# MLOps Week 30 - From Recession to Al Boom: Venture Capital Perspectives with Gautam Krishnamurthi

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Text version: https://stenobird.com/podcast/mlops-weekly/mlops-week-30-from-recession-to-al-boom-venture-capital-perspectives-with-gautam-krishnamurthi.md
Podcast: [MLOps Weekly Podcast](https://stenobird.com/podcast/mlops-weekly)
Published: 2024-07-03T22:40:01+00:00
Episode link: https://rss.com/podcasts/mlops-weekly/1555404
Audio file: https://content.rss.com/episodes/132586/1555404/mlops-weekly/2024_07_03_22_38_35_8d279b01-0bda-4b52-8e10-a65115cd8a2b.mp3
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Duration seconds: 1612

## Resource

Venture capitalist Gautam Krishnamurthi analyzes how rising interest rates have stalled the IPO market and created a backlog in growth-stage investing. He explores the distinction between 'efficiency gain' AI startups and high-moat infrastructure plays in the current LLM boom.

## Highlights
- Main idea: High interest rates have created a bottleneck in the public markets, delaying exits and impacting early-stage venture capital deployment
- Failure mode: Startups offering only marginal efficiency gains (e.g., 5x to 6x) are vulnerable to being absorbed by foundational model providers like OpenAI
- Practical takeaway: The most scalable opportunities lie in serving 'data have-nots'—enterprises that need software to act like they have massive engineering teams
- Investment thesis: Real differentiation in the application layer requires building deep moats, potentially through proprietary foundation models
- Strategic insight: Partnering with System Integrators (SIs) provides a critical entry path into large enterprises through established Centers of Excellence

## Topics

Venture Capital, Machine Learning Infrastructure, Large Language Models, Enterprise Software, AI Startups, Economic Trends, Biotech AI, Data Engineering

## Chapters
- 1:05 — The Macro Landscape: An overview of how interest rates and the current economic climate are influencing venture valuations and the broader market.
- 2:50 — The LLM Market Boom: Discussion on the surge of capital flowing into early-stage machine learning and LLM businesses despite broader market volatility.
- 4:55 — The Mobile Wave Parallel: Comparing the current AI explosion to the early mobile era and the resulting low barriers to entry for new startups.
- 6:50 — Scaling Enterprise AI: The importance of building infrastructure that can handle enterprise-scale deployment and increasing user bandwidth.
- 8:55 — Up-leveling the Enterprise: How AI tools can bridge the expertise gap for companies lacking massive internal machine learning manpower.
- 10:45 — Hard Tech and Biotech: Exploring the intersection of AI with complex fields like protein generation and diffusion models.
- 18:45 — Solving Real Problems: Why solving fundamental problems is more important than riding the LLM hype cycle for long-term venture viability.
- 24:35 — The Data Have vs. Have-Nots: Identifying the two primary buyer segments in the ML infrastructure market: tech giants and traditional enterprises.

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