宏途：人工智能引领的数字浪潮

本书聚焦数字经济领域，深度剖析其在全球的发展态势与中国的机遇挑战。本书涵盖数字经济的多个关键层面，从数字经济大国中国的崛起，展现其规模增长、技术创新等成就，到人工智能大模型掀起的巨浪，探讨其技术演进、商业应用及安全风险。作者深入解读大模型的盈利模式、端侧AI的发展前景，以及企业在人工智能时代的发展思路，为企业提供数字化转型的策略参考。同时，对空间智能、软件、数据等领域进行了全面分析，阐述数据资产化的重要性与实现路径，强调构筑企业数字化领导力的关键意义。此外，还关注到低空经济这一万亿赛道的全球格局与中国发展，探讨技术创新趋势和政策响应维度。

杨之曙教授自2001年执教于清华大学经济管理学院，2009年至今任清华大学经济管理学院教授。期间曾担任香港科技大学管理学院访问学者、麻省理工学院斯隆管理学院访问学者。研究领域包括金融市场微观结构，行为金融，银行与金融机构，研究成果发表在Journal of Finance, Journal of Financial Quantitative and Analysis, Journal of Financial Markets, Journal of Corporate Finance, China Economic Review等国际顶尖和一流学术期刊。

第一章 数字经济：中国与世界········································.1
数字经济大国···················································.3
大变局如期而至················································.9
案例：中国电信构建数字经济国家底座·················.11
第二章 大模型掀起AI 的巨浪·········································17
字母“T”的故事···············································18
大模型的威力···················································22
大模型需要千万场景和海量数据···························24
中国AI 商业化历程回顾······································27
AI 的安全风险··················································29
案例：“道交一体化”调解大模型··························30
第三章 大模型如何真正盈利···········································33
GPT 的发展历程················································35
大模型的进展···················································39
大模型如何产生真正的价值·································42
案例：中国联通用大模型重构业务························44
第四章 端侧AI：未来已来············································47
AI 重塑手机能力···············································49
新一代芯片和手机大模型加速面世························51
XR：另一个热门端侧·········································55
AI PC：焕新赛道···············································57
NPU 定义AI PC ················································58
AI 浪潮推动PC 智能化·······································61
案例：豆包的AI 耳机·········································65
第五章 企业AI 化的发展思路·········································67
从个人赋能到系统重构：企业AI 落地的双轨演进·····68
企业知识库······················································70
交互型多模态大模型：全能王者···························76
混合专家模型···················································79
混合AI 架构：成本优势······································82
风险投资公司的投资偏好····································83
案例：金融行业的谷歌·······································87
第六章 空间智能：一块关键拼图·····································89
从具身智能的定义说起·······································90
触觉数据是增量信息··········································92
人形机器人：万亿美元的市场······························95
热闹的展示 遇冷的商业化···································99
案例：腾讯Robotics X 实验室的机器狗Max ·········.101
第七章 软件：数字经济的硬度·····································.105
从“卖产品”到“建生态” ·····································.106
价值：关键技术与数字平台······························.107
数字经济的底盘·············································.109
第八章 数据：洞察力的货币········································.111
释放数据要素潜能··········································.113
数字产权的三个基本问题·································.115
全球的数据定价和收益分配问题························.118
企业数据交易：蹒跚学步·································.122
数据资产图谱················································.124
案例：阿里巴巴集团数据要素的定价和收益结算···.126
第九章 新增长极：数据资产管理··································.131
数据要素市场日趋活跃····································.134
从数据到数据资源化·······································.136
数据资产化第一步：确权·································.137
数据资产化闭环：入表····································.139
数据资本化：惊险的一跳·································.141
细说数据资产：企业迈出的第一步·····················.142
案例：恒丰银行数据资产估值研究与入表探索······.144
第十章 构筑企业的数字化领导力··································.147
冰山之下······················································.148
数字融合的四个步骤·······································.149
案例：华为智能制造实践·································.150
第十一章 万亿赛道：低空经济的演进轨迹与全球格局······.157
各国家和地区竞相布局低空经济························.159
从无到优：中国低空经济的发展情况··················.161
发展思路：技术+生态+人才······························.163
地方政府推动低空经济快速发展························.165
商业化运营的挑战··········································.167
培育市场 任重道远·········································.170
第十二章 技术创新的四个趋势·····································.173
无处不在的感知·············································.174
跨域多维的关联·············································.176
超越人脑的智能·············································.178
真实与虚拟的交融··········································.183
第十三章 政策响应的六个维度·····································.187
提升产业科技创新能力····································.188
发展数字经济核心产业····································.189
推进制造业数字化网络化智能化························.190
完善数字基础设施和服务体系···························.191
培育壮大一批优质企业····································.191
完善数据治理体系··········································.192