LLM, or large language model, is a program designed to understand and generate human language. It uses deep learning techniques to analyze text data and learn patterns and structures of language. LLMs make predictions on next words and phrases based on previous input. Specifically, when using chat GPT, it predicts what words and phrases should come next based on what has been typed before.
How do you build defensible business value in an era when, as AngelList CEO Avlok Kohli said on our last ACQ2 episode, the “cost of intelligence is going to zero”? Longtime friend of the show Jake Saper and his partners at Emergence Capital have been refining their thesis for this brave new world of Generative AI in B2B, and we sit down with him to discuss. We cover topics including:
- When do exactly correct answers matter, and when do they not?
- When are human-in-the-loop systems necessary?
- When do startups have an advantage vs. incumbents, and vice-versa?
- Where can companies capture value on a durable basis?
- When do you need proprietary data in order to be defensible?
Whether you’re building or investing in existing businesses from the “pre-AI” era or brand new startups that are native to GPT, this episode has plenty of takeaways you should consider. Tune in!
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