After reading this piece on CNBC’s website regarding how students should be using AI (I still prefer the term LLMs for purposes of nobody can identify what AI is and isn’t), it’s making me consider what today’s youth is learning with respect to preferential employment skills moving forward.

First consider the interviewer. Jesen Huang’s goal is to sell as many customers on GPU compute and resources as humanly possible given his field so we must take that with a grain of salt. Secondly, the tools of LLMs are a must have in today’s educational and workforce. If you aren’t utilizing prompting to the fullest extent; you are already falling behind. Take the time to find an online course through EdX or Coursera, for example, to home in these skills.

Huang stated:

Learning how to interact with AI is not unlike being someone who’s really good at asking questions,” he added. “Prompting AI is very similar. You can’t just randomly ask a bunch of questions. Asking AI to be an assistant to you requires some expertise and artistry of how to prompt it.

Like all tools, they must not only be learned but practically used. Using a tool for the sake of it, creates more problems and diminishing results will follow.

We also must question whether the idea of learning how to code is vital for today’s computer science programs. I still argue yes! If we blindly follow output from a chatbot, we lack the ability to understand what the code means, if it works, or how useful it is to the original prompt. “Is this what the client actually asked for?” or “How can we implement this?” are two major questions that will never go away. Just like Wikipedia was and is a tool as a basis for research and learning, chatbots, and LLM products should also provide this starting point. As always, check the source material as like Wikipedia, bias and humans still intervene in the research and results that an LLM product provides.

The part that Huang really gets correct is as follows:

Perfecting AI prompts — and asking better questions in general — is a skill that will remain relevant for years to come, so students should take the time to develop it, no matter what career field they see themselves in.

A large amount of Academica is yet to be versed on Large Language Models as a whole and prompting is still new to those set in their ways. Aiding in research is paramount to have a companion in the room that makes learning easier and the consumption of knowledge more streamlined.

We have a long way to go as a society between those who are skeptical of LLMs at all costs and those who talk to it and treat it as it’s a human being with real thoughts and valid feelings. The battle between skeptics vs. accelerationists is not one we should be having; but a moderating position to accept them as tools that we all must learn to be successful in any career or academic endeavor; no matter what areas of study we choose to pursue.