Overview of Understanding Hyperscalers: Masters in Business with Ankur Crawford
This episode of Masters in Business features Ankur Crawford, portfolio manager at Alger, in a wide-ranging conversation about her unusual path from engineering and semiconductor research to growth investing, and why her technical background gives her an edge in analyzing AI, semiconductors, hyperscalers, and software. The discussion centers on her investing philosophy of finding “change” rather than just growth, how AI is reshaping the economics of software and infrastructure, and why she believes the current AI cycle is still early rather than bubble-like.
Key Themes and Main Takeaways
Technical expertise as an investing advantage
Crawford argues that understanding the underlying technology is crucial in today’s market, especially in AI and semiconductors.
- Her background at Intel, including patents and doctoral work in materials science, helps her understand chip manufacturing, tooling, and technical bottlenecks.
- She believes many investors are “loose holders” of AI stocks because they don’t understand the technology well enough.
- Her technical fluency helped her identify long-term shifts early, such as the end of Moore’s law.
Growth investing at Alger = finding change
A major theme is that Alger’s style is less about screening for fast growers and more about identifying meaningful change.
- Alger looks for companies undergoing:
- High unit volume growth
- Life cycle change
- The firm often invests early in an S-curve transformation, when a company is reaccelerating or reinventing itself.
- Crawford emphasized that some companies that appear “value-like” are actually misunderstood growth stories.
AI is changing where value accrues
Crawford’s core AI thesis: when software starts writing software, the cost to create software falls dramatically, changing the profit pool across the industry.
- AI increases the speed and scale of software creation.
- That lowers barriers and makes software more competitive.
- She believes value shifts away from software and IT services and toward hardware, networking, chips, and data-center infrastructure.
- She sees the current AI cycle as real revenue, real demand, and real profits—not just “clicks and eyeballs” like the dot-com era.
Hyperscaler demand still looks insatiable
Crawford is bullish on compute demand and says the market is still constrained by supply, not demand.
- Hyperscalers are still short on:
- chips
- power
- data-center capacity
- skilled labor such as electricians and plumbers
- She thinks supply constraints are actually preventing the market from overbuilding too quickly.
- In her view, fears of immediate oversupply are premature.
Open-source models don’t eliminate the need for frontier models
She addressed concerns that Chinese open models or more efficient AI systems will reduce the need for massive capital spending.
- Her view: open models often distill from frontier models rather than replace them.
- She believes frontier model training still requires major CapEx.
- The real spend is increasingly driven by inference, which is what end users experience.
Career Journey and Personal Background
From engineering to investing
Crawford’s path was unconventional and, by her own admission, not fully planned.
- Studied mechanical engineering and materials science at UC Berkeley and Stanford
- Considered becoming an astronaut as a child
- Worked at Intel and earned patents
- Eventually answered a recruiting ad at Alger, despite knowing very little about investing
Why she left science
She explained that she achieved her academic goals but still felt unfulfilled.
- She realized that accomplishment alone did not equal happiness.
- The narrowness and isolation of research work also pushed her to look elsewhere.
- Alger initially seemed like a temporary stop, but she stayed and built a long career there.
The value of a global upbringing
She described her international childhood—Kansas, Florida, the Middle East, the Himalayas, Buffalo—as shaping how she evaluates people and businesses.
- She is more attentive to cultural differences in management style
- She does not mistake humility or understatement for weakness
- She has learned to separate tone from business fundamentals
Investing Philosophy in Practice
What she looks for in companies
Crawford focuses on businesses with large opportunity sets and clear earnings compounding.
- Strong growth potential
- Large total addressable markets
- A catalyst for change
- Management teams willing to adapt
When she sells
A sale can happen for several reasons:
- A better opportunity emerges
- The thesis stops working
- Valuation gets ahead of fundamentals
- Another name offers higher upside with lower risk
Learning from mistakes
She emphasized the importance of scars and experience in investing.
- Mistakes become durable lessons
- Real-world accountability matters more than classroom theory
- She keeps a personal record of lessons learned from earlier in her career
The Alger Concentrated Equity ETF
Crawford also discussed the Alger Concentrated Equity ETF (ticker: CNEQ).
Portfolio construction
- Holds about 20 to 30 stocks
- Fully transparent and actively managed
- Focuses on the best businesses with strong change-driven upside
Position sizing
- Determined by risk/reward
- Larger positions go to names with stronger conviction
- Example mentioned: NVIDIA was a large weight, while smaller positions were held in earlier-stage names like Figure Technologies
Advice and Personal Favorites
Career advice for students
Her advice to new graduates:
- Do work you genuinely love
- Be open to changing direction
- Don’t stay on a path just because it was your original plan
- A fulfilling career is more likely when you allow yourself to evolve
Books she recommends
- Think Again by Adam Grant
- A favorite because it emphasizes humility, flexibility, and the ability to revise your thinking
- How to Make a Few More Billion by Brad Jacobs
- She admired its focus on discipline and centering oneself
Podcasts she listens to
- Macro Voices
- The Knowledge Project
- The Circuit
- Education and semiconductor-focused conversations were also mentioned as favorites
Notable Insights
- “When software begins to write software, innovation becomes exponential.”
- Change, not just growth, is the real signal in her investing framework.
- AI’s biggest long-term impact may be on health care and education, not just tech margins.
- She believes AI can help make health care more affordable and education more accessible globally.
- Her view on the AI cycle is broadly optimistic: the risks are real, but the underlying demand and value creation are also real.
Bottom Line
This conversation presents Ankur Crawford as a technically sophisticated, change-oriented growth investor who sees AI as a structural shift rather than a passing trade. Her core message is that investors should look beyond headlines and understand where innovation is actually creating value—especially in chips, infrastructure, and new applications in sectors like health care and education.