What is AI?

 

Job opportunitiy: Senior Core IT Services Specialist in AI Services

Short Description: UNM IT is looking for a Senior Core IT Services Specialist to help develop and guide university adoption of AI services to support teaching and learning. This position will report to UNM’s Director of Online Strategies and Academic Technologies and work in a department that is passionate about empowering students and faculty to participate in higher education through the ethical and effective adoption of technology. From the rapid expansion of online and hybrid meetings that resulted from the COVID-19 pandemic to transformative impacts of artificial intelligence, technology is playing an increasing role in the delivery of education, in classrooms, computer labs, makerspaces, back offices, and online. Key to that successful transformation is an awareness of the intersection of technology, pedagogy, and higher education policy as we design and develop solutions to ensure that the digital divide doesn’t leave any members of our diverse student body behind. Consideration for this position closes on August 14, 2025.

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Artificial Intelligence (AI) refers to the simulation of human intelligence processes by machines, particularly computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions), and self-correction. AI is often categorized into two types:

  1. Narrow AI: Also known as weak AI, operates under a limited set of constraints and is designed to perform a narrow task, such as voice recognition or driving a vehicle. Most AI that we interact with today, like virtual assistants (e.g., Siri or Alexa), are considered narrow AI.

  2. General AI: Also known as strong AI, this type of AI possesses the ability to perform any intellectual task that a human being can do. It can understand, learn, adapt, and implement knowledge in a way that's not limited to a specific domain. 

Machine learning (ML) is a branch of artificial intelligence (AI) and computer science that focuses on the using data and algorithms to enable AI to imitate the way that humans learn, gradually improving its accuracy (IBM - What is ML).

Large language models (LLMs) are a category of foundation models trained on immense amounts of data making them capable of understanding and generating natural language and other types of content to perform a wide range of tasks (IBM - What are LLMs).

A neural network is a machine learning program, or model, that makes decisions in a manner similar to the human brain, by using processes that mimic the way biological neurons work together to identify phenomena, weigh options and arrive at conclusions. (IBM - What is a Neural Network).

Generative AI can learn from existing artifacts to generate new, realistic artifacts (at scale) that reflect the characteristics of the training data but don’t repeat it. It can produce a variety of novel content, such as images, video, music, speech, text, software code and product designs.  Generative AI uses a number of techniques that continue to evolve. Foremost are AI foundation models, which are trained on a broad set of unlabeled data that can be used for different tasks, with additional fine-tuning. Complex math and enormous computing power are required to create these trained models, but they are, in essence, prediction algorithms. (Gartner - What is Gen AI).

 

 

Below is a recording of a recent UNM panel discussion of how AI may shape public discourse around elections.

 

 

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