AI和機器學習:TinyML

本報告提供AI和機器學習的市場調查，彙整TinyML的AI晶片組的出貨數·收益的預測，地區·產業·架構·主要案例等各種區分的詳細分析，主要的洞察等資訊。

實用的優點:

• 您可以了解 2030 年之前嵌入式設備中 TinyML（微型機器學習）/AI 晶片組的市場規模（出貨量和收入）。
• 了解 TinyML 晶片組出貨量和收入將如何以關鍵區域和架構（例如 NPU）成長
• 根據關鍵用例、產業、設備類型和架構的相對成長來評估策略

重要問題的答案：

• 到 2030 年，人工智慧晶片組在嵌入式設備的採用有多重要？
• 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用例？
• 到 2030 年，哪種晶片組架構將主導 TinyML？

研究亮點：

• TinyML 市場人工智慧晶片組出貨量與收入預測：2023-2030 年
• 按地區、產業、架構和用例詳細分類

目錄

主要發現

關鍵洞察建議

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 Tiny Machine Learning (TinyML)/embedded devices for the rest of the decade.
• Understand how TinyML chipset shipments and revenue will grow by key regions and architectures, e.g., Neural Processing Units (NPUs).
• Evaluate strategy based on relative growth of key use cases, verticals and device types, and architectures.

Critical Questions Answered:

• How significant will AI chipsets adoption be in embedded devices through 2030?
• How will the AI chipset market for each region develop going forward?
• Which AI use cases will these chipsets target?
• Which chipset architecture will dominate TinyML by 2030?

Research Highlights:

• Forecasts for AI chipset shipments and revenue in the TinyML market from 2023 to 2030.
• Detailed breakdowns by region, vertical, architecture, and use case.

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 TinyML.
• Strategists across the entire AI stack developing embedded products and marketing.

TABLE OF CONTENTS

Key Findings

Key Insights Recommendations

Whats New

Methodology

Significant Forecasts