人工智慧主要趨勢：端側人工智慧、開源投資、數據服務融資等。

這份報告調查了與全球人工智慧相關的主要趨勢，包括邊緣人工智慧的前景和預測、開源和閉源、底層模型的參數化規模、主要創新者和生成式人工智慧實施策略的分析。

報告的優點：

• 根據關鍵硬體和軟體趨勢制定內部和外部市場策略
• 根據市場走勢對您的內部能力和資訊傳遞進行基準測試
• 制定有機和無機人工智慧成長策略，考慮到主要市場領導者的情況
• 制定反映主要市場趨勢的短期、中期和長期訊息傳遞策略

關鍵問題的答案：

• 誰是加速邊緣和設備生成式 AI 發展的關鍵創新者？
• 領先的科技公司如何在 MLOps（機器學習營運）價值鏈中開發 AI 功能？
• 設備端人工智慧發展如何？ 誰在掌控？
• 超大規模企業如何避免硬體供應鏈挑戰？
• 人工智慧的監管環境如何？這對利害關係人意味著什麼？

研究亮點：

• 軟體、硬體和垂直產業的 13 個主要人工智慧趨勢
• 多種預測，包括邊緣人工智慧、開源和閉源、底層模型的參數化大小
• 評估主要趨勢對利害關係人的影響
• 營運商生成式人工智慧實施策略的詳細分析

目錄

• 開源與閉源
• 各大科技公司引進 "客製化" 模式
• 中美晶片大戰
• 邊緣人工智慧機遇
• 生成式 AI 用例
• 晶片供應商：探索軟體合作夥伴
• 各大科技公司開發獨特的人工智慧晶片
• 國際法規
• 人工智慧資料服務
• 電信業者的人工智慧活動
• 通訊生態系支持
• 企業人工智慧市場進入策略
• 晶片供應商主導的設備端人工智慧活動

Actionable Benefits:

• Build internal and external market strategy that builds on key hardware and software trends.
• Benchmark internal capabilities and messaging against market activity.
• Build organic and inorganic Artificial Intelligence (AI) growth strategy that considers key market leaders.
• Develop short, medium, and long-term messaging strategies to reflect key market trends.

Critical Questions Answered:

• Who are the key innovators accelerating generative AI at the edge and device?
• How is "big tech" developing AI capabilities across the Machine Learning Operations (MLOps) value chain?
• How is on-device AI developing and who is leading the charge?
• How are hyperscalers circumventing the hardware supply chain challenge?
• What does the AI regulatory landscape look like and what does it mean for stakeholders?

Research Highlights:

• 13 key AI trends spanning software, hardware, and vertical deployment.
• Multiple forecasts, including edge AI, open versus closed source, and foundation model parametric size.
• Evaluation of the impact key trends will have on stakeholders.
• In-depth breakdown of telco generative AI deployment strategies.

Who Should Read This?

• IT decision makers looking to build vertical AI deployment strategies.
• AI supply side strategy executives developing long-term product, marketing, and sales roadmaps, including Original Equipment Manufacturers (OEMs), chip vendors, hyperscalers, and Independent Software Vendors (ISVs).
• Marketing leaders looking to position their AI messaging effectively to build partnerships and align with customers.
• Telco strategists looking to identify opportunities and understand how their ecosystem is building on AI.

Table of Contents

• Open versus Closed Source
• Big Tech Introduces "Tailored" Models
• U.S.-China Chip War
• Edge AI Opportunities
• Generate AI Use Cases
• Chip Vendors Find Software Partners
• Big Tech Building Their Own AI Chips
• International Regulation
• AI Data Services
• Telecoms Industry AI Activity
• Telco Ecosystem Support
• Enterprise AI Go-to-Market Strategy
• Chip Vendor-Led On-Device AI Activity