Crypto 和 AI,需要女高管

比推Pubblicato 2026-01-21Pubblicato ultima volta 2026-01-21

Introduzione

最近AI圈出现一个现象:女性高管日益活跃。Meta收购Manus后,90后COO CZ Chen进入公众视野;MiniMax上市时,31岁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联合创始人Daniela Amodei、DeepMind的Lila Ibrahim等女性高管也扮演关键角色。 这一现象曾在2017-2021年加密行业出现,如何一、Lisa Loud等女性CMO/COO推动交易所成长。Crypto和AI行业相似:技术前沿但创始人多偏技术背景,缺乏市场与公关能力。女性高管成为技术与外界的桥梁,擅长共情、叙事和商业化,推动产品从实验室走向大众。 行业成熟需要女性高管实现技术产品化。AI已进入这一阶段,而加密行业若留不住此类人才,可能难以实现大规模应用。人才流向标志行业价值所在,女性高管的崛起往往意味着行业商业化成熟。

作者:Alice,深潮 TechFlow

原标题:Crypto 和 AI,需要女高管


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。


原文链接:https://www.bitpush.news/articles/7604790

Crypto di tendenza

Domande pertinenti

Q文章中提到Crypto和AI行业需要女性高管的原因是什么?

A文章指出Crypto和AI行业技术性较强,创始人多为技术背景,但在市场营销、政府关系和公共关系方面较为薄弱。女性高管(如COO/CMO)能够作为技术团队与外部世界的桥梁,既理解技术细节,又能向投资人和用户讲述动人故事,推动技术产品化和商业化。

Q文中提到的AI圈女性高管有哪些?请列举两位并简述她们的成就。

A文中提到的AI圈女性高管包括:1. Daniela Amodei,Anthropic联合创始人兼总裁,专注于日常运营和商业化,推动Claude产品的市场化;2. 贠烨祎,MiniMax的COO,负责产品、商业化、运营等事务,帮助公司从实验室走向C端市场,身价达48亿港元。

Q加密黄金时代中提到的女性高管有哪些?请举例说明。

A加密黄金时代的女性高管包括:1. 何一,币安联合创始人兼CMO(现联席CEO),帮助币安成为全球最大加密货币交易所;2. Lisa Loud,BitMEX的CMO,推动其成为全球最大加密衍生品交易平台;3. Cynthia Wu,Matrixport的COO,将传统金融经验带入加密金融服务。

Q文章认为女性高管在哪些方面具有优势?

A文章认为女性高管在公关和产品方面具有共情能力优势,能够与技术团队深度对话,同时向外部世界有效传递价值。她们擅长将技术转化为大众接受的产品,推动行业从技术驱动转向商业化和大众化。

Q文章最后对加密行业提出了什么批评或建议?

A文章批评加密行业缺乏能将技术转化为大众产品的人才,导致Mass adoption和正外部性难以实现。建议行业留住“能讲人话的精英”,否则可能继续陷入内部竞争(PVP)而无法成熟。人才的流向被视为行业价值创造的风向标。

Letture associate

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

Ethereum Q1 2026 Report: Fees Down, Users & Transactions Hit New Highs Token Terminal's Q1 2026 report on Ethereum presents a pivotal development: the network achieved record highs in monthly active users (13.2M, +85.9% YoY), total transactions (200.4M, +81.5% YoY), and throughput (25.78 TPS), while transaction fees on the mainnet plummeted by 47.9% quarter-over-quarter. This shift is attributed to the network's strategic move into a "low fees for scale" phase, exemplified by the Fusaka upgrade which increased data capacity and lowered block space costs, releasing pent-up demand (a manifestation of Jevons's Paradox). The report highlights a core narrative shift for Ethereum: from a DeFi-centric blockchain to a global financial settlement layer. It maintains a dominant position in tokenized assets, holding majority market shares among top chains in stablecoins (61.8%), tokenized funds (73.0%), and tokenized commodities (84.0%). Growth in tokenized funds (+73.1% YoY) and commodities (+325.9% YoY) was particularly strong, driven by institutions like BlackRock and JPMorgan entering the space. Contrasting these usage gains, several USD-denominated value metrics declined in Q1: fully diluted market cap fell 30.3% QoQ, total value locked (TVL) dropped 11.0%, and ecosystem transaction volume decreased 24.0%. The report interprets this as Ethereum prioritizing long-term network expansion and cementing its role as the default settlement layer for finance over short-term fee capture. The commentary from Etherealize argues that, much like the early internet, Ethereum's open, permissionless model is poised to win over closed alternatives as institutional tokenization accelerates.

marsbit1 h fa

Ethereum Q1 2026 Report: Fees Decline, Users and Transaction Volume Hit New Highs

marsbit1 h fa

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

Pete Florence, a former senior research scientist at Google DeepMind and a key contributor to the Vision-Language-Action (VLA) model architecture, is deliberately distancing his startup, Generalist AI, from the trendy "world model" label. He argues that the industry should prioritize concrete goals over buzzwords. His goal is to create robots that can perform a vast range of unseen tasks with high speed and success rates, without needing task-specific training data. Recently, his company raised $400 million (¥2.7 billion) at a $2 billion valuation. Notable investors include NVIDIA's NVentures, Bezos Expeditions, NFDG, as well as Xiaomi co-founder Lin Bin, Zoom founder Eric Yuan, and renowned AI scientist Fei-Fei Li. Florence's approach stems from his academic background at MIT under Professor Russ Tedrake, focusing on understanding the physical world. After joining DeepMind, he developed models like Transporter Network and co-created the VLA framework. He left in 2025 to found Generalist AI. The company has launched two models: GEN-0, which demonstrated that scaling laws apply to physical motion, and GEN-1. GEN-1 was trained on over 500,000 hours of physical interaction data collected via a specialized wearable device. It achieves a 99% success rate on precise mechanical tasks like folding boxes and maintains performance three times faster than its predecessor. Florence believes GEN-1 is reaching a commercial utility threshold similar to the GPT-3 inflection point. The substantial funding round, following GEN-1's release, signifies strong investor confidence in Generalist AI's practical, goal-driven path to creating versatile, useful robots, regardless of the "world model" terminology.

marsbit1 h fa

He Just Raised 2.7 Billion, and Li Fei-Fei Also Invested

marsbit1 h fa

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.

marsbit3 h fa

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

marsbit3 h fa

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.

marsbit3 h fa

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

marsbit3 h fa

Trading

Spot
Futures

Articoli Popolari

Come comprare ALICE

Benvenuto in HTX.com! Abbiamo reso l'acquisto di My Neighbor Alice (ALICE) semplice e conveniente. Segui la nostra guida passo passo per intraprendere il tuo viaggio nel mondo delle criptovalute.Step 1: Crea il tuo Account HTXUsa la tua email o numero di telefono per registrarti il tuo account gratuito su HTX. Vivi un'esperienza facile e sblocca tutte le funzionalità,Crea il mio accountStep 2: Vai in Acquista crypto e seleziona il tuo metodo di pagamentoCarta di credito/debito: utilizza la tua Visa o Mastercard per acquistare immediatamente My Neighbor AliceALICE.Bilancio: Usa i fondi dal bilancio del tuo account HTX per fare trading senza problemi.Terze parti: abbiamo aggiunto metodi di pagamento molto utilizzati come Google Pay e Apple Pay per maggiore comodità.P2P: Fai trading direttamente con altri utenti HTX.Over-the-Counter (OTC): Offriamo servizi su misura e tassi di cambio competitivi per i trader.Step 3: Conserva My Neighbor Alice (ALICE)Dopo aver acquistato My Neighbor Alice (ALICE), conserva nel tuo account HTX. In alternativa, puoi inviare tramite trasferimento blockchain o scambiare per altre criptovalute.Step 4: Scambia My Neighbor Alice (ALICE)Scambia facilmente My Neighbor Alice (ALICE) nel mercato spot di HTX. Accedi al tuo account, seleziona la tua coppia di trading, esegui le tue operazioni e monitora in tempo reale. Offriamo un'esperienza user-friendly sia per chi ha appena iniziato che per i trader più esperti.

144 Totale visualizzazioniPubblicato il 2024.12.11Aggiornato il 2026.06.02

Come comprare ALICE

Discussioni

Benvenuto nella Community HTX. Qui puoi rimanere informato sugli ultimi sviluppi della piattaforma e accedere ad approfondimenti esperti sul mercato. Le opinioni degli utenti sul prezzo di ALICE ALICE sono presentate come di seguito.

活动图片