The Foundations of Scalable AI

SponsoredPresented byVanguard A scalable AI system requires a strong foundation. Data, engineering, platforms, operating models, and governance must converge to work as one. This session from MIT Technology Review’s EmTech Future conference explores what it takes to build that foundation in a highly regulated environment and how a responsible, trustworthy implementation can turn emerging capabilities, including agentic systems, into lasting value for investors.

由 Vanguard 赞助。一个可扩展的 AI 系统需要坚实的基础。数据、工程、平台、运营模式和治理必须融合在一起，协同工作。本次来自《麻省理工科技评论》EmTech Future 大会的会议探讨了在高度监管的环境下构建该基础所需的条件，以及负责任、可信的实施如何将包括代理系统在内的新兴能力转化为投资者的持久价值。

About the speaker Jing Wang, Principal, Center for AI and Insights, Vanguard Jing Wang leads Vanguard’s Center for AI & Insights (CAI), advancing the firm’s AI, machine learning, generative AI, and behavioral science capabilities. Her team drives enterprise-wide innovation, research, and delivery, enabling Vanguard to translate emerging technologies into trusted solutions that enhance client experiences, improve investor outcomes, and create measurable business value.

关于演讲者：Jing Wang，Vanguard AI 与洞察中心负责人。Jing Wang 领导 Vanguard 的 AI 与洞察中心 (CAI)，推进公司在人工智能、机器学习、生成式 AI 和行为科学方面的能力。她的团队推动全企业的创新、研究和交付，使 Vanguard 能够将新兴技术转化为可信的解决方案，从而提升客户体验、改善投资者成果并创造可衡量的商业价值。

Before her current position, Jing served in a range of leadership roles across Vanguard’s Financial Services, Workplace Solutions, International, and Corporate Services divisions. Throughout her tenure, she has led teams and enterprise initiatives that advanced strategic priorities, strengthened client outcomes, and drove business performance across the firm. She joined Vanguard in 2009 after several years as a Principal at the Boston Consulting Group.

在担任现职之前，Jing 曾在 Vanguard 的金融服务、工作场所解决方案、国际业务和企业服务部门担任过多个领导职务。在任职期间，她领导了多个团队和企业计划，推进了战略重点，加强了客户成果，并推动了整个公司的业务绩效。她在波士顿咨询集团担任了几年负责人后，于 2009 年加入 Vanguard。

Jing earned a B.S. in Physics from the University of Science and Technology of China, a Ph.D. from the University of Pennsylvania, and an M.B.A. in Finance and Marketing from the Wharton School of Business at the University of Pennsylvania. Jing holds Series 7, 24, and 65 licenses.

Jing 获得了中国科学技术大学物理学学士学位、宾夕法尼亚大学博士学位，以及宾夕法尼亚大学沃顿商学院金融与市场营销 MBA 学位。Jing 持有美国金融业监管局 (FINRA) 的 Series 7、24 和 65 执照。

Deep DiveArtificial intelligenceDon’t be fooled—LLMs don’t reasonTen years after AlphaGo’s match against Go champion Lee Sedol, today’s AI still isn’t tapping into the machinery that made that win possible. By Thore Graepelarchive page

深度解析：人工智能。别被骗了——大语言模型（LLM）并不会推理。在 AlphaGo 与围棋冠军李世石对弈十年后，当今的 AI 仍然没有利用到使那场胜利成为可能的机制。作者：Thore Graepel，存档页面。

“We were looking at it wrong”: The explosive claim that’s upended the AI worldAn exclusive interview with Nick Cammarata, the researcher whose 26,000-word viral blog post has AI safety folks celebrating. By Will Douglas Heavenarchive page

“我们一直看错了”：颠覆 AI 界的爆炸性主张。对研究员 Nick Cammarata 的独家专访，他那篇 26,000 字的病毒式博客文章让 AI 安全领域的人士欢呼雀跃。作者：Will Douglas Heaven，存档页面。

Don’t be fooled by this summer of AI hype Breathless claims about AGI and new capabilities fall apart pretty quickly under scrutiny. By Timnit Gebruarchive pageEmily M. Benderarchive page

别被这个 AI 炒作之夏所迷惑。关于通用人工智能（AGI）和新能力的夸大宣传在审查下很快就会破灭。作者：Timnit Gebru，存档页面；Emily M. Bender，存档页面。

The inside story on why OpenAI agents hacked Hugging FaceThe underlying models had been rewarded for cheating and communicating with each other, a new OpenAI report finds. By Grace Huckinsarchive page

OpenAI 代理为何入侵 Hugging Face 的内幕。一份新的 OpenAI 报告发现，底层模型因作弊和相互通信而获得了奖励。作者：Grace Huckins，存档页面。

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