AI Acronyms
Common abbreviations and short-hands in artificial intelligence.
14 terms
- BM25 Retrieval
A probabilistic term-matching keyword search algorithm widely used in information retrieval.
- Direct Preference Optimization (DPO)
An alignment algorithm that optimizes policy networks directly using pairwise preference data without reward model training.
- Infrastructure as Code (IaC)
Defining cloud infrastructure in version-controlled files instead of console clicks — reviewable, repeatable, and recoverable.
- Inverted File Index (IVF)
A vector search optimization that clusters vector spaces to limit search scopes.
- Kahneman-Tversky Optimization (KTO)
An alignment algorithm that optimizes models using binary utility signals (good/bad) rather than pairwise preferences.
- NormalFloat 4 (NF4)
An information-theoretically optimal quantile quantization data type designed to compress parameters.
- Parameter-Efficient Fine-Tuning (PEFT)
A collection of fine-tuning techniques that adapt pre-trained models by modifying only a tiny fraction of parameters.
- Post-Training Quantization (PTQ)
An offline compression technique that converts weights to lower precision after model training finishes.
- Product Quantization (PQ)
A lossy vector compression technique that reduces database RAM footprints.
- Proximal Policy Optimization (PPO)
An on-policy reinforcement learning algorithm that restricts step updates to maintain training stability.
- QLoRA
A fine-tuning method that backpropagates gradients through frozen, 4-bit quantized base models into LoRA adapters.
- Quantization-Aware Training (QAT)
A training process that models quantization error during the forward pass to minimize precision loss.
- Reinforcement Learning from Human Feedback (RLHF)
The post-training technique that turns a raw next-token predictor into a helpful assistant by optimizing against human preference judgments.
- RLHF Reward Model
A scoring model trained on human feedback to evaluate language model generation quality.