Truthfully, AI can be categorized and subdivided infinitesimally depending on what you’re looking for. To answer the question “What kinds of AI exist?” is as broad and difficult to answer as “What kinds of websites exist?”. On this page we will make you aware of the classifications of AI based on capabilities and functionality. That being said, a majority of this website’s information will be about integrating and dealing with Natural Language Processors which you can read more about below.


AI designed to complete very specific actions; unable to independently learn.

Examples include image recognition software, self-driving cars and AI virtual assistants like Siri.

AI designed to learn, think and perform at similar levels to humans.

Examples include technologies such as supercomputers, quantum hardware and generative AI models like ChatGPT.

AI able to surpass the knowledge and capabilities of humans.

Examples exist in science fiction

AI capable of responding to external stimuli in real time; unable to build memory or store information for future.

Examples include video game AI or “bots” that players fight against

AI that can store knowledge and use it to learn and train for future tasks.

Examples include customer support chatbots all the way to self-driving cars

AI that can sense and respond to human emotions, plus perform the tasks of limited memory machines.

Examples exist in science fiction

AI that can recognize others’ emotions, plus has sense of self and human-level intelligence; the final stage of AI that we have not yet reached.


NLP, or Natural Language Processing, is a field of artificial intelligence (AI) that focuses on the interaction between computers and humans through natural language. The ultimate goal of NLP is to read, decipher, understand, and make sense of the human language in a valuable way.

NLP involves several tasks and challenges, including:

  1. Text Analysis: Extracting meaningful information and insights from text documents.

  2. Sentiment Analysis: Understanding the sentiment or emotion behind a given piece of text.

  3. Machine Translation: Automatically translating text or speech from one language to another.

  4. Speech Recognition: Transcribing and transforming human speech into a readable format.

  5. Information Extraction: Structuring information from text, often using named entity recognition and relationship extraction techniques.

  6. Text-to-Speech and Speech-to-Text Conversion: Converting text into audible speech or converting spoken language into written text.

  7. Question Answering: Building systems that can answer questions posed by humans in a natural language.

NLP allows for a wide range of applications, including but not limited to: chatbots, voice assistants like Amazon Alexa or Google Assistant, machine translation services like Google Translate, and text analysis tools. It’s a rapidly growing field with ongoing advancements, making human-computer interactions more natural and intuitive.


Image generators are types of AI that generate new images from textual descriptions or other image inputs. They work by training a deep learning model on a large dataset of images so it can learn to produce new, original images that are similar but not identical to the images it was trained on. For example, you could ask the AI to generate an image of “a two-story pink house shaped like a shoe,” and it would produce a unique image based on this prompt.

Image generators have a variety of potential uses:

  1. Art and Design: Artists and designers could use image generators to help visualize concepts, create original artwork, or generate design ideas.

  2. Advertising and Marketing: Marketers could use these tools to create unique images for advertising campaigns based on specific themes or concepts.

  3. Entertainment: In the gaming and film industry, these AI systems can be used to generate new characters, environments, and objects.

  4. Research: In scientific research, these tools can be used to visualize theoretical concepts or phenomena that can’t be observed directly.

  5. Prototyping: Engineers and inventors could use image generators to visualize new products or designs.

Remember, while the potential applications are exciting, the technology also raises issues around copyright, originality, and the potential misuse of generated images. Thus, it’s important to consider these ethical implications when using or developing these systems.

Below are some FREE IGs to play around with. Because they are free, they are low quality but a great window into the power of generative AI: