What factor matters most when investing in AI infrastructure?

Most answers emphasize technical strength, efficiency, or depth as key factors, while one prioritizes applications and another highlights energy as a critical bottleneck.

5 answers

Answers

  • Emily Man

    Partner · Primary Venture Partners

    Applications

    Emily Man says she focuses a lot more on the applications—the last level of the stack—rather than the chips, infrastructure, and models.

    Run the Numbers with CJ Gustafson · Watch on YouTube

  • Sam Altman

    Chief Executive Officer · OpenAI

    Compute Efficiency

    Sam Altman says he prioritizes compute efficiency because the most important thing is to create smart models and run them efficiently and abundantly for many people, and if that is right everything else will follow.

    David Senra · David Senra · Listen at 10:07

  • Eric Vishria

    General Partner · Benchmark

    Energy

    Eric Vishria says he worries about energy: models translate compute into intelligence, demand for intelligence seems large, and compute needs lots of energy, which he calls the bottleneck.

    Invest Like The Best · Watch on YouTube

  • Sunil Dhaliwal

    Founder and General Partner · Amplify Partners

    Technical Strength

    Sunil Dhaliwal says he prioritizes technical strength and differentiation, because in hard infrastructure domains the technology really matters.

    N/A · N/A · Listen at 11:33

  • Navin Chaddha

    Managing Partner · Mayfield Fund

    Technical Depth

    Navin Chaddha says technical depth matters because these are hard products with high technical risk—only a few teams can build CPUs, GPUs or optics.

    The Peel with Turner Novak · The Peel with Turner Novak · Listen at 43:42

More Venture Capital questions

View all →