The AI terms that
actually matter.
Clear, technical definitions of 115 key concepts — written by AI engineers, not marketers.
Semantic Chunking
Semantic chunking splits a document into retrieval chunks at points where consecutive sentences stop being topically similar, using embedding-similarity drops or discourse boundaries instead of a fixed character or token count. It trades extra compute at ingest time for chunks that hold together as coherent units of meaning.
Read definitionSHAP (SHapley Additive exPlanations)
SHAP is a method for explaining any machine learning prediction by assigning each input feature a signed contribution that adds up to the difference between that prediction and the model's average output. The contributions are Shapley values from cooperative game theory, which makes them the unique attribution satisfying a short list of fairness axioms.
Read definitionSliding Window Attention (SWA)
Sliding Window Attention (SWA) restricts each token to attending only within a fixed-size local neighborhood instead of the full sequence, cutting attention cost from quadratic to linear in sequence length; stacked across layers its effective receptive field still reaches far, and interleaving it with periodic full-attention layers (Mistral, Gemma, GPT-OSS) is the standard recipe modern LLMs use to control KV cache size at long context.
Read definitionSora AI Model
Sora is OpenAI's groundbreaking text-to-video AI model and can generate high-def videos of up to 1 min duration.
Read definitionSovereign AI
Sovereign AI refers to the strategic development, deployment, and control of artificial intelligence capabilities by a nation, region, or organization to ensure data privacy, security, and cultural alignment, independent of foreign or third-party infrastructure.
Read definitionSpeaker 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 definitionStay ahead of the curve
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