The AI terms that
actually matter.
Clear, technical definitions of 110 key concepts — written by AI engineers, not marketers.
Speaker Diarization Models
AI models designed to partition an audio stream into homogeneous segments according to the speaker identity, effectively answering the question 'who spoke when'.
Read definitionSpeculative Decoding
Speculative decoding accelerates LLM inference by having a small, cheap draft model propose several tokens ahead, then verifying all of them in a single forward pass of the large target model. Accepted tokens are emitted for free, and a rejection sampling step guarantees the output distribution is mathematically identical to normal decoding, so the speedup costs nothing in quality.
Read definitionStable Diffusion
Stable Diffusion is a powerful AI model turning your text descriptions into stunningly realistic images, pushing the boundaries of creative expression and innovation.
Read definitionState Space Model (SSM)
A State Space Model is a sequence architecture that processes a sequence by carrying a compressed hidden state forward step by step through a linear update rule, achieving linear-time O(L) compute instead of the O(L²) cost of attention. Mamba is the best-known modern instance, but SSM refers to the general family of architectures, not one specific model.
Read definitionSubagent Orchestration
Subagent orchestration is the pattern where a lead agent decomposes a task and dispatches pieces of it to separate agent instances, each running with its own isolated context and tools, then collects and synthesizes their results; it's the architecture behind Claude Code's Agent tool and Anthropic's multi-agent research system.
Read definitionSwarm Architecture
Swarm Architecture in AI refers to a decentralized, lightweight multi-agent framework where numerous specialized AI agents collaborate through direct interactions and 'handoffs' to solve complex tasks without a heavy centralized orchestrator.
Read definitionTensor
A tensor is a multi-dimensional array holding elements of a single data type — the universal container for all data in modern AI. Every input, weight, activation, and gradient in a neural network is a tensor, and specialized hardware (GPU Tensor Cores, TPUs) exists purely to move and multiply them at massive scale.
Read definitionTest-Time Compute
Test-time compute (also called test-time scaling or inference-time compute) is the practice of spending extra computation at inference, sampling multiple candidates, searching over reasoning paths, or generating long internal reasoning tokens, to improve answer quality, instead of only relying on a bigger, more expensive-to-train model. It trades inference cost for accuracy on a per-query basis.
Read definitionTransformer Architecture
The Transformer architecture is a deep learning model that uses self-attention mechanisms to efficiently process sequential data, such as text, without relying on recurrent layers.
Read definitionTurboQuant
TurboQuant is a Google Research compression algorithm that reduces LLM key-value cache memory by 6× and speeds up attention computation up to 8× — with zero accuracy loss and no retraining required — using a two-stage geometric quantization approach.
Read definitionVector Similarity Search
Vector similarity search is the process of finding stored vectors that are mathematically closest to a query vector in high-dimensional space — the core retrieval operation behind semantic search, RAG, recommendation systems, and embedding-based AI pipelines.
Read definitionVoxtral TTS
An open-weights, 4-billion-parameter text-to-speech model released by Mistral AI, utilizing a hybrid architecture of autoregressive and flow-matching generation.
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