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