Published Sep 11, 2024
Futures of the data foundry business model
Nathan Lambert delves into the intricate challenges and future trends of the data foundry business model, focusing on data acquisition, market dynamics, and the critical role of high-quality data for AI training and utilization.

Topics covered
Popular Clips
Questions from this episode
- Asked by 96 people
- Asked by 35 people
- Asked by 24 people
- Asked by 13 people
- Asked by 10 people
- Asked by 4 people
- Asked by 2 people
- Asked by 2 people
- Asked by 1 person
Episode Highlights
Related Episodes


A recipe for frontier model post-training
Answers 383 questions
We aren't running out of training data, we are running out of open training data
Answers 383 questions
A realistic path to robotic foundation models
Answers 383 questions
Frontiers in synthetic data
Answers 383 questions

On the current definitions of open-source AI and the state of the data commons
Answers 383 questions
Alignment-as-a-Service: Scale AI vs. the new guys
Answers 383 questions
Interconnects year in review: 2023
Answers 383 questions
Llama 3.2 Vision and Molmo: Foundations for the multimodal open-source ecosystem
Answers 383 questions
DBRX: The new best open LLM and Databricks' ML strategy
Answers 383 questions
OpenAI's Model (behavior) Spec, RLHF transparency, and personalization questions
Answers 383 questions
Model merging lessons in The Waifu Research Department
Answers 383 questions
OLMoE and the hidden simplicity in training better foundation models
Answers 383 questions

A post-training approach to AI regulation with Model Specs
Answers 383 questions
