Prompt Engineering
The process where you guide generative artificial intelligence (generative AI) solutions to
generate desired outputs.
Artificial Intelligence
A field of computer science dedicated to solving cognitive problems commonly associated with
human intelligence.
Conversational AI
A technology that makes software capable of understanding and responding to voice-based or
text-based human conversations.
Generative AI
A type of AI that can create new content and ideas, including conversations, stories, images,
videos, and music.
Embedding
A numerical representation of real-world objects that machine learning (ML) and artificial
intelligence (AI) systems use to understand complex knowledge domains like humans do.
Supervised learning
This is a prominent type of machine learning due to its vast range of applications. It's termed
supervised learning because there must be a supervisor.
,Classification
A supervised learning technique that assigns labels or categories to new, previously unseen data
examples using a learned model.
Regression
A supervised learning technique that predicts continuous or numerical values given one or more
input variables.
Unsupervised learning
The algorithm tries to discover hidden patterns or structures within the data without any prior
information or guidance.
Clustering
This method divides data into clusters based on similar traits or distances between data points in
order to better understand the characteristics of a particular cluster.
Dimensionality reduction
An unsupervised learning strategy that minimizes the number of features or dimensions in a
dataset while retaining the most relevant information or patterns.
Reinforcement learning
One continuously improves their model by analyzing feedback from prior versions. In
reinforcement learning, an agent learns by trial and error as it interacts with its surroundings.
, Intelligent Document Processing (IDP)
A software tool that extracts and categorizes information from unstructured or structured data,
generates summaries, and delivers actionable insights.
Adaptability
It can adapt to a variety of activities and domains by learning from data and producing material
that is suited to specific situations or needs. Because of its flexibility, generative AI can be applied
to a wide number of sectors.
Responsiveness
It can generate content in real time, resulting in faster reaction times and more dynamic
interactions. This is especially beneficial for chatbots, virtual assistants, and other interactive
applications that demand instant feedback.
Simplicity
It can make hard tasks easier by automating content generation processes. For example, AI
language models may generate human-like text, reducing the time and effort necessary for
content development.
Creativity and exploration
It can develop new ideas, designs, or solutions by combining and recombining pieces in unusual
ways. This can encourage creativity and the discovery of new possibilities.
Data efficiency
The process where you guide generative artificial intelligence (generative AI) solutions to
generate desired outputs.
Artificial Intelligence
A field of computer science dedicated to solving cognitive problems commonly associated with
human intelligence.
Conversational AI
A technology that makes software capable of understanding and responding to voice-based or
text-based human conversations.
Generative AI
A type of AI that can create new content and ideas, including conversations, stories, images,
videos, and music.
Embedding
A numerical representation of real-world objects that machine learning (ML) and artificial
intelligence (AI) systems use to understand complex knowledge domains like humans do.
Supervised learning
This is a prominent type of machine learning due to its vast range of applications. It's termed
supervised learning because there must be a supervisor.
,Classification
A supervised learning technique that assigns labels or categories to new, previously unseen data
examples using a learned model.
Regression
A supervised learning technique that predicts continuous or numerical values given one or more
input variables.
Unsupervised learning
The algorithm tries to discover hidden patterns or structures within the data without any prior
information or guidance.
Clustering
This method divides data into clusters based on similar traits or distances between data points in
order to better understand the characteristics of a particular cluster.
Dimensionality reduction
An unsupervised learning strategy that minimizes the number of features or dimensions in a
dataset while retaining the most relevant information or patterns.
Reinforcement learning
One continuously improves their model by analyzing feedback from prior versions. In
reinforcement learning, an agent learns by trial and error as it interacts with its surroundings.
, Intelligent Document Processing (IDP)
A software tool that extracts and categorizes information from unstructured or structured data,
generates summaries, and delivers actionable insights.
Adaptability
It can adapt to a variety of activities and domains by learning from data and producing material
that is suited to specific situations or needs. Because of its flexibility, generative AI can be applied
to a wide number of sectors.
Responsiveness
It can generate content in real time, resulting in faster reaction times and more dynamic
interactions. This is especially beneficial for chatbots, virtual assistants, and other interactive
applications that demand instant feedback.
Simplicity
It can make hard tasks easier by automating content generation processes. For example, AI
language models may generate human-like text, reducing the time and effort necessary for
content development.
Creativity and exploration
It can develop new ideas, designs, or solutions by combining and recombining pieces in unusual
ways. This can encourage creativity and the discovery of new possibilities.
Data efficiency
