LoRA Adapter
Product term: LoRA
Category: infrastructure
Definition
Low-Rank Adaptation: a lightweight AI fine-tuning technique that personalizes Digital Twins without requiring massive compute. Instead of retraining a full model, LoRA adapts specific weights based on your Cognitive Transcripts. Efficient, cheap, and personal.
Key Points
- •Efficient AI personalization method
- •Lightweight fine-tuning
- •Based on your Cognitive Transcripts
- •Creates personalized model layers
- •Cheap to compute
- •Enables widespread Twin deployment
Frequently Asked Questions
Is LoRA a technical term?
Yes, but you don't need to know it. It just means your Twin is efficiently personalized to you.
How does LoRA work?
Instead of retraining a giant model, LoRA adjusts specific internal weights. Like adjusting a few dials instead of rebuilding a machine.
How is LoRA personalization different from just "prompting"?
Much deeper. Prompting changes outputs; LoRA changes how the model thinks. Your Twin becomes truly personal.
Can I see my LoRA adapter?
Not really—it's internal weights. But you can see its effects: your Twin's decisions and recommendations.
Related Terms
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