The Effective Utilization of AI: Focusing on Large Language Models (LLMs)

An artificial intelligence (AI) system can automate repetitive tasks such as data entry, thereby increasing productivity while reducing errors associated with manual tasks. AI also excels in analyzing vast amounts of data to identify patterns and trends, making it a powerful tool in various industries. Specifically, AI can help with generating content for social media and online platforms, creating business logos, and editing and creating videos. Additionally, AI can aid in content writing and fiction writing, providing brainstorming ideas and extensive editing.

The term 'AI' is often ambiguous, and in this context, I will discuss Large Language Models (LLMs). LLMs, which are a subset of AI, are less powerful and more narrowly focused than the popular perception suggests. They excel in specific tasks but are not well-suited for a wide range of other activities.

The Limitations of LLMs

LLMs are not adept at performing many tasks, and even when they can, their performance is often subpar. Despite this, my preferred method of utilizing LLMs is as a search engine. LLMs are incredibly valuable when you are learning about a new area and need to ask rapid-fire questions in quick succession. This efficiency is demonstrated through a concise conversation that highlights their utility.

A Practical Example of LLMs as a Search Engine

Imagine having a conversation with an LLM about npm, a package manager for Node.js. The exchange would go as follows:

You: How do I find out where npm installs nodejs packages?

LLM: You can run `npm root` and `npm list` in your terminal.

You: What's the difference between those two?

LLM: `npm root` shows the directory where your node packages are installed. `npm list` lists the actual packages.

You: Do I see the global root or the one for my current project?

LLM: `npm root -g` will show the global root. Without the `-g` flag, it shows the local project root where local packages are installed.

You: Does that work for `npm list` too?

LLM: Yes, you can run `npm list -g` to list global packages.

You: What determines the output?

LLM: It looks for the nearest `package.json` or `/node_modules` subdirectory in the current directory.

How much time would you need to spend browsing documentation to find this information? How much reading would you need to do to find just a few specific data points? By simply typing commands like `man npm` or `npm help`, you would not find the required information in either case. A quick Google search may lead to directories that do not contain your packages.

This example illustrates a significant advantage of LLMs over traditional search engines. They allow for rapid-fire questions, which can help you learn quickly about a new subject. Thus, while the capability of LLMs is limited, their efficiency in specific scenarios can be highly beneficial.

In conclusion, while the term AI can be ambiguous, focusing on LLMs as a search tool can significantly enhance the learning process and problem-solving capabilities, especially in technical and specific domains.