What is AI and how does it work?
AI, which stands for artificial intelligence, is a broad term encompassing a wide range of technologies. The AIs most talked-about these days are more specifically known as generative AIs.
Generative AIs use a technology which allows them to generate many different kinds of content, including text, images, code, and others.
What's the technology behind generative AI?
To be able to generate new content, any given generative AI draws from a data set, which is a huge set of text, images, code, or other content.
Each AI is comprised of a large network of computer-hosted components known collectively as an artificial neural network (ANN). Artificial neural networks include the term "neural" because they are modeled loosely after the way neurons function in a biological brain. Both animal and artificial neural networks can store, transmit, and act on billions of small pieces of data in myriad patterns.
The technology at the core of a generative AI is a Large Language Models (LLM). The word "model" refers to the types of algorithms (i.e. set of calculations) which allows it to process data in a specific way.
"Model" is used to describe computer systems that can model weather systems, biological systems, or any complex mathematically-based system. In the case of generative AIs what's being modeled is the comprehension and creation of textual and visual language.
Although a generative AI does not truly replicate the biological processes in an animal brain, it can engage in a specific cognitive skill called "pattern recognition".
A generative AI develops the ability to recognize and generate meaningful patterns out of data when it is given a very large set of data to reference and is provided with a very large amount of computational power.
What is generative AI good at?
Generative AI is good at recognizing and replicating patterns in the various textual and visual languages contained within its data set.
Some AIs, such as ChatGPT, have been trained on an enormous data set which contains many different kinds of languages, including, for example human languages like English, Spanish, and Hindi, computer languages like Python and C++, and visual languages, like x-rays and sports photos.
Because ChatGPT has been trained with data that includes all these languages, it develops the ability to generate content in all of those languages too.
Why are some AIs like ChatGPT remarkably good at generating content?
The most advanced AIs are very good at generating text and images because they attend to contextual and positional details of each word, phrase, or component. This is similar to how humans generate coherent language!
"'GPT' stands for 'Generative Pre-Trained Transformer'. A transformer model is an innovation on a more conventional neural network that adds in 'attention layers', allowing the model to selectively 'pay attention' to different positions of an input string. So, for example, if the model is 'learning' from an example sentence, different layers of the neural network can 'attend' to different words in the sentence, and can learn about the relationships between different parts of the sentence, not just those parts that are immediately adjacent. Models like GPT-3 have an enormous number of 'parameters', which allow the model to 'attend' to many, many aspects of the 'context' in which a particular word appears. This architecture gives transformer models a way of flexibly representing a LOT of information about the context in which different words appear, and that flexibility is a big part of what gives transformer models the power they have to generate such fluent-sounding text."
A word of caution about generative AI security —
AIs are new and experimental technology. Even AIs which claim to be secure may have security vulnerabilities which have not yet been discovered or addressed.
Before you use AI for teaching read: Tufts Guidelines for Use of Generative AI Tools
Tufts has vetted and licensed a select set of AIs for use in teaching.