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
