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25 technologies shown

• GraphRAG technique Retrieval over a knowledge graph built from the corpus.
• Multi-Agent technique Several agents working on a task, with defined roles or handoffs.
• Pretraining technique The initial large-scale training that produces a base model.
• Reranking technique Second-stage ordering of retrieved candidates by a more accurate scoring model.
• Self-Consistency technique Sampling several reasoning paths and taking the majority answer.
• Structured Output technique Constraining a model to emit valid JSON or a schema-conforming object.
• Synthetic Data technique Training examples generated rather than collected.
• Chain of Thought technique Prompting a model to reason step by step before answering.
• DPO technique Aligning a model directly on preference pairs, without training a reward model.
• Query Rewriting technique Reformulating a question before retrieval to improve what comes back.
• Agent Memory technique State an agent keeps beyond the current context window.
• HyDE technique Embedding a generated answer instead of the question.
• Tree of Thoughts technique Searching over intermediate reasoning states instead of one linear chain.
• Quantization technique Storing model weights at lower precision to cut memory and speed up inference.
• Self-RAG technique Model decides for itself when to retrieve and critiques what it retrieved.
• Constitutional AI technique Aligning a model using written principles rather than human labels alone.
• Diffusion technique Generates data by learning to reverse a gradual noising process.
• Guardrails technique Checks around a model's input and output that constrain what it can do.
• Distillation technique Training a small model to reproduce the behaviour of a larger one.
• Red Teaming technique Adversarially probing a model for harmful or unsafe behaviour.
• LoRA technique Fine-tuning by training small low-rank adapter matrices instead of all weights.
• RLAIF technique Reinforcement learning from AI feedback instead of human feedback.
• Jailbreak technique Prompt that circumvents a model's refusal behaviour.
• Tokenization technique Splitting text into the subword units a language model actually reads.
• KV Cache technique Cached attention keys and values that make generating one token at a time affordable.