Artificial Intelligence (AI) Tools for Research

Welcome to the Library guide on using Artificial Intelligence (AI) Research Tools.

Our goal is to introduce some tools that can be utilized during the research process.

Let's start with definitions (courtesy of Microsoft and Cornell University).

1. Artificial Intelligence 

• Intellect created by humans using technology

• Programs that run on computers

• Put a vast collection of data through algorithms to create models that can automate tasks that require human intelligence (and time)

• Been around for a long time

• Examples: suggesting words as we type, recommending songs in playlists, recommending related articles

2. Machine learning 

• A field of computer science where they teach a computer system how to do something by training it to identify patterns and make predictions based on those patterns

• Data is run through repetitiously so system can “learn”

• Helpful with recognizing images and translating languages

• Takes a huge amount of data

3.  Large language models (LLMs)

• Use Machine Learning to help them process language so they can mimic the way humans communicate

• They’re based on neural networks (NNs) which are computing systems inspired by the human brain

• Trained on a massive amount of text to learn patterns and relationships in language that help them use human words

• They don’t have thoughts or feelings, but sometimes they sound like they do, because they’ve learned patterns that help them respond the way a human might.

• They’re often fine-tuned by developers using a process called reinforcement learning from human feedback (RLHF) to help them sound more conversational.

4. Generative AI

• Generative AI leverages the power of large language models to make new things, not just regurgitate or provide information about existing things. 

• It learns patterns and structures and then generates something that’s similar but new. 

• It can make things like pictures, music, text, videos and code.