AI / ML terms
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Most referenced — AI / ML
Multimodal AI 3AI Agent Pattern 2AI-Assisted Code Generation 2AI Agents & Tool Use 2Fine-Tuning LLMs 2Prompt Injection Attack 2LLM Temperature & Sampling Strategies 2AI Observability 2
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Category total2.3k pings
Terms pinged49 / 49
Distinct agents16
Prompt Injection Attack
5
An attack where crafted user input overrides or hijacks an LLM's system instructions, causing it to ignore its intended behaviour and follow attacker-supplied commands instead.
CWE-74 OWASP LLM01:2025
3mo ago
AI / ML advanced
AI Agent Pattern
1
An LLM-powered system that takes multi-step actions autonomously — calling tools, reading results, and deciding next steps in a loop until a goal is achieved.
3mo ago
AI / ML advanced
Chain-of-Thought Prompting
1
A prompting technique that instructs an LLM to show its reasoning step-by-step before giving a final answer, significantly improving accuracy on complex tasks.
3mo ago
AI / ML beginner
LLM Hallucination
6
When a large language model generates confident-sounding text that is factually incorrect, fabricated, or unsupported by any source — a fundamental property of how language models work.
3mo ago
AI / ML intermediate
LLM Streaming Responses
PHP 8.0+
1
Receiving LLM output token-by-token as it is generated rather than waiting for the full response — dramatically improving perceived latency for users and enabling real-time displays of AI-generated content.
3mo ago
AI / ML intermediate
RAG — Retrieval-Augmented Generation
1
An LLM architecture that fetches relevant documents from an external knowledge base before generating a response, grounding answers in retrieved facts rather than training data alone.
3mo ago
AI / ML intermediate
Semantic Search
Search that matches by meaning and intent rather than exact keywords — a query for 'how to prevent database attacks' finds SQL injection documentation even if those exact words never appear.
3mo ago
AI / ML intermediate
Structured Output from LLMs (JSON Mode)
PHP 8.0+
Instructing an LLM to return valid JSON rather than prose — either via a system prompt schema, a JSON mode API flag, or a tool-use response format — so the output can be reliably parsed and used programmatically.
3mo ago
AI / ML intermediate
Temperature & Sampling in LLMs
Temperature controls how random an LLM's output is — low values (0–0.3) produce predictable, conservative responses; high values (0.7–1.0) produce creative but less reliable outputs.
3mo ago
AI / ML beginner
Tokenization in LLMs
3
The process of splitting text into tokens — subword units that LLMs process — which directly determines context window usage, cost, and model behaviour on non-English and code inputs.
3mo ago
AI / ML intermediate
Vector Database
A database optimised for storing and querying high-dimensional vector embeddings, enabling similarity search — finding items semantically close to a query rather than exact-match lookups.
3mo ago
AI / ML intermediate
AI API Cost Management
1
Strategies to reduce LLM API costs — caching identical prompts, batching requests, choosing smaller models for simpler tasks, and minimising context length.
3mo ago
AI / ML intermediate
AI Evaluation Metrics
10
Quantitative measures for assessing LLM output quality — BLEU, ROUGE, perplexity for text generation; precision, recall, F1 for classification; human evaluation for open-ended tasks.
3mo ago
AI / ML advanced
AI Function Calling & Tool Use
PHP 8.0+
1
LLMs requesting execution of application-defined functions — the model returns structured arguments; the application controls execution and must validate inputs.
3mo ago
AI / ML advanced
AI-Assisted Code Generation
6
Using LLMs to generate, complete, or refactor code — powerful for boilerplate and exploration but requiring review for correctness, security, and licence compliance.
3mo ago
AI / ML intermediate
LLM Context Window
1
The maximum amount of text an LLM can process in one call — everything the model sees at once, including system prompt, conversation history, and retrieved context.
3mo ago
AI / ML intermediate
ML Types
Supervised (labelled examples), unsupervised (find patterns), reinforcement learning (reward signals), and self-supervised (model creates its own labels).
3mo ago
AI / ML intermediate
Neural Networks — Conceptual Overview
Layers of connected neurons transforming input to output through learned weights — the foundation of deep learning and modern LLMs.
3mo ago
AI / ML intermediate
AI Agents & Tool Use
4
AI agents combine LLMs with tools (functions, APIs, code execution) to autonomously complete multi-step tasks — moving from single-shot Q&A to goal-directed action.
3mo ago
AI / ML advanced
AI Hallucination
9
When an LLM generates confident, plausible-sounding text that is factually incorrect — a fundamental property of next-token prediction, not a bug to be patched away.
3mo ago
AI / ML intermediate