Glossary

AI Glossary

Explore definitions for common AI and Knowledge Management terms.

 

A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

 

A

ACID test: 

A test applied to data for atomicity, consistency, isolation, and durability.

AGI (Artificial General Intelligence):

A general purpose system that has intelligence similar to the human mind. AGI is also known as, “Human-level AI” or “Strong AI”.

Algorithm:

A mathematical formula placed in software that performs an analysis on a set of data.

Analogical Reasoning:

A method that uses analogies or patterns that compares a new concept to an already understood concept to derive a probable conclusion about what could be true about the new concept.

Anonymization:

A type of information sanitizing that prioritizes privacy. Anonymization cuts the ties between collected data and other personal information to keep the person involved incognito.

Artificial Intelligence:

Artificial Intelligence is the ability for computer systems to perform tasks that normally require human intelligence. AI can be a great assistant, that can help optimize tasks such as visual perception, speech recognition, decision making and more.

ANI (Artificial Narrow Intelligence):

A one trick pony, this AI has some cool tricks in their back pocket. They can play chess, recognize faces or translate foreign languages.

ANN (Artificial Neural Network): 

Also know as a “neural network”, this computing system is patterned after the way neurons in the human brain work in a simplified way. This systems goal is to solve pattern recognition problems.

ASI (Artificial Super Intelligence): 

These AI’s are smarter than the best human brains and can apply their wit and charm to absolutely anything. This is the AI that Elon Musk warned you about.

Audience Extension: 

This takes a known audience segment and sorts them by shared traits. This can be used to target people who have similar characteristics to the known audience, who are likely to become customers themselves.

 

B

Behavioral Targeting:

Shows people advertisements that could be most relevant to them based on the websites they visit. Food for thought: What do your targeted ad's say about you?

Big Data: 

Also known as the “new oil”, Big Data is massive amounts of information of all types, that needs to be processed and analyzed quickly. Big Data includes structured, semi-structure, and unstructured data that can be used to find new insights.

Black Box: 

Used to describe some deep learning systems. Black box takes an input and provides an output very mysteriously, as the calculations that occur in the process are not easy for humans to interpret.  

 

C

Cognitive Search:

Cognitive Search is next level enterprise search. Cognitive search uses AI to understand the users intent, rather than relying on simple keywords to provide rich, relevant search results.

Content Management:

Refreshes and organizes the content of a website or database, to make sure the content is current, accurate, easily accessible and relevant. Content management helps businesses deliver the highest quality and most valuable information to their users.

  

D

Data-Management Platform (DMP):

A company that offers technology to organize and store marketer data.

Data Mining: 

A process to discover patterns in large sets of data in hopes to find useful information.

Deep Learning:

A subset of machine learning used to model and understand complex structures and relationships in data using specialized algorithms. Deep learning has multiple connected neurons (see ANN), that take machine learning a step further.

 

E

Enterprise Data

Data that is shared across all areas of an organization. AI-powered knowledge management platforms can help manage all this information, so you don't have to.

 

F

First Party Data

Data that has been collected directly from your clients or audience

 

G

Geotargeting: 

Uses location services or a registered ZIP code to show consumers advertisements based on where they are located. 

 

I

Internal Data Source

Information gathered through how customers engage within your corporate communications channels. Some examples are, your social pages, internally built customer personas, sales and customer service and your marketing automation software.

 

K

Knowledge Management:

The process of creating, sharing, using and managing knowledge and information of an organization, so organizations can get the most out of their information.

 

M

Machine Learning:

Machine Learning keeps track of and learns what users click on, search for, and if they get the information they need. As a result, machine learning makes the “intelligence” in AI more intelligent.

 

N

Natural Language Processing(NLP):

NLP translates human communication so that the AI can understand it in the same way another human would. NLP makes it so search results come back with the most relevant and meaningful answers.

 

Q

Qualitative Data

Requires a subjective decision in order to be categorized or measured. See unstructured data.

Quantitative Data

Can be measured numerically and precisely. See structured data.

 

R

Reinforcement Learning:

A method of teaching AI that involves giving the AI a goal that isn’t defined with a specific metric, such as telling it to “find solutions.” Instead of just finding one answer, the AI will process the information it has, and report results. The results are then judged by humans, the humans give reinforcement training and the AI uses that reinforcement to achieve better results the next time.

 

S

Structured Data

Quantitative data made up of clearly defined data, whose pattern makes them easily searchable. If only everything was this easy.

 

T

Third Party Data

Data that a marketer gets through outside sources.

 

U

Unstructured Data

Qualitative data such as, multimedia content, blog posts, emails, customer service interactions and more. Unstructured Data has helpful insights you didn't know you needed.