Experience Over Technical Strength in AI Investments

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Investors are focusing too much on the technical strength of individuals when investing in AI, neglecting to inquire about the founders' experience in commercializing businesses, iterating quickly, and creating value. Researchers in renowned companies like DeepMind and Meta may be highly intelligent, but transitioning to successful and profitable businesses requires more than technical prowess. In a rapidly evolving industry like AI, the ability to execute, iterate, and adapt quickly is crucial for long-term success.

Tom Hulme is a Managing Partner of GV (Google Ventures), and leads the European team. Today, GV has over $10BN in AUM and Tom has led investments in Lemonade.com (IPO), Snyk, Secret Escapes, Blockchain.com, GoCardless, Blue Vision Labs (exited to Lyft), and Currency Cloud (exited to Visa). Prior to joining venture full-time, Tom was one of Europe's most successful angel investors with a 5x DPI track record and 20x+ TVPI.

In Today's Episode with Tom Hulme We Discuss:

1. Lessons from a 24x TVPI Angel Track Record:

What are Tom's biggest lessons from his biggest winners angel investing?
What are Tom's biggest takeaways from the 0's in his angel track record?
What is the biggest advice Tom would give to angel investors starting out today?
What are the single biggest mistakes Tom sees angel investors make today?

2. The Four Pillars of Venture Capital:

What does Tom believe are the four key components of being successful as a VC?
Why does Tom describe VC as "being a founder on anti-depressants"?
How does Tom categorise the three different types of investors that exist?
Sourcing, selecting, servicing: What is Tom best at and what is he worst at?

3. The Conventional Wisdom in Venture That is Not True:

Why does Tom believe it is BS that you should never sell your winners?
Why does Tom believe he has never had complete conviction in any of the companies he invests in?
Why does Tom believe the "everything has to be a fund returner mindset" is BS?
Why naivety doesn't lead to great founders? Why employees at rocketships are the best founders?

4. AI: Foundation Models, Generative AI, The Incumbents: Where Does the Value Go:

Does Tom believe there is money to be made investing in foundation models?
Why does Tom liken investing in foundation models to investing in power stations?
Where does Tom believe there is value in the application layer?
Why does Tom think that generative AI is largely a sustaining innovation?
Why does Tom think Microsoft will win the next wave of AI? Who else is well-positioned?
Why does Tom believe there is a correlation between those that fear monger around AGI and those that need funding for their businesses?