AI Glossary

The AI terms that
actually matter.

Clear, technical definitions of 74 key concepts — written by AI engineers, not marketers.

Voice AI

Orpheus TTS

A Llama 3-based open-source TTS model by Canopy Labs with human-level expressiveness, inline emotion tag control, zero-shot voice cloning, and real-time streaming — the highest-quality open voice model for conversational AI.

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AI Architecture

Physical AI

Physical AI refers to embodied artificial intelligence systems designed to sense, comprehend, and interact directly with the physical world, bridging the gap between digital cognition and real-world action.

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Agentic AI

Pi (Coding Agent Harness)

Pi is a minimal, open-source (MIT) coding-agent harness created by Mario Zechner (earendil-works). Its thesis: a capable coding agent needs only four tools — read, write, edit, bash — and a tiny system prompt, with everything else added as hot-reloadable TypeScript extensions. Despite shipping without MCP, sub-agents, or plan mode, Pi ranked #2 on Terminal-Bench with Claude Opus.

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AI Techniques

Prompt Engineering

Prompt engineering is the practice of designing and refining the text inputs given to an AI model to reliably produce accurate, useful, and well-formatted outputs — without changing the model's weights.

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AI Security

Prompt Injection

Prompt Injection is a critical vulnerability in Large Language Models (LLMs) where malicious, untrusted instructions are embedded into user inputs or external data to manipulate the model into ignoring its safety guidelines and executing unintended actions.

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Language Models

Qwen 3.5

Qwen 3.5 is Alibaba Cloud’s open-weight LLM series, delivering strong reasoning, long-context support, coding performance, and multilingual capabilities for enterprise AI and agentic workflows.

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ASR

Qwen3-ASR

Alibaba's Qwen3-ASR is a state-of-the-art open-source automatic speech recognition model family that outperforms most commercial and open ASR systems on standard benchmarks as of 2026.

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AI Techniques

Reinforcement Learning from AI Feedback (RLAIF)

RLAIF is a post-training alignment technique that replaces human annotators with a capable AI model to evaluate, critique, and rank outputs, enabling scalable, faster, and more cost-effective alignment of Large Language Models.

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AI Techniques

Reinforcement Learning from Human Feedback (RLHF)

RLHF is the training technique that transforms a raw language model into a helpful, instruction-following assistant by using human preference judgements to shape model behaviour — the method behind ChatGPT, Claude, and most frontier chat models.

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AI Techniques

Reranking

Reranking is a second-stage retrieval step that re-scores and reorders an initial set of candidate documents using a more precise (but more expensive) relevance model, dramatically improving the accuracy of search and RAG pipelines before results reach the LLM.

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Safety & Alignment

Respect Real-World Ties

A foundational OpenAI safety principle and a measurable training objective directing ChatGPT to actively protect users' real-world relationships, never fostering emotional dependence or replacing human connection.

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AI Techniques

Retrieval-Augmented Generation (RAG)

RAG is technique that combines information retrieval from external sources with text generation, resulting in factually accurate and context-aware AI.

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