# MLOps Week 18: The LLM Revolution & the Future of Data with Josh Wills

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Text version: https://stenobird.com/podcast/mlops-weekly/mlops-week-18-the-llm-revolution-the-future-of-data-with-josh-wills.md
Podcast: [MLOps Weekly Podcast](https://stenobird.com/podcast/mlops-weekly)
Published: 2023-05-24T15:37:13+00:00
Episode link: https://rss.com/podcasts/mlops-weekly/966178
Audio file: https://content.rss.com/episodes/132586/966178/mlops-weekly/2023_05_24_15_36_48_de6a6a90-4335-4dff-a632-ca6d985881f9.mp3
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Duration seconds: 2773

## Resource

Josh Wills shares lessons from scaling data pipelines at Slack and Google, focusing on the necessity of data contracts. The discussion explores whether LLMs represent a fundamental shift like electricity or a functional shift like the mobile phone.

## Highlights
- Main idea: Data contracts are essential for decoupling production systems from downstream data warehouses
- Practical takeaway: Treat data pipelines as production-grade software by implementing integration tests between upstream and downstream systems
- Failure mode: Over-identifying with source code can lead to professional burnout and resistance to necessary code reviews
- Main idea: The future of LLMs likely depends on whether the economics favor a single dominant model or a fragmented ecosystem of specialized models
- Practical takeaway: In high-scale environments, prepare for 'one-in-a-trillion' edge cases that become frequent when processing trillions of records

## Topics

Data Engineering, LLMs, Data Contracts, MLOps, Scalable Systems, Data Warehousing, Artificial Intelligence, GPU Scarcity

## Chapters
- 1:00 — The Mount Everest of Data Engineering: Reflecting on the technical and human challenges of rebuilding Slack's massive search indexing pipeline.
- 4:20 — Implementing Data Contracts: How using Thrift schemas to tie production systems to the data warehouse prevents downstream breakage.
- 18:20 — The Hype Cycle of LLMs: Evaluating whether Large Language Models are a paradigm shift akin to the mobile phone or the invention of electricity.
- 21:45 — Lessons from Google and Go: A look at the adoption of the Go programming language and the importance of tools fitting the community's needs.
- 25:25 — The Middle Ground of AI Hype: Navigating the space between extreme skepticism and the 'electricity-level' hype of generative AI.
- 35:40 — The Economics of Model Training: Discussing the scarcity of GPUs and the business incentives for platforms like Databricks to support decentralized model training.

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## Transcript

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