Crypto 和 AI，需要女高管

marsbitPublished on 2026-01-21Last updated on 2026-01-21

Abstract

最近AI圈出现一个现象：越来越多女性高管走向台前。Meta收购Manus后，其90后COO CZ Chen进入大众视野；MiniMax上市时，94年出生的COO贠烨祎身价达48亿港元，她几乎包办公司除技术外的所有事务。全球范围内，Anthropic的Daniela Amodei、DeepMind的Lila Ibrahim、前OpenAI CTO Mira Murati等女性高管也扮演关键角色。 这一现象与2017-2021年加密黄金时代类似，当时币安何一、BitMEX的Lisa Loud、Matrixport的Cynthia Wu等女性高管也曾在行业中发挥重要作用。Crypto和AI行业都具有“前沿又土”的特点：技术底层革新，但创始人多技术背景，缺乏商业化和对外沟通能力。 女性高管成为技术天才与外部世界的桥梁，擅长将技术转化为商业战略，推动产品市场化和大众化。其共情能力在公关和产品推广中具有优势。人才流向反映行业价值：AI行业正经历从实验室到商业化的转折，而加密行业若无法留住具备技术理解力和商业敏感度的精英，可能难以实现大规模应用。 女性高管的崛起标志行业真正成熟，她们去向哪里，价值就在哪里创造。

撰文:Alice,深潮 TechFlow

最近注意到 AI 圈一个有趣的现象,越来越多的女性高管开始站到舞台前。

12 月 30 号,Meta 宣布将以 20 亿美元的高价收购 Manus, 90 后 COO CZ Chen 开始进入大众视野,本科上财,哥大硕士,18 年开始工作,先后供职于万科,FA 机构,2024 年最后一跳进入 Manus,直接财务自由。

1 月 9 日,MiniMax 上市敲钟仪式上,与 36 岁创始人闫俊杰一同站在台上的,是一位 94 年出生的女生,贠烨祎。

这位年仅 31 岁的 COO,如今身价已达 48 亿港元。

贠烨祎什么背景?

约翰霍普金斯大学电子工程,辅修经济学和数学;2017 年毕业就进商汤,从融资经理做到 CEO 徐立的助理,再到创新业务部总监,亲历了商汤从独角兽到港股上市的全过程。

2022 年,闫俊杰决定离开商汤创办 MiniMax,贠烨祎几乎没犹豫就跟了过去。

她的价值不只是跟随。

MiniMax 招股书显示,贠烨祎几乎包办了公司除技术研发外的所有事务:产品、商业化、董事会、运营、管理......她的年薪是 147.9 万美元,比其他所有执行董事加起来还多,这个金额足以说明一切。

不只是中国,放眼全球 AI 圈,女性力量都不容小觑。

Daniela Amodei,英文文学专业出身,在 Stripe 和 OpenAI 打拼之后,在 2021 年与哥哥 Dario 联合创立 Anthropic,担任总裁,专注日常运营和商业化,推动 Claude 产品的市场化。

Lila Ibrahim,前 Intel 高管,2018 年加入 DeepMind 成为首任 COO ,负责日常运营、合作伙伴关系、社会影响、外部事务与政府关系。

Mira Murati,这位阿尔巴尼亚裔的前 OpenAI CTO,16 岁获奖学金来美国,从特斯拉 Model X 团队到 OpenAI,最终离职创立 Thinking Machines Lab,估值 90 亿美元......

这个场景似曾相识。

2017-2021 年,加密黄金时代里群星荟萃,其中一道靓丽的风景就是,女性 CMO 和 COO。

最让人熟知的当属币安联合创始人兼 CMO 何一(现在已经是联席 CEO),从上海到东京,再从马耳他到巴黎再到迪拜,每一次战略转移都有她的身影,帮助公司成为全球最大的加密货币交易所。

Lisa Loud,从苹果工程师到 PayPal 加拿大市场负责人,2017 年跳槽 BitMEX 担任 CMO,此后 BitMEX 一度成为全球最大的加密衍生品交易平台。

Cynthia Wu,Matrixport 的 COO,前港交所产品开发副总裁,将传统金融的经验带到了加密金融服务中,帮助公司成为亚洲最大的数字资产服务平台之一。

......

曾经,加密就是全世界的资产焦点,聚光灯自然也打在了这些站在舞台中央的女性高管身上。

但潮水退了,主角更换。

如今,AI 才是聚光灯的焦点,于是我们看到了 Daniela Amodei 登上福布斯富豪榜,看到了贠烨祎在 MiniMax 上市敲钟现场意气风发。

从本质来看,Crypto 和 AI 有着惊人的相似性,“又前沿又土”。

前沿体现在技术本身,区块链重构信任机制,AI 重构生产力,都是能改变世界的底层技术。

土则体现在创始人画像上,大多技术背景,对代码如数家珍,但对市场营销,特别是政府关系、公关关系感到陌生。

这就是女性 COO/CMO 的价值所在,她们是技术天才与外部世界之间的桥梁,能跟技术团队深度对话,也能向投资人和用户讲出动人故事。

Daniela Amodei 将 AI 安全哲学转化为可执行的商业战略,让 Claude 在 ChatGPT 的阴影下杀出重围;贠烨祎让 MiniMax 从实验室走向 C 端市场;何一长期担任首席客户,亲自为用户解答疑惑,建立信任。

当一个产品脱离纯技术阶段,越需要面向 C 端,女性高管的优势就越明显。

毕竟,公关和产品需要的不是对抗思维,而是共情能力。

从另外一个角度出发,有能力的女性高管会用脚投票,她们去那些能让自己施展才华、创造价值的地方。如果当她们开始离开某个行业时,说明这个行业的商业确定性在消失。

加密行业现在的问题很明显,缺少能把技术转化为大众接受的产品的人才,Mass adoption 和正外部性依然是空谈。观察任何新兴行业都能发现这个规律,当那些兼具技术理解力、商业敏感度和叙事能力的女性高管开始崛起时,行业才真正从技术驱动转向商业化和大众化。

她们的出现,标志着行业的真正成熟。

AI 圈已经经历这个转折,像 Daniela Amodei 和贠烨祎这样的女性高管正在推动技术产品化,让 AI 从实验室算法走进日常生活和商业世界。

而加密行业,如果留不住“能讲人话的精英”,那就活该继续在泥潭里 PVP。

人才的流向就是行业的风向标。

她们去哪里,价值就在哪里被创造;她们离开的地方,往往就是泡沫破裂的地方。

Trending Cryptos

ctr
CitreaCTR
wstusdt
wrapped stUSDTWSTUSDT
apr
aPrioriAPR
ctx
Cryptex FinanceCTX
audio
AudiusAUDIO
comp
CompoundCOMP
mantra
MantraMANTRA
xvs
VenusXVS
waxl
AxelarWAXL
bill
Billions NetworkBILL
pyth
PYTH (Pyth)PYTH
rune
THORChainRUNE
velodrome
Velodrome FinanceVELODROME
brev
BrevisBREV
zrx
ZRX（0X）ZRX

Related Questions

Q文章中提到哪些AI和Crypto领域的女性高管？

AAI领域：Meta收购的Manus的COO CZ Chen、MiniMax的COO贠烨祎、Anthropic联合创始人兼总裁Daniela Amodei、DeepMind首任COO Lila Ibrahim、前OpenAI CTO Mira Murati；Crypto领域：币安联合创始人兼CMO（现联席CEO）何一、BitMEX前CMO Lisa Loud、Matrixport COO Cynthia Wu。

Q为什么AI和Crypto行业需要女性高管？

A因为AI和Crypto技术前沿但创始人多为技术背景，缺乏市场营销、政府关系和公关能力。女性高管擅长共情和沟通，能作为技术团队与外部世界的桥梁，将技术转化为大众接受的产品，推动行业商业化和大众化。

Q贠烨祎在MiniMax扮演什么角色？

A贠烨祎担任MiniMax的COO，几乎包办了除技术研发外的所有事务，包括产品、商业化、董事会、运营和管理。她的年薪高达147.9万美元，体现了其在公司的重要价值。

Q女性高管的崛起对行业意味着什么？

A女性高管的崛起标志行业从技术驱动转向商业化和大众化，是行业真正成熟的信号。她们的流向反映行业价值创造的方向，离开则可能预示行业泡沫破裂或商业价值下降。

Q加密行业当前面临什么问题？

A加密行业缺乏能将技术转化为大众接受产品的人才，Mass adoption（大规模采用）和正外部性仍是空谈。如果留不住具备技术理解力、商业敏感度和叙事能力的精英，行业可能继续陷入内耗（PVP）。

Related Reads

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

In three days, Google lost two AI legends. On June 18, Noam Shazeer, co-author of the seminal "Attention is All You Need" paper and Gemini co-lead, left for OpenAI. Just 48 hours later, John Jumper, 2024 Nobel laureate and AlphaFold lead, departed DeepMind for Anthropic. This follows Andrej Karpathy joining Anthropic in May. These moves highlight a structural trend: top AI talent is concentrating at mission-driven, pre-IPO firms like OpenAI and Anthropic, while Google becomes a primary source. The exodus stems from a core mission mismatch. Google's ad-centric model often subordinates AI research to product and revenue goals, creating friction for pioneers like Shazeer, who returned in 2024 only to leave again. In contrast, OpenAI and Anthropic offer singular focus on pushing AI boundaries, whether towards AGI or safety-aligned models, which deeply appeals to top researchers like Jumper. Financial incentives amplify the pull. With both OpenAI and Anthropic nearing IPO, employees stand to gain immensely from equity, an upside Google's mature stock cannot match. Furthermore, the 2023 merger of Google Brain and DeepMind, intended to consolidate strength, has instead created cultural tension and slowed the path from research to product, as evidenced by Gemini's pace. This talent redistribution is reshaping the AI landscape. While Google retains vast data and compute resources, its true crisis is the quiet, continuous loss of the people who define the field's future. The real moat in AI is not infrastructure, but the concentration of brilliant minds—a battle Google is currently losing.

marsbit49m ago

Two Legends Lost in Three Days: Is Google's AI Talent Dam Cracking?

marsbit49m ago

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

Beyond the familiar performance charts like MMLU-Pro and MMMU, which major AI models strive to ace, stands a key "examiner": Chinese-Canadian researcher Wenhu Chen. An assistant professor at the University of Waterloo and founder of TIGERLab, Chen addresses the crucial need for more rigorous AI evaluation. As models like GPT-4 began scoring near-perfect results on older benchmarks like MMLU, it became difficult to distinguish their true capabilities. In response, Chen introduced MMLU-Pro in 2024, featuring harder, more reasoning-focused questions with more answer choices, successfully reintroducing meaningful performance gaps. His work extends to multi-modal evaluation with MMMU and its enhanced version, MMMU-Pro. These benchmarks test a model's ability to understand and reason with complex information from images, charts, and text across diverse academic subjects, exposing the significant challenges even top models face in genuine comprehension. Chen's background in complex QA, table reasoning, and his experience at Google DeepMind on projects like Gemini inform his approach. He understands that effective benchmarks must anticipate how models might "cheat" by memorizing data or avoiding visual analysis. His lab also actively researches video understanding and generation models (e.g., UniVideo, Vamba), ensuring his evaluation work is grounded in practical model-building challenges. Now at Meta's Super Intelligence Lab, Chen continues his focus on multi-modal data and evaluation, representing the deep yet often unseen contributions of Chinese talent in shaping the fundamental tools of the AI industry.

marsbit1h ago

Behind the AI Report Card, Lies a Chinese 'Exam Setter'

marsbit1h ago

Alliance Co-founder's Letter to Entrepreneurs: Written at the Moment Cursor Sold for $600 Billion

Alliance Co-founder's Letter to Entrepreneurs: On Cursor's $60 Billion Sale Many aspiring founders see massive exits like Cursor's $60B sale and wonder why they can't achieve the same, often concluding opportunities are exhausted. But great companies aren't built in obvious, crowded spaces. Cursor, like Stripe, Figma, and Shopify before it, started with a non-consensus belief about the future. Before ChatGPT, they believed AI would transform knowledge work. They focused on a genuinely exciting domain, became their own customer, and obsessed over power users. Their journey involved years of "glass-chewing" effort before the market was ready. The pattern is consistent: identify a long-term technological shift, find a missed entry point, and execute for years before the trend becomes obvious. First-generation products (PayPal, Adobe, Amazon) prove a market exists. Second-generation winners (Stripe, Figma, Shopify) rebuild that market around new insights, technology, or changing customer behaviors. Founders must identify their phase in the cycle. Early entrants like Coinbase or Cursor focus on making new technology usable for power users. Later entrants find the "yin" to the established "yang"—the blind spots incumbents miss as they grow distant from individual users. The key is deep market immersion. Use every product in your space. Talk to users. Build an audience. Stop looking for ideas and start *seeing* them everywhere. Then, choose one. The idea must offer a 10x improvement or solve a "hair-on-fire" pain point—something severe enough that users are already crafting workarounds. When building, avoid feature bloat. Ask: why would someone switch? Great startups rarely force new behaviors; they improve familiar workflows with drastically lower friction (e.g., Cursor forked VS Code instead of creating a new editor). Distribution is the underestimated moat. Before product-market fit, achieve distribution-market fit. How do customers discover new tools? Founders like those at Airbnb, Stripe, and Cursor did unscalable, manual work to recruit early users. The final, unteachable ingredient is resilience. Cursor built for years pre-market, faced rejection, and persisted. So did Airbnb, Nvidia, and Rain (which launched post-FTX collapse). The lesson isn't that these founders were smarter, but that they stayed in the game long enough for their insights to compound. Framework: Spot technological cycles. Cultivate unique insight. Obsess over your market. Talk to customers. Find a hair-on-fire problem. Build the simplest wedge. Win your distribution channel. Above all, don't quit when it gets hard. Most people won't do these things consistently. The few who do build the next generation of great companies. Go build.

marsbit1h ago

Alliance Co-founder's Letter to Entrepreneurs: Written at the Moment Cursor Sold for $600 Billion

marsbit1h ago

Weekly Editor's Picks (0613-0619)

Weekly Editor's Picks (0613-0619): Market Insights & Analysis This weekly digest curates in-depth analysis often lost in the information flow, focusing on key insights across macro trends, investment, and technology. **Macro & Geopolitics:** With the Strait of Hormuz reopening and military conflict shifting to negotiation, markets are pivoting from "war shock" to "supply restoration." Trades include shorting crude risk premiums, longing airlines/tourism, Asian energy importers, and bond duration, while shorting inflation expectations. LNG, fertilizer, and chemical chains are also being repriced. **Investment & VC:** Ray Dalio advises against betting on concentrated AI giants dominating indices, advocating for diversified portfolios of high-quality, low-correlation assets instead. Analysis covers the 4-year crypto cycle, predicting the core surviving product by 2029 will be asset trading markets. Current BTC metrics suggest a potential bottoming zone, presenting a patient accumulation window. SpaceX's high-profile IPO at a $2.1T valuation faces scrutiny over fundamentals, with key watchpoints being its likely inclusion in the Nasdaq index and Q2 earnings. Concerns are raised about potential "gamma squeeze" and systemic risks if its narrative-driven valuation gets amplified by passive index funds. Robinhood (HOOD) is noted for breaking its high correlation with crypto, bolstered by its stock trading and new underwriting business. **Web3 & AI:** A warning highlights ~$1.8T in off-balance-sheet AI infrastructure commitments (purchase commitments, leases) as a potential systemic risk if AI monetization lags. AI models are being used for World Cup predictions, adding a new layer for betting markets. A cost breakdown of a $20 AI subscription reveals the supply chain from model companies to cloud, GPUs, and power. **Prediction Markets:** The emergence of prediction market "concept stocks" is noted, with Robinhood developing its own platform, Rothera, signaling a shift from market competition to a "channel war" for user access. **CeFi & DeFi:** The SpaceX IPO tested perpetual contract mechanisms for pre-IPO assets, highlighting challenges in handling corporate actions like stock splits on-chain. The de-pegging of STRC (Strategy's preferred share) to ~$89 reflects market concerns over MicroStrategy's capital structure and BTC-backed leverage model. BlackRock's covered-call Bitcoin ETF (BITA) offers yield but caps upside, appealing to yield-seeking institutions. **Ethereum:** An opinion piece argues Ethereum's core strength is its vast developer community and composability, solidifying its role as the default operating system for the financial internet. **Weekly Hot Topics:** Include the US-Iran deal reopening the Strait of Hormuz, Fed's hawkish hold, Anthropic restricting model access, SpaceX acquiring Cursor, and a humorous stock surge for "Liuliumei" due to its "LLM" ticker.

marsbit1h ago

Weekly Editor's Picks (0613-0619)

marsbit1h ago

Alliance's Co-Founder's Letter to Entrepreneurs: Written on the Occasion of Cursor's $60 Billion Sale

In this letter to entrepreneurs, Alliance reflects on the success of Cursor's $60 billion sale to Elon Musk, using it as a case study to counter the misconception that opportunities in crowded fields like AI or crypto are exhausted. The piece argues that great companies like Cursor, Stripe, Figma, and Shopify are not built by geniuses with perfect ideas, but by founders who start with a non-consensus belief about the future and build for years before that future becomes obvious to everyone. They identify long-term shifts, find overlooked entry points, and execute relentlessly. The framework for success involves: 1. **Identifying your place in the technology cycle**: Early-stage opportunities focus on making new tech usable for power users (e.g., Coinbase, Cursor). Later-stage opportunities involve finding the "yin" to an existing "yang"—the blind spots of first-generation players (e.g., Stripe vs. PayPal, Figma vs. Adobe). 2. **Cultivating unique insights**: Immerse yourself deeply in the market. Use every product, talk to users, and build an audience. Insights will emerge naturally from deep engagement. 3. **Finding a "hair-on-fire" problem**: Look for a 10x improvement or a severe, urgent pain point. The strongest signal is people already building clumsy workarounds. 4. **Building a focused MVP**: Don't just add features because you can. Ask why users would abandon their current tool for yours. The best startups rarely force new behaviors; they improve familiar workflows with drastically lower friction. 5. **Winning a distribution channel**: Distribution is often the moat. Before product-market fit, achieve channel-market fit. Find where your customers are and build an engine to reach them, even through unscalable, manual efforts initially. 6. **Persistence**: The final, unteachable ingredient is resilience. Success stories like Cursor, Airbnb, and Nvidia involved years of grinding, rejection, and perseverance when the path forward seemed unclear. The conclusion is that there is no secret. Most people fail to consistently execute these steps over the long term. The few who do build the companies that define the next era. The world is yours to create.

链捕手1h ago

Alliance's Co-Founder's Letter to Entrepreneurs: Written on the Occasion of Cursor's $60 Billion Sale

链捕手1h ago

Trading

Spot
Futures

Hot Articles

How to Buy ALICE

Welcome to HTX.com! We've made purchasing My Neighbor Alice (ALICE) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy My Neighbor Alice (ALICE) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your My Neighbor Alice (ALICE)After purchasing your My Neighbor Alice (ALICE), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade My Neighbor Alice (ALICE)Easily trade My Neighbor Alice (ALICE) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

3.3k Total ViewsPublished 2024.03.29Updated 2026.06.02

How to Buy ALICE

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of ALICE (ALICE) are presented below.

活动图片

Top Questions