Experimenting With AI Part 2
Going forward, if I write any more posts about my use of AI, I am not going to add the following caveat. I will do it once more here, so everyone knows where we all stand. I am fully aware that AI has already taken jobs and will continue to do so. I also know that data centres are not environmentally friendly. As for the evil corporate billionaires that get rich from the situation, that also has not come as a surprise to me. I also believe that the AI market needs regulating and there should be legislation in place to ensure that AI is never directly linked to important government and civil infrastructure. That being said, I am not going to stop using AI at a domestic level over notions of ethical purity. All of the above criticisms can broadly be applied to the industrial revolution and society came to terms with that and survived it. The same goes for the computer revolution. Things change and we adapt. Plus, if you really wanted to protest and lobby against AI, the best time to do this was two decades ago.
Experimenting With AI
For the last few months I have being using Google Gemini. I subscribed so I could access a wider spectrum of services and evaluate it effectively. I also wanted to dispel some of the hysteria that accompanies any conversation about Large Language Models and Artificial Intelligence. The results were initially interesting and Google Gemini proved useful when researching material for blog posts. It is good at providing summaries about well documented subjects. I wrote a post about food banks recently and it distilled a lot of data into a manageable amount, which was ideal for my article. Google Gemini has also produced some visual basic scripting and simple batch files that have allowed me to automate processes on my PC. Such as changing the default monitor, or screen resolution at the click of an icon. However, I found this AI struggled with in-depth software troubleshooting and that its ability to create images varies greatly depending on the subject.