AI Watermarking
In one line
AI watermarking embeds an imperceptible signal in AI-generated text, images or audio so that the content can later be identified as machine-made.
Going deeper
AI watermarking embeds a signal that humans cannot really perceive but a dedicated detector can read as 'this came from a model'. It is well underway in images and audio (Google's SynthID and friends), and text watermarking — typically through subtle statistical biases in token choice — is in active research and limited deployment.
The policy push behind it is clear. With deepfakes and automated misinformation rising, governments are converging on watermarking or equivalent identifiers as a baseline expectation — see the EU AI Act and recent guidance in the US and UK.
Be honest about the limits. Text watermarks are often broken by rewriting, translating or quoting short fragments. The realistic framing is not 'silver bullet' but 'one layer in a stack' that also includes provenance metadata, digital signatures and content credentials like C2PA.
Related terms
LLM-as-a-Judge
LLM-as-a-judge is the practice of using one LLM to grade or compare the answers of another — a standard way to scale evaluation beyond what human labelling can cover.
LLMInstruction Tuning
Instruction tuning is the fine-tuning step that teaches a base LLM to follow instructions in natural language — the stage that turns 'a model that completes text' into 'a model you can actually ask things'.
LLMKnowledge Distillation
Knowledge distillation trains a smaller 'student' model to mimic a larger 'teacher' model — preserving most of the quality while drastically cutting cost and latency.
LLMLLM
A large language model (LLM) is a neural network trained on massive text corpora to understand and generate human language — the engine behind ChatGPT, Claude, Gemini and similar products.
AI AgentAgent Hijacking
Agent hijacking is the attack where malicious instructions hidden inside external data or tool outputs take over an agent's decision-making — the headline security threat for autonomous agents.
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