人工智慧和機器學習：雲端人工智慧

本報告調查了雲端環境中人工智慧（AI）和機器學習的趨勢，並提供了有關雲端環境中人工智慧晶片組的市場規模（出貨量和收入）、區域、架構、工作負載和人工智慧框架的資訊。

實際好處：

• 可以了解未來 10年雲端環境中 AI 晶片組的市場規模（出貨量和收入）。
• 了解雲端 AI 晶片組出貨量和收入將如何以關鍵區域和架構（例如 GPU）成長
• 根據主要人工智慧框架以及推理和雲端人工智慧培訓的相對成長來評估策略
• 比較雲端和邊緣環境中人工智慧晶片組的市場規模

關鍵問題的答案：

• 到2030年，人工智慧晶片組在伺服器中的採用有多重要？
• 未來各地區AI晶片市場將如何發展？
• 這些晶片組針對哪些人工智慧框架？
• 到2030年，哪種晶片組架構將主導雲端人工智慧？

研究亮點：

• 2023-2030年雲端市場人工智慧晶片出貨量及營收預測
• 按區域、架構、工作負載和 AI 框架詳細細分

目錄

主要發現

主要建議

新資訊

調查方法

重要預測

Actionable Benefits:

• Identify the market size (shipments and revenue) of Artificial Intelligence (AI) chipsets in cloud environments for the rest of the decade.
• Understand how cloud AI chipset shipment and revenue will grow by key regions and architectures, e.g., Graphics Processing Units (GPUs).
• Evaluate strategies based on relative growth of key AI frameworks and inference versus training in cloud AI.
• Compare the market size of AI chipsets in the cloud to edge environments.

Critical Questions Answered:

• How significant will AI chipset adoption be in servers until 2030?
• How will the AI chipset market for each region develop going forward?
• Which AI frameworks will these chipsets target?
• Which chipset architecture will dominate cloud AI by 2030?

Research Highlights:

• Forecasts for AI chipset shipments and revenue in the cloud market from 2023 to 2030.
• Detailed breakdowns by region, architecture, workload, and AI framework.

Who Should Read This?

• Chipset vendors seeking greater insight into their market sizes and new growth areas.
• Sales and marketing leaders in diverse markets impacted by AI.
• Investors gauging the potential for growth in cloud AI.
• Strategists across the entire AI stack developing cloud AI product and marketing.

TABLE OF CONTENTS

Key Findings

Key Recommendations

What's New

Methodology

Significant Forecasts