All sources are listed at bottom for further reading.
Artificial intelligence (A.I. or AI) refers to the development of computer systems that can perform tasks that typically require human intelligence. These tasks include learning, reasoning, problem-solving, perception, understanding natural language, and interacting with the environment. AI systems often utilize techniques such as machine learning, neural networks, natural language processing, and robotics to mimic human cognitive functions and achieve specific goals (OpenAI 
). It is an umbrella term.
Machine learning (ML) is a subfield or branch of AI that uses algorithms trained on data to produce adaptable models that can perform a variety of complex tasks (Coursera, 2023) including making predictions or "decisions" based on new data (OpenAI ).
Deep learning (DL) is a young subfield of AI and ML based on artificial neural networks that requires data to learn and solve problems (Oppermann, 2022). Modeled loosely on the human brain, a neural net consists of thousands or even millions of simple processing nodes that are densely interconnected (Hardesty 2017).
Large language models (LLMs) are a specific type of AI system that work from and generate natural language (Toner, 2023). While the generative output trained on LLMS is seemingly coherent, Drs. Bender, McMillan-Major, Gebru and Schmitchell warn that they are, in essence, stochastic parrots, devoid of meaningful coherence due to the lack of human agency and context (Bender and Gebru et al., 2021). See What are chatbots? further down this page.
Generative artificial intelligence (also known as generative AI, OR GAI) is a broad label that’s used to describe any type of artificial intelligence that's used to create. Text, which is capable of natural language processing (NLP), code, molecular simulations, audiovisual outputs: video, sounds, music, images, art; 3D objects, simulations, synthetic data and robotic motion planning are all categories of generative AI (Islam, 2023 and Rouse, 2023). Generative AI can be either unimodal or multimodal; unimodal systems take only one type of input, whereas multimodal systems can take more than one type of input (Islam, 2023). It can also be grounded (the model output is connected to verifiable information sources) or ungrounded (the model output cannot be verified) ("Grounding Overview," n.d.).
While it's often associated with ChatGPT and deep fakes, the technology was initially used to automate repetitive processes used in digital image and audio correction. Arguably, because machine learning (ML) and deep learning (DL) are inherently focused on generative processes, they can be considered types of generative AI, too (Rouse, 2023).
A chatbot is a computer program that uses artificial intelligence (AI) and natural language processing (NLP) to react to questions and automate responses to them, simulating human conversation (IBM, n.d.). It is a specific category of generative AI. Large language models (LLMs) like ChatGPT, an AI chatbot, are essentially a very sophisticated form of auto-complete or predictive text sourced from terabytes of data (Wooldridge, 2023). They do not "comprehend" their output.
Other categorical divisions to consider in AI and machine learning are: extractive vs generative and supervised vs semi-supervised vs unsupervised vs reinforcement models.
Visit three (3) different text generative AI bots and ask them to define any of the terms listed above, or a term of your choice, then compare their responses to see the differences and investigate their accuracy.
Recommendations: In a text document, keep track of exactly how you wrote your request, when (date/time), and what the responses were by bot. Consider returning 3, 6, and 9 months from that time and note how (or if) the answers have changed over time and make note of the differences. Did the answers become more accurate or less accurate? Shorter or longer? More or less explicit? Would you use them again for this purpose? Note your responses.
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Credo Reference: https://0-search-credoreference-com.librus.hccs.edu/content/entry/encyccs/artificial_intelligence_ai/0?institutionId=1798.
Bender, E. M., Gebru, T., McMillan-Major, A., & Schmitchell, S. (2021, March 1). On the dangers of stochastic parrots: Can language models be
too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610-623.
https://doi.org/10.1145/3442188.3445922
Coursera. (2023, May 17). Machine learning vs. AI: Differences, uses, and benefits. Coursera Inc.
https://www.coursera.org/articles/machine-learning-vs-ai.
Google. (n.d.). AI across Google: PaLM 2. Google AI. https://ai.google/discover/palm2/.
Google Cloud. (n.d.) Grounding overview. Retrieved May 13, 2024. https://cloud.google.com/vertex-ai/generative-ai/docs/grounding/overview.
Hardesty, L. (2017, April 14). Explained: Neural networks. MIT News. https://news.mit.edu/2017/explained-neural-networks-deep-learning-0414.
Henderson, H. (2021). Weizenbaum, Joseph. In H. Henderson, Encyclopedia of computer science and technology (4th ed.). Facts On File. Credo
IBM. (n.d.) What is a chatbot? IBM. https://www.ibm.com/topics/chatbots.
Islam, A. (2023, Mar 21). A history of generative AI: From GAN to GPT-4. Marktechpost Media Inc.
https://www.marktechpost.com/2023/03/21/a-history-of-generative-ai-from-gan-to-gpt-4/.
Meta. (2023, Feb 23). Introducing LLaMA: A foundational, 65-billion-parameter large language model. Meta AI.
https://ai.facebook.com/blog/large-language-model-llama-meta-ai/.
OpenAI. (2023). ChatGPT 3.5 (May 2, 2024 version) [Large language model]. https://chat.openai.com/chat.
Oppermann, A. (2022, Sep 16). Artificial intelligence vs. machine learning vs. deep learning: What’s the difference?
Built In. https://builtin.com/artificial-intelligence/ai-vs-machine-learning.
Ortiz, S. (2023a, May 23). The best AI chatbots: ChatGPT and other noteworthy alternatives. ZDNET. https://www.zdnet.com/article/chatgpt-now-lets-you-create-and-share-links-to-your-conversations/.
Ortiz, S. (2023b, Jun 1). What is Google Bard? Here's everything you need to know. ZDNET. https://www.zdnet.com/article/what-is-google-bard-heres-everything-you-need-to-know/.
Rouse, M. (2023, Jun 5). What does generative AI mean? Techopedia. https://www.techopedia.com/definition/34633/generative-ai.
Scribbr. (n.d.) Where does ChatGPT get its information from? Scribbr.
Toner, H. (2023, May 12). What are generative AI, large language models, and foundation models? Center for Security and Emerging
Technology. https://cset.georgetown.edu/article/what-are-generative-ai-large-language-models-and-foundation-
Wooldridge, M. (2023, May 17). ChatGPT is not “true AI.” A computer scientist explains why. Big Think. https://bigthink.com/the-future/artificial-
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