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The Twenty Minute VC (20VC): Venture Capital | Startup Funding | The Pitch

The Twenty Minute VC (20VC) interviews the world's greatest venture capitalists with prior guests including Sequoia's Doug Leone and Benchmark's Bill Gurley. Once per week, 20VC Host, Harry Stebbings is also joined by one of the great founders of our time with prior founder episodes from Spotify's Daniel Ek, Linkedin's Reid Hoffman, and Snowflake's Frank Slootman. If you would like to see more of The Twenty Minute VC (20VC), head to www.20vc.com for more information on the podcast, show notes, resources and more.
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Now displaying: Page 1
Sep 22, 2023

Christian Kleinerman is the SVP of Product @ Snowflake. Before Snowflake, Christian spent close to 5 years at Google as a Senior Director of Product Management @ YouTube working on their infrastructure and data systems. Before YouTube, Christian spent over 13 years at Microsoft serving as General Manager of the Data Warehousing product unit where he was responsible for a broad portfolio of products.

In Today's Episode with Christian Kleinerman We Discuss:

1. Lessons from the Greats:

  • How did Christian first make his way into the world of product?
  • What are 1-2 of his biggest lessons from working with Satya Nadella and Frank Slootman?
  • What are 1-2 of hs biggest product lessons from Google and Microsoft?

2. Generative AI: Real vs Fake:

  • How does Christian analyze the current generative AI landscape?
  • Which segments will be the fastest to adopt? Which will be the slowest?
  • What aspects of the ecosystems are overblown? Which are under-appreciated?
  • How does Christian respond to many VCs who suggest that many startups are simply wrappers on GPT?

3. Models 101: Why Size is Not Everything!

  • What matters more, the size of the data or the size of the model?
  • Will any of the models used today be used in a year?
  • Does Christian believe Alex @ Nabla is right in saying that "the most successful companies will be those that are able to transition between models the easiest"?
  • How are we seeing the evolution of model size impact the accuracy of result snad size of data required?

4. Incumbent vs startup & Open vs Closed:

  • Who is best positioned to win; startups or incumbents?
  • What are the nuances; which spaces are best served for startups to win vs incumbents?
  • Will open or closed source be the dominant mode?
  • What are the single biggest challenges preventing open from being successful?

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