Top Eleven Articles on AI this year

These days, there is a growing excitement about artificial intelligence and its potential benefits. Whether you support or criticize this technology, opinions and experiences are abundant. Our writers have explored this topic in depth. Jim Hall, who teaches technical writing at the University of Minnesota, was interviewed by his student, Aaron Barke. Jim has also researched generative AI in the context of technical communication. Jim emphasizes the importance of using AI responsibly. He advises his students to be cautious with AI-generated answers. Be sure to read the entire interview for a thorough discussion of the topic.

While machine learning is taking the world by storm, it cannot replace the community. Seth Kenlon writes about why AI cannot replace community. Large Language models like ChatGPT are not open source yet their algorithms have been trained on a host of material that all of us have put on the internet. Does this mean that ChatGPT has joined a community or is it merely a usurper? Seth also gave us five lessons we can learn from artificial intelligence. They are the importance of concise communication, asserting defensible truths, avoiding misinformation, citing credible sources, and taking feedback seriously. Be sure to read the entire articles for a closer look at the topic.

Don Watkins wrote extensively about his experience downloading, installing, and using open-source large languages from various sources. His first article was about downloading and using Llamafile from Mozilla. Developed by Justine Tunney, Llamafile is a locally hosted, open-source large language model designed for privacy-conscious users. The article explains how to install and run Llamafile, showcasing its versatility in generating code, content, and creative outputs through text prompts.

Never one to leave a stone unturned, Don continued to look for other opportunities to explore open-source implementations of artificial intelligence. That led him to discover Ollama.His first article dealt with how to download and install Ollama on his Linux computer. Follow his directions to get started with a locally hosted large language model.

Once you have downloaded and installed Ollama, you will want to explore how to download the various large language models (LLM) available. Working with Ollama provides an easy-to-follow guide about how to do that. Now that you have downloaded a few models you will want to begin learning how to use these models and we covered that in our first article about how to use Ollama and Phi3.5 model to help you improve your writing.

Continuing to explore open-source LLMs led Don to discover how to use Ollama and the Phi3.5 model, which led to an attempt at financial analysis using open-source artificial intelligence. This article provides an easy-to-follow guide on how that is accomplished. My exploration of Ollama and open-source LLMs led me to look for easier ways to interact with these models.

That exploration led Don to discover Hollama, a minimalist web interface for interacting with Ollama servers. Developed by Fernando Maclen and maintained by nine contributors, Hollama simplifies interaction with these open-source LLMs while leveraging Ollama’s power. The article also guides readers through the installation process on Linux and macOS.

Continued exploration led to the discovery of OpenWebUI, an open-source interface for large language models. OpenWebUI offers a robust, feature-packed, and intuitive self-hosted interface that operates seamlessly offline. It supports various large language models like Ollama and OpenAI-compatible APIs. Open WebUI is open source with an MIT license.

Just in time for the holidays, we published an article that provides a step-by-step guide for using open-source tools that rely on artificial intelligence to remove the background of existing pictures for inclusion in holiday greetings.