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Model Context Protocol (MCP)
Model Context Protocol (MCP) is a standard that lets LLM apps and agents connect to external context and…
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Tree-of-Thought (ToT)
Tree-of-Thought structures reasoning as a search over branching steps. An LLM expands candidate thoughts, a controller scores and…
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Constitutional AI
Constitutional AI aligns models to an explicit set of principles, enabling self‑critique and revision (and optionally AI feedback)…
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Vector Database
A vector database indexes high‑dimensional embeddings for fast similarity search with metadata filters and hybrid retrieval—foundational for RAG,…
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Speculative Decoding
Speculative decoding speeds up LLM inference by letting a fast draft model propose tokens that a larger model…
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Vision-Language Model (VLM)
A Vision-Language Model (VLM) jointly learns from images and text to understand and generate multimodal content, enabling captioning,…
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Model Quantization
Model quantization reduces precision (e.g., INT8/INT4) for weights and activations to shrink memory and speed inference, enabling cheaper,…
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Prompt Injection
Prompt injection is an attack where malicious text in prompts or retrieved content hijacks an LLM or agent,…
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Mixture of Experts (MoE)
Mixture of Experts (MoE) scales model capacity by routing each token to a small subset of expert networks,…
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Key-Value Cache (KV Cache)
A KV cache stores past attention keys/values so LLMs reuse them at each step, cutting latency, enabling continuous…
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Model Context Protocol (MCP)
Model Context Protocol (MCP) is a standard that lets LLM apps and agents connect to external context and…
-
Tree-of-Thought (ToT)
Tree-of-Thought structures reasoning as a search over branching steps. An LLM expands candidate thoughts, a controller scores and…
-
Constitutional AI
Constitutional AI aligns models to an explicit set of principles, enabling self‑critique and revision (and optionally AI feedback)…
-
Vector Database
A vector database indexes high‑dimensional embeddings for fast similarity search with metadata filters and hybrid retrieval—foundational for RAG,…
-
Speculative Decoding
Speculative decoding speeds up LLM inference by letting a fast draft model propose tokens that a larger model…
-
Vision-Language Model (VLM)
A Vision-Language Model (VLM) jointly learns from images and text to understand and generate multimodal content, enabling captioning,…
-
Model Quantization
Model quantization reduces precision (e.g., INT8/INT4) for weights and activations to shrink memory and speed inference, enabling cheaper,…
-
Prompt Injection
Prompt injection is an attack where malicious text in prompts or retrieved content hijacks an LLM or agent,…
-
Mixture of Experts (MoE)
Mixture of Experts (MoE) scales model capacity by routing each token to a small subset of expert networks,…
-
Key-Value Cache (KV Cache)
A KV cache stores past attention keys/values so LLMs reuse them at each step, cutting latency, enabling continuous…