Eric Vishria: Where is the Value in AI - Chips, Models or Apps? | E1206
66Eric Vishria is a General Partner @ Benchmark Capital, one of the world’s leading venture firms. At Benchmark, Eric has served on over 10 boards including Confluent (CFLT), Amplitude (AMPL), Benchling, Contentful, Cerebras and several other private companies. Prior to joining Benchmark, Eric was the Co‐Founder and CEO of RockMelt, acquired by Yahoo in 2013.
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Timestamps:
(00:00) Intro
(01:00) Reflecting on CEOship at RockMelt
(12:48) The Impact of AI on Markets
(22:21) Does AI Enhance Revenue or Erode Margins for Companies?
(25:13) Analyzing Revenue Quality: Sugar High vs. Sustainable Revenue
(30:36) Value in the Stack: Compute vs. Models
(39:43) Are We Overestimating AI's Impact in the Short Term?
(48:54) Does a $3M Gross Margin Matter in the Long Run?
(51:14) Balancing Time Across Sourcing, Diligence, and Servicing
(55:42) Takeaways from Working with Bill Gurley, Peter Fenton & Matt Cohler
(01:00:07) Quick-Fire Round
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In Today’s Episode with Eric Vishria We Discuss:
1. How to Make Money Investing in AI Today:
How does Eric think through where value will accrue in the stack between chips, models and applications?
Why does Eric believe foundation models are the fastest commoditising asset in history?
Why does Eric believe that Nvidia will not be the only game in town in the next 3-5 years?
2. How to Invest in AI Application Layer Successfully:
How does Eric analyse between a standalone and deep product vs a product that a foundation model will commodities and incorporate into their feature set?
How does Eric differentiate between the 10 different players all going after customer service, or sales tools or data analyst products etc?
How does Eric analyse the quality of revenue of these AI application layer companies? What does he mean when he describes their revenue as “sugar high”?
3. How the Best VC Firm Makes Decisions:
What is the decision-making process for all new deals in Benchmark?
As specifically as possible, how does the voting process inside Benchmark work?
What deal was the most contentious deal that went through? What did the partnership learn?
How has the Benchmark decision-making process changed over 10 years?
4. Does AI Break Venture Models:
Does the price of AI deals and size of their rounds break the Benchmark model?
Will foundation model companies all be acquired by the larger cloud providers?
Unless multiples reflate in the public markets, does venture as an asset class have hope?
Why does AI make paying ludicrously high prices potentially rational?
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