Dear Reader,

Good day and thanks for reading this edition of the CM Videos Insider Newsletter.

Here are the focus for today:

1. Technical Reflections: Code Interpreter and Computational Modelling
2. Behind the Scene at CM Videos: Where I get my graphics/art work.
3. Quote of the Week: Identity and Habit

Technical Reflections

Code Interpreter and Computational Modelling

In a recent newsletter which you can read here, I speculated on the impact of AI tools (like ChatGPT) on computational modelling. After that, I got to know about this GPT-4 plugin called: Code Interpreter which is accessible on the inventor's (OpenAI's) website here. I was pleasantly surprised what it can do and want to reflect today on how I see this affecting computational modelling.

What is Code Interpreter

According to the developers at OpenAI,

As plain a definition as that may be, Code Interpreter is essentially a plugin which runs on the GPT-4 large language model system. It runs a Python interpreter which works with text prompts and file uploads to carry out specific tasks. It can generate text outputs (as traditional ChatGPT) but also can generate downloadable image outputs. It is proving a very powerful addition to the ever increasing library of GPT-4-enabled plugins available for carrying out computational modelling work.

What can Code Interpreter do for the Computational Modeller?

From my initial basic assessment of Code Interpreter, here are some of the major features/capabilities of note for computational :

Final Reflections on Code Interpreter and Computational Modelling

I do see Code Interpreter as yet another wonderful addition to the basket of plugins that users should better engage with. There is the clear fear that it might be the end of jobs for the data scientist, and whilst that might be concerning, I do not see it to be so. Instead, it can help the data analyst quickly generate trends in their data. They will then have to do the in-depth evaluation and interpretation of what the data is telling them and their organization.

For the computational modeller, the used cases indicated above will certainly not mean the death of the modeller. If anything, it can complement what we already do in computational modelling especially in the STEM fields. It is certainly going to balance the playing field between those who have access to a large workforce of data analysts and those who have little. It is democratizing the availability of experts who generate excellent conclusions on data. This can only be good.

However, it will certainly open up a new workforce who are those who develop the right prompts to extract valuable data from the Code Interpreter. Therefore, the skillset for the computational modeller worth developing is the skill of understanding the usefulness of these plugins, and being imaginative in how we interact with it for the best output. We should also develop the ability to generate, extract, and locate the right data resources that we will need to give to these AI plugins.

I will be reflecting more on this and hopefully make a video showing how some of these used cases explained here can be demonstrated. If you have any suggestions for me in this regard, I will be happy to hear them.

Behind the Scene at CM Videos

Where I get my graphics/art work

You might have realized on this newsletter and also in the YouTube channel, I have a thing for graphics. I like to convey the thoughts behind my reflections using an image. Getting high quality images without falling foul of the copyright laws is difficult.

This is why right from the start of my YouTube and content creation journey, I understood the need to pay for this service and therefore never worry about this. So, I currently subscribe to the Pro license of Canva.

With this tool, I am not going to worry about copyright issues. It has a large library of images and videos with templates to help any user at any level of expertise to create some of the most amazing art work. It is very popular among content creators and social media influencers.

For students, there is a academic license version that you can access with a school/university email address. Here is a link to access Canva for Students. Also, I recently demonstrated how I used it in designing a poster presentation for my students in a final year project module that I am responsible in my university. If you are interested in this, then do watch the video below.

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CM Videos

Identity and Habit by James Clear

I am taking the quote for the week from the book - Atomic Habits - by James Clear. The book - Atomic Habits - is a New York bestseller and this is not surprising as it contains a lot of really interesting advice to help many become more productive. Here is the quote:

Two keywords are worth considering here: identity and habit. Of course we know habit is what you do regularly and such becomes your norm. Identity is who you are - what personality, you want to show and people know you as. So, according to James, your identity (who you are and what people recognize you as) emerges/proceeds/comes out of what you do regularly (your habit).

For example, if I want to be known as a computational modeller (my identity), then I must be busy doing those things that computational modellers do i.e. be entangled with the habit of computational modellers and that includes: numerical analysis, computational work, data visualization, predictive modelling and even understanding the theoretical pillars upon which computational outputs stand.

The implication for you is that if you want to be known for a given identity, then recognize the habits that define the possessors of that identity. If you want to be a first class student, then you must read and study quite a lot. If you want to be a writer and publisher of books, then you must write - whether for a large audience or a small audience. One of the reasons why I write this newsletter is because I like writing and see myself as author of thoughts about computational modelling.

In deed, you become the identify that was fashioned by the habits you are persistently involved in.

That brings us to the end of this newsletter. I hope you have enjoyed it and we will come back next week with another edition of the newsletter. In the mean time, I wish you well and do leave me any feedback you want to give me about the thoughts reflected in this newsletter.