人工智慧主要趋势：端侧人工智慧、开源投资、数据服务融资等。

这份报告调查了与全球人工智慧相关的主要趋势，包括边缘人工智慧的前景和预测、开源和闭源、底层模型的参数化规模、主要创新者和生成式人工智慧实施策略的分析。

报告的优点：

• 根据关键硬体和软体趋势制定内部和外部市场策略
• 根据市场走势对您的内部能力和资讯传递进行基准测试
• 制定有机和无机人工智慧成长策略，考虑到主要市场领导者的情况
• 制定反映主要市场趋势的短期、中期和长期讯息传递策略

关键问题的答案：

• 谁是加速边缘和设备生成式 AI 发展的关键创新者？
• 领先的科技公司如何在 MLOps（机器学习营运）价值链中开发 AI 功能？
• 设备端人工智慧发展如何？ 谁在掌控？
• 超大规模企业如何避免硬体供应链挑战？
• 人工智慧的监管环境如何？这对利害关係人意味着什么？

研究亮点：

• 软体、硬体和垂直产业的 13 个主要人工智慧趋势
• 多种预测，包括边缘人工智慧、开源和闭源、底层模型的参数化大小
• 评估主要趋势对利害关係人的影响
• 营运商生成式人工智慧实施策略的详细分析

目录

• 开源与闭源
• 各大科技公司引进 "客製化" 模式
• 中美晶片大战
• 边缘人工智慧机遇
• 生成式 AI 用例
• 晶片供应商：探索软体合作伙伴
• 各大科技公司开发独特的人工智慧晶片
• 国际法规
• 人工智慧资料服务
• 电信业者的人工智慧活动
• 通讯生态系支持
• 企业人工智慧市场进入策略
• 晶片供应商主导的设备端人工智慧活动

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