Nathan and Erik chat OpenAI GPT-3.5 fine tuning updates, using GPT 4 outputs to fine-tune 3.5, when to accelerate, and AI bundles. If you're looking for an ERP platform, check out our sponsor, NetSuite: http://netsuite.com/cognitive

We're hiring across the board at Turpentine and for Erik's personal team on other projects he's incubating. He's hiring a Chief of Staff, EA, Head of Special Projects, Investment Associate, and more. For a list of JDs, check out: eriktorenberg.com.

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TIMESTAMPS:

(00:00) - Intro and GPT-3.5 fine tuning update

(05:50) - Using GPT-4 to generate training data for GPT-3.5 

(09:54) - Potential for training models on synthetic/cleaned data 

(10:24) - Using chain of thought prompts to improve model performance 

(15:02) - Sponsors: Netsuite | Omneky

(19:39) - Accelerating applications vs new AI models 

(20:40) - What to accelerate vs what to slow down

(26:07) - AI as a co-pilot vs fully automating tasks 

(30:12) - When to delegate to AI

(36:40)- Displacement of human roles by AI systems

(40:39) - Does training on synthetic data solve a problem?

(45:10) - The idea of an AI bundle/subscription 

(50:28) - Bundling in other industries like cable and SaaS

(54:27) - Churn and retention challenges for AI apps 

(01:02:54) - Low retention for easy-to-use AI apps

(01:03:57) - Incentives for AI companies to join a bundle

(01:04:39) - Potential for collaboration between AI companies 

(01:12:01) - Leading AI firms creating separate bundles

(01:16:43) - Outro