There is a video version of this post in my YouTube Channel. So we have our boilerplate app, and we are ready to start adding fun stuff. If you do not have that, check the part 1 of this series. We will start by making sure we have Semantic.Kernel in our usings: using Microsoft.SemanticKernel; Now we will configure the “Kernel”, which as the name says is the heart of SK (Semantic Kernel). We will add this to our services configuration helper method:

I’ll keep this short and sweet since there’s already gazillions of information about Large Language Models (LLMs) and artificial intelligence (AI), and I doubt I’ll contribute anything novel to the discussion. This post aims to put in words this interlude video about LLMs and AI before adding the magic AI bits into our app. I will argue two things: 1) LLMs are a form of artificial intelligence, 2) They represent a rather limited form of intelligence that requires constant supervision. Following this, I’ll include a link on how to install these models locally.

ChatGPT and most AI systems have biases, often manifesting as racism and discrimination, mirroring the biases present in human society and hence in the data we use to train such systems. And look, I am excited about AI, but sometimes we are moving too fast without thinking in the consequences. Last week we had our team monthly lunch, and as in other ocassions we were talked about everything, ranged from topics as cane sugar industry, spicy food levels, skiing, and of course, AI. The small talk was about tips on using Microsoft Teams and Copilot to summarize what people said in a chat after prolonged absences from the office. This sparked an idea for an experiment.