The process where you guide generative artificial intelli-
gence (generative AI) solutions to generate desired out- Prompt Engineering
puts.
A field of computer science dedicated to solving cognitive
Artificial Intelligence
problems commonly associated with human intelligence.
A technology that makes software capable of understand-
ing and responding to voice-based or text-based human Conversational AI
conversations.
A type of AI that can create new content and ideas, includ-
Generative AI
ing conversations, stories, images, videos, and music.
A numerical representation of real-world objects that ma-
chine learning (ML) and artificial intelligence (AI) systems
Embedding
use to understand complex knowledge domains like hu-
mans do.
This is a prominent type of machine learning due to its
vast range of applications. It's termed supervised learning Supervised learning
because there must be a supervisor.
A supervised learning technique that assigns labels or
categories to new, previously unseen data examples using Classification
a learned model.
A supervised learning technique that predicts continuous
Regression
or numerical values given one or more input variables.
The algorithm tries to discover hidden patterns or struc-
tures within the data without any prior information or Unsupervised learning
guidance.
This method divides data into clusters based on similar
traits or distances between data points in order to better Clustering
understand the characteristics of a particular cluster.
, AWS Certified AI Practitioner Foundational AIF-C01 Test with Answers Rated A
An unsupervised learning strategy that minimizes the
number of features or dimensions in a dataset while re- Dimensionality reduction
taining the most relevant information or patterns.
One continuously improves their model by analyzing feed-
back from prior versions. In reinforcement learning, an
Reinforcement learning
agent learns by trial and error as it interacts with its sur-
roundings.
A software tool that extracts and categorizes information
from unstructured or structured data, generates sum- Intelligent Document Processing (IDP)
maries, and delivers actionable insights.
It can adapt to a variety of activities and domains by
learning from data and producing material that is suited
Adaptability
to specific situations or needs. Because of its flexibility,
generative AI can be applied to a wide number of sectors.
It can generate content in real time, resulting in faster re-
action times and more dynamic interactions. This is espe-
Responsiveness
cially beneficial for chatbots, virtual assistants, and other
interactive applications that demand instant feedback.
It can make hard tasks easier by automating content gen-
eration processes. For example, AI language models may
Simplicity
generate human-like text, reducing the time and ettort
necessary for content development.
It can develop new ideas, designs, or solutions by com-
bining and recombining pieces in unusual ways. This can
Creativity and exploration
encourage creativity and the discovery of new possibili-
ties.
It can learn from relatively little quantities of data and
Data eflciency
produce new samples that are consistent with the training