutions Proposed for AI Data Centers: What to Expect 2026
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Jeroen Van Heghe

Manager - EMEA

+32-2-535-7543

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Christine Sirois

Manager - Americas

+1-860-674-8796

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