Main Takeaway: State-of-the-art foundation models are often seen as black boxes: we send a prompt in and we get out our - often useful - answer. Most people think there are two ways to control an AI: write a better prompt, or fine-tune it on more data.
Steering Vectors Tailor Llms Without Training Part Ii Code Interpretability Series - Overview
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State-of-the-art foundation models are often seen as black boxes: we send a prompt in and we get out our - often useful - answer. Most people think there are two ways to control an AI: write a better prompt, or fine-tune it on more data. In this AI Research Roundup episode, Alex discusses the paper: 'Manifold
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- State-of-the-art foundation models are often seen as black boxes: we send a prompt in and we get out our - often useful - answer.
- Most people think there are two ways to control an AI: write a better prompt, or fine-tune it on more data.
- In this AI Research Roundup episode, Alex discusses the paper: 'Manifold
- In this AI Research Roundup episode, Alex discusses the paper: 'Persona
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