人工智慧和机器学习：云端人工智慧

本报告调查了云端环境中人工智慧（AI）和机器学习的趋势，并提供了有关云端环境中人工智慧晶片组的市场规模（出货量和收入）、区域、架构、工作负载和人工智慧框架的资讯。

实际好处：

• 可以了解未来 10年云端环境中 AI 晶片组的市场规模（出货量和收入）。
• 了解云端 AI 晶片组出货量和收入将如何以关键区域和架构（例如 GPU）成长
• 根据主要人工智慧框架以及推理和云端人工智慧培训的相对成长来评估策略
• 比较云端和边缘环境中人工智慧晶片组的市场规模

关键问题的答案：

• 到2030年，人工智慧晶片组在伺服器中的采用有多重要？
• 未来各地区AI晶片市场将如何发展？
• 这些晶片组针对哪些人工智慧框架？
• 到2030年，哪种晶片组架构将主导云端人工智慧？

研究亮点：

• 2023-2030年云端市场人工智慧晶片出货量及营收预测
• 按区域、架构、工作负载和 AI 框架详细细分

目录

主要发现

主要建议

新资讯

调查方法

重要预测

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