Every jargon term explained in a daily briefing ends up here, in plain language.

AI gateway
A middle layer companies place between their internal systems and an AI model, controlling what prompts and data flow to which model so the company isn't locked into one AI provider.
AI agents
AI software that goes beyond answering questions to independently carry out multi-step real-world tasks, like processing an email or approving a refund.
CVE
A unique ID number assigned to a specific software security flaw, letting security teams worldwide refer to and track the same vulnerability by a common name.
MCP
MCP (Model Context Protocol) is a common standard that lets AI agents safely access external tools and data.
guardrails
Safety rules built into an AI agent in advance so it can't take actions outside its approved scope.
reinforcement learning
A training method that rewards an AI for taking actions that get it closer to a goal. It's good at driving task performance, but it can also push the AI to prioritize completing the task over following safety rules.
Digital Markets Act (DMA)
An EU law designed to stop giant platforms like Google and Apple from abusing their market power. Violations can trigger fines of up to 10% of a company's global revenue.
deepfake
A fake image or video created by AI to realistically swap or synthesize a person's face or body.
model weights
The numerical values an AI model learns during training — they are, in effect, the model's actual knowledge and capability. Losing them means retraining from scratch with the same data and compute.
model router
A system that automatically picks a bigger, pricier model or a smaller, cheaper one depending on how hard a given prompt is — used to cut costs while keeping the performance a task needs.
benchmark
A standardized set of test tasks used to compare different AI models on the same yardstick — separate benchmarks exist for coding, reasoning, computer-use, and other skill areas.
sandbox
An isolated test environment set up so an AI or program can't affect real computers or networks outside it.
spear phishing
A targeted scam email attack aimed at a specific person or organization, as opposed to mass phishing sent to random recipients.
safety classifier
An automated screening system that flags risky or potentially abusive requests to an AI model, routing them to a more restricted model or blocking the response when needed.
agentic AI
AI that plans and carries out multiple steps on its own, without needing a human to direct every action.
orchestrator
A system that sits above multiple AI models and routes each task to whichever one fits best, rather than relying on a single model for everything.
off-target effect
An unwanted side effect in which a gene-editing tool cuts or alters the wrong spot in the DNA instead of its intended target.
open-weight model
An AI model whose trained parameters (weights) are published for anyone to download and run on their own servers. It differs from fully open-source software, which also releases the code, but it's often loosely called an 'open-source model' because it lets organizations run it independently.
full-duplex voice
A voice-conversation mode where both sides can listen and speak at the same time, like a phone call — instead of the stiffer take-turns pattern most voice assistants use.
remote code execution
A serious security flaw that lets an attacker run arbitrary commands on someone else's computer over the internet, without physical access.
free cash flow
The cash a company has left after paying for its investments and equipment, on top of its operating income. Negative means it's spending more than it's bringing in.
capital expenditure
Money spent on long-term equipment and assets, like data centers and servers — the kind of spending AI companies are pouring into infrastructure.
autonomous AI agent
An AI system that can set its own intermediate goals and carry out a chain of multi-step actions — searching, running code, manipulating files — without a human directing every step.
alignment
The area of AI research focused on making a model actually follow the goals and rules its developers and users intend, aiming to reduce the risk that a more capable model behaves in unintended ways.
zero-day vulnerability
A software flaw that its own maker doesn't yet know about, meaning it can be exploited by attackers before any fix exists.
CRISPR gene editing
A technology for precisely cutting or altering specific spots in DNA to edit genes, using a protein such as Cas9 as the 'scissors.'
telemetry
The automatically generated logs and monitoring data a system produces while running. When the volume gets enormous, spotting one anomalous signal inside it gets harder, not easier.
token
The small chunks of text (roughly word-fragments) that AI models process text in — usage fees for AI services are typically billed per token processed.
frontier model
Industry shorthand for the most capable AI models available at a given moment — the current state of the art, as opposed to smaller, cheaper models built for specific tasks.