It probably makes sense to know a little bit of the fundamentals of AI and machine learning before you jump headfirst into using it! While I don’t think the math or specific theories are very useful, you should at least know the vocabulary and have a vague idea of how these systems fit together.
In this section we’ll start by looking at what a model is, the most fundamental aspect of AI and machine learning. Every time you talk to ChatGPT or ask DALL-E for an image you’re actually talking to a model!
After testing out a few different pre-existing models, we’ll move on to how we can build our own models through training (or, more realistically: fine-tuning others’ more powerful models). This will also reveal the shortcomings of these tools, along with the difference between the older custom machine learning models and the newer “black box” AI-driven ones.
Finally, we’ll look at… I’m not sure how we’re dividing this up yet, honestly. But we’ll definitely have three sections!
So let’s do this.