BRICS AI Economics

Tag: LoRA

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Mar, 12 2026

Parameter-Efficient Generative AI: LoRA, Adapters, and Prompt Tuning at Scale

Emily Fies
0
LoRA, adapters, and prompt tuning let you adapt massive AI models without retraining them fully. These methods cut costs by 90%+, making fine-tuning possible on consumer hardware. Learn how they work, how they compare, and which one to choose.
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Mar, 2 2026

Benchmark Transfer After Fine-Tuning: How LLMs Keep Their General Skills When Learning New Tasks

Emily Fies
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Fine-tuning LLMs for specific tasks can erase their general knowledge. Learn how benchmark transfer ensures models stay smart across all tasks - not just the one you trained them for.

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    NLP Pipelines vs End-to-End LLMs: When to Use Traditional Processing vs Prompting

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    Real-Time Multimodal Assistants Powered by Large Language Models: What They Can Do Today

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    Cost Management for Large Language Models: Pricing Models and Token Budgets

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    Parameter-Efficient Generative AI: LoRA, Adapters, and Prompt Tuning at Scale

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    How Synthetic Data Generation Protects Privacy in LLM Training

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