Crypto and AI Need Female Executives

marsbitPublicado em 2026-01-21Última atualização em 2026-01-21

Resumo

Recent growing prominence in the AI industry is the rise of female executives in key operational and commercial roles. Recent examples include CZ Chen, COO of Manus (acquired by Meta for $2 billion), and MiniMax’s 31-year-old COO Yun Yeyi, now worth HK$4.8 billion. Similar trends were observed during crypto’s heyday with leaders like He Yi (Binance), Lisa Loud (BitMEX), and Cynthia Wu (Matrixport). Both AI and crypto share a dual nature: technically cutting-edge yet often led by technical founders who lack strong commercial, narrative, or public-facing skills. Female COOs and CMOs excel as bridges—translating complex technology into market-ready products and building trust through communication and empathy. Figures like Daniela Amodei (Anthropic) and Yun Yeyi have been instrumental in driving commercialization and mass adoption. The migration of such talent signals a sector’s maturation and commercial viability. As AI enters its productization phase, crypto’s failure to attract or retain similar talent may hinder its transition beyond niche technical circles toward mainstream relevance. Where skilled female leaders go, value follows; where they leave, stagnation often remains.

Author: Alice, Shenchao TechFlow

Recently, an interesting phenomenon has been observed in the AI circle: more and more female executives are stepping into the spotlight.

On December 30th, Meta announced it would acquire Manus for $2 billion, bringing 90s-born COO CZ Chen into the public eye. With an undergraduate degree from Shanghai University of Finance and Economics and a master's from Columbia, she started working in 2018, first at Vanke, then at an FA agency, and made her final career move to Manus in 2024, achieving financial freedom directly.

On January 9th, at MiniMax's bell-ringing ceremony, standing alongside the 36-year-old founder Yan Junjie was a woman born in 1994, Yun Yeyi.

This 31-year-old COO now has a net worth of HKD 4.8 billion.

What is Yun Yeyi's background?

She studied electronic engineering at Johns Hopkins University, with minors in economics and mathematics. After graduating in 2017, she joined SenseTime, rising from financing manager to assistant to CEO Xu Li, and then to director of the innovation business department, experiencing SenseTime's journey from unicorn to listing on the Hong Kong stock exchange.

In 2022, when Yan Junjie decided to leave SenseTime to found MiniMax, Yun Yeyi followed almost without hesitation.

Her value goes beyond just following.

MiniMax's prospectus shows that Yun Yeyi handles almost everything outside of technical R&D: product, commercialization, board matters, operations, management... Her annual salary is $1.479 million, more than all other executive directors combined, a figure that speaks volumes.

It's not just in China; globally, the influence of women in the AI circle is undeniable.

Daniela Amodei, with a background in English literature, after working at Stripe and OpenAI, co-founded Anthropic with her brother Dario in 2021, serving as president, focusing on daily operations and commercialization, driving the marketization of Claude products.

Lila Ibrahim, former Intel executive, joined DeepMind in 2018 as its first COO, responsible for daily operations, partnerships, social impact, external affairs, and government relations.

Mira Murati, the Albanian-born former CTO of OpenAI, came to the U.S. on a scholarship at 16, moved from the Model X team at Tesla to OpenAI, and eventually left to found Thinking Machines Lab, valued at $9 billion...

This scene feels familiar.

From 2017 to 2021, during the golden age of crypto, a dazzling array of stars emerged, including a prominent presence of female CMOs and COOs.

The most well-known is undoubtedly Binance co-founder and CMO He Yi (now co-CEO). From Shanghai to Tokyo, then from Malta to Paris and Dubai, she was present at every strategic shift, helping the company become the world's largest cryptocurrency exchange.

Lisa Loud, from Apple engineer to PayPal's Canadian market head, jumped to BitMEX as CMO in 2017. Subsequently, BitMEX once became the world's largest crypto trading platform for derivatives.

Cynthia Wu, COO of Matrixport, former vice president of product development at HKEX, brought traditional finance experience to crypto financial services, helping the company become one of Asia's largest digital asset service platforms.

......

Back then, crypto was the world's asset focus, and the spotlight naturally fell on these female executives at the center of the stage.

But the tide receded, and the protagonists changed.

Now, AI is the focus of the spotlight, so we see Daniela Amodei on the Forbes rich list, and Yun Yeyi radiant at MiniMax's listing ceremony.

Fundamentally, Crypto and AI are strikingly similar: "both cutting-edge and rudimentary."

Cutting-edge is reflected in the technology itself: blockchain reconstructs trust mechanisms, AI reconstructs productivity—both are underlying technologies that can change the world.

Rudimentary is reflected in the founder profile: mostly technical backgrounds, fluent in code, but unfamiliar with marketing, especially government and public relations.

This is the value of female COOs/CMOs. They are the bridge between technical geniuses and the external world, capable of deep dialogue with technical teams and telling compelling stories to investors and users.

Daniela Amodei translated AI safety philosophy into executable business strategies, allowing Claude to break through in the shadow of ChatGPT; Yun Yeyi brought MiniMax from the lab to the C-end market; He Yi long served as the chief customer officer, personally answering user questions and building trust.

When a product moves beyond the pure technical stage and increasingly needs to face the C-end, the advantages of female executives become more apparent.

After all, PR and product require not a confrontational mindset, but empathy.

From another perspective, capable female executives vote with their feet. They go where they can utilize their talents and create value. If they start leaving an industry, it indicates the disappearance of commercial certainty in that industry.

The problem in the crypto industry is obvious now: a lack of talent who can translate technology into products accepted by the masses. Mass adoption and positive externalities remain empty talk. Observing any emerging industry reveals this pattern: when female executives with technical understanding, business acumen, and narrative skills begin to rise, the industry truly shifts from technology-driven to commercialization and mass adoption.

Their emergence marks the true maturity of an industry.

The AI circle has already undergone this transition. Female executives like Daniela Amodei and Yun Yeyi are driving productization, moving AI from lab algorithms into daily life and the business world.

As for the crypto industry, if it can't retain "elites who can speak human language," then it deserves to remain stuck in the mud of PVP.

The flow of talent is the风向标 (wind vane) of the industry.

Where they go, value is created; where they leave, bubbles often burst.

Perguntas relacionadas

QWhat is the trend observed in the AI industry regarding female executives, as mentioned in the article?

AThe article notes that more female executives are stepping into the spotlight in the AI industry, taking on key roles such as COO and CMO, and driving commercialization and productization of AI technologies.

QWho is Yun Yeyi, and what is her role and significance at MiniMax?

AYun Yeyi is the 31-year-old COO of MiniMax, with a background from Johns Hopkins University and experience at SenseTime. She handles almost all non-R&D aspects of the company, including product, commercialization, and operations, with an annual salary of $1.479 million, reflecting her critical role in the company's success.

QHow does the article compare the roles of female executives in Crypto and AI industries?

AThe article highlights that both Crypto and AI industries have seen prominent female COOs and CMOs who act as bridges between technical teams and the external world. They excel in marketing, government relations, and storytelling, which are essential for turning complex technologies into widely accepted products.

QWhat common characteristics do Crypto and AI share, according to the article?

ACrypto and AI are both described as 'cutting-edge yet rustic.' They are cutting-edge in terms of technology (blockchain redefining trust mechanisms and AI redefining productivity), but rustic in that founders are often technical experts who lack skills in marketing and external relations.

QWhat does the article suggest about the importance of female executives for industry maturity?

AThe article suggests that the rise of female executives with technical understanding, business acumen, and narrative ability marks an industry's transition from technology-driven to commercialization and mass adoption. Their presence indicates true industry maturity, while their departure may signal a decline in commercial certainty.

Leituras Relacionadas

Has the 'Digital Gold' Narrative for BTC Failed?

**Title: Has the "Digital Gold" Narrative for Bitcoin Failed?** The article argues that Bitcoin's "digital gold" narrative remains valid despite a recent sharp price decline (from a peak near $126k in Oct 2025 to briefly under $61k in Feb 2026). It presents a long-term investment framework based on three core points: **1. Viewing Bitcoin as an Asset:** Bitcoin is presented as a superior potential store of value compared to gold. Key arguments are its absolute scarcity (21 million cap), superior portability, and transparent auditability via its public ledger. While acknowledging its current use in early, volatile stages (~3-4% global adoption), the author draws parallels to the early, disruptive phases of the internet and e-commerce. **2. Understanding the Recent Downturn:** The current ~50% correction is framed as a predictable, consensus-driven cycle following its post-halving peak (the 2024 halving preceded the Oct 2025 high). A crucial factor is a historic "changing of hands": the influx of new institutional buyers via ETFs allowed early, low-cost holders (miners, OG believers) to take profits. The author notes that while severe, Bitcoin's historical drawdowns (e.g., 93% in 2011, 77% in 2021-22) have been progressively smaller, suggesting maturing holder structure and decreasing volatility over time. **3. The Long-Term Perspective:** The long-term thesis hinges on Bitcoin capturing a portion of gold's market value. With Bitcoin's market cap at ~$1.4 trillion (at $70k) versus gold's ~$20 trillion, significant upside potential exists if the "digital gold" narrative is partially realized. However, the author strongly cautions that short-term risks remain, the bottom is unpredictable, and high volatility is inherent. The real risk is not Bitcoin failing but poor personal position management (over-leverage, wrong capital) and a lack of deep understanding, which can force investors out during severe downturns. The conclusion uses Amazon's 95% crash post-2000 dot-com bubble and subsequent 42x recovery as an analogy. The ultimate question is not if Bitcoin's price will rise, but if an investor's strategy and conviction can withstand the volatility to see the long-term play out. The recent divergence (gold up, Bitcoin down) is posed not as a narrative failure, but as potential evidence of this ongoing, painful transition from a speculative asset to a mainstream allocation.

marsbitHá 5h

Has the 'Digital Gold' Narrative for BTC Failed?

marsbitHá 5h

Has BTC's 'Digital Gold' Narrative Failed?

The article discusses Bitcoin's "digital gold" narrative, its recent price drop, and long-term outlook through the perspective of "Jason". It argues the narrative is not a failure but that Bitcoin represents a superior, new asset class due to its fixed supply (21 million), portability, and auditability. The piece compares its current ~3-4% global adoption rate to early internet/e-commerce, suggesting significant growth potential. Regarding the 2025-2026 price decline (from ~$126k to briefly under $61k), the author views it as a predictable, consensus-driven sell-off within Bitcoin's ~4-year cycle post-halving, exacerbated by a major "handover" from early, low-cost holders to new institutional buyers via ETFs. A key observation is that historical peak-to-trough drawdowns have lessened over time (e.g., 93% in 2011 to ~50% in 2026), indicating maturing volatility as holder structure changes. For the long term, the author uses a simple framework: Bitcoin's total market cap (~$1.4T at $70k) is only about 7% of gold's (~$20T). Even capturing 30-50% of gold's value would imply substantial upside. However, the article strongly cautions against viewing this as investment advice, emphasizing extreme volatility and the critical importance of risk management, position sizing, and deep fundamental understanding to survive severe drawdowns. It concludes by drawing a parallel to Amazon's 95% crash in 2000 and subsequent 42x recovery, stressing that the key is surviving market cycles to realize long-term potential.

链捕手Há 5h

Has BTC's 'Digital Gold' Narrative Failed?

链捕手Há 5h

From Code to Cognition: A Ten-Thousand-Word Guide to the Evolution of the Robot Brain

"From Code to Cognition: The Evolution of Robot Brains" The journey of robotic intelligence has shifted dramatically from manually coded systems to AI-driven brains. For decades, robots relied on layered software stacks—perception, state estimation, planning, control—each handcrafted. While predictable, they lacked adaptability. The 2010s saw deep learning revolutionize perception (e.g., object detection) and control (via reinforcement learning), but learned skills remained narrow. The arrival of Large Language Models (LLMs) marked a turning point. LLMs acted as high-level planners, interpreting natural language instructions and generating sequences of actions for traditional robotic systems to execute. However, true integration came with Visual-Language-Action (VLA) models, which fused vision, language, and motion prediction into a single network. Pioneered by models like RT-2 and open-source projects like OpenVLA, VLAs enable robots to reason and act directly from visual input and commands. The most advanced humanoid robots now employ a "dual-brain" architecture: a slow-thinking, large VLA (System 2) for reasoning and planning, and a fast-reacting, small network (System 1) for high-frequency motion control, sometimes with an even lower-level System 0 for balance. This split balances cognition with the physics of real-time movement. Computation is split between onboard hardware (e.g., NVIDIA Jetson) for safety-critical control loops and cloud/edge servers for non-critical tasks like learning and interfaces. A crucial driver is the open-source ecosystem—models like GR00T and OpenVLA allow startups to build upon pre-trained brains and fine-tune them with their own data, accelerating development. Despite progress, current systems struggle with recovery from errors, sample inefficiency, and long-horizon tasks. This has spurred the rise of **World Models**—neural networks that predict the consequences of actions. By simulating possible futures before acting (like NVIDIA Cosmos or Meta V-JEPA), robots can plan, recover, and generalize better. This represents the next frontier: shifting intelligence from learned reactions to an internal model of physics and cause-and-effect. The field is rapidly evolving. While not yet at its "ChatGPT moment," the convergence of cheaper hardware, scalable simulation, and world models points toward robots that are increasingly capable, adaptive, and useful. The question is shifting from "what can robots do?" to "what *should* they do?"

marsbitHá 5h

From Code to Cognition: A Ten-Thousand-Word Guide to the Evolution of the Robot Brain

marsbitHá 5h

Trading

Spot
Futuros

Artigos em Destaque

Como comprar ALICE

Bem-vindo à HTX.com!Tornámos a compra de My Neighbor Alice (ALICE) simples e conveniente.Segue o nosso guia passo a passo para iniciar a tua jornada no mundo das criptos.Passo 1: cria a tua conta HTXUtiliza o teu e-mail ou número de telefone para te inscreveres numa conta gratuita na HTX.Desfruta de um processo de inscrição sem complicações e desbloqueia todas as funcionalidades.Obter a minha contaPasso 2: vai para Comprar Cripto e escolhe o teu método de pagamentoCartão de crédito/débito: usa o teu visa ou mastercard para comprar My Neighbor Alice (ALICE) instantaneamente.Saldo: usa os fundos da tua conta HTX para transacionar sem problemas.Terceiros: adicionamos métodos de pagamento populares, como Google Pay e Apple Pay, para aumentar a conveniência.P2P: transaciona diretamente com outros utilizadores na HTX.Mercado de balcão (OTC): oferecemos serviços personalizados e taxas de câmbio competitivas para os traders.Passo 3: armazena teu My Neighbor Alice (ALICE)Depois de comprar o teu My Neighbor Alice (ALICE), armazena-o na tua conta HTX.Alternativamente, podes enviá-lo para outro lugar através de transferência blockchain ou usá-lo para transacionar outras criptomoedas.Passo 4: transaciona My Neighbor Alice (ALICE)Transaciona facilmente My Neighbor Alice (ALICE) no mercado à vista da HTX.Acede simplesmente à tua conta, seleciona o teu par de trading, executa as tuas transações e monitoriza em tempo real.Oferecemos uma experiência de fácil utilização tanto para principiantes como para traders experientes.

159 Visualizações TotaisPublicado em {updateTime}Atualizado em 2026.06.02

Como comprar ALICE

Discussões

Bem-vindo à Comunidade HTX. Aqui, pode manter-se informado sobre os mais recentes desenvolvimentos da plataforma e obter acesso a análises profissionais de mercado. As opiniões dos utilizadores sobre o preço de ALICE (ALICE) são apresentadas abaixo.

活动图片