Research Guides @ Fordham: Computer & Information Science: Home

Fordham Computer and Information Science Department

Fordham - Computer and Information Science
The department website for the Computer and Information Science department at Fordham. Find information about courses, faculty, and research
Fordham Computer Science Tutoring Program
Tutoring is available for students in CS 1100 (Structures of Computer Science), CS1400 (Discrete Structures), CISC2100 (Discrete Structure II), CISC1600 (Computer Science I), CISC2000 (Computer Science II).

Citation Guidance

Chicago Manual of Style Online This link opens in a new window
Provides access to the Chicago Manual of Style in a searchable online format.

Chicago Style - Purdue OWL
Guidance on Chicago style from Purdue's Online Writing Lab.
ACM Citation Style
Citation style and reference formats for the Association of Computer Machinery,
IEEE Editorial Style Manual for Authors
Style manual and writing guidelines for the Institute of Electrical and Electronics Engineers (IEEE) Transactions, Journals, and Letters.
IEEE Documentation Style
Abbreviated guidance on citing sources in IEEE style.
Other Citation Styles
Link to library research guide on other MLA, APA, and Chicago styles.

ChatGPT

What is ChatGPT?

ChatGPT is a chatbot that runs on top of the GPT-3 (Generative Pre-trained Transformer) family of language models, built by OpenAI. GPT-3 is a prediction model that uses deep learning to produce text.

ChatGPT uses these language models to interact with the user in a conversational way. In addition to these language models, it was further trained using Reinforcement Learning from Human Feedback (RLHF) - meaning that human AI trainers provided example conversations and ranked AI responses.

ChatGPT can follow a conversation, write and debug computer programs, play games, write essays, and more. It can also remember and reference previous prompts given by the user, which is a feature that many other chatbots do not have.

ChatGPT has limitations. It is limited to knowledge pulled from its training data and can sometimes produce responses that sound correct but are false or nonsensical. Trainers tended to prefer longer answers and it suffers from common over-optimization issues (see Goodhart's law), so it has a tendency to be overly wordy and overuse certain phrases. There are also risks of algorithmic bias and misuse that appear in many AI implementations.