How to Learn about AI for Non Technical Users

How you should approach learning about the most powerful ideas in AI if you're an investor, manager, policy maker, sales rep, etc.

The following article will be the next installation on our series on how to teach yourself AI. Previous installations, such as the very popular “How I taught myself to get cutting edge in AI”, were mainly geared towards people who want to develop the technical expertise to build the systems. Applying their methods to nontechnical people would be overkill, especially given other commitments like jobs, families, side businesses, hobbies, power struggles, possible coups, etc.

Hopefully this is what atleast one of your lives end looking like.

A carpenter does not learn how to build how to build hammers. Taylor Swift makes some pretty dope music w/o (I assume) deep knowledge of how audio is stored or streamed (I’m not a “Swiftie”, but All Too Well is a really good song). We interact with the internet w/ no understanding of how it works. However, many people have fetishized AI to the point where it’s not uncommon to hear that the only mark of true understanding is to be able to implement everything from scratch w/o libraries. This has, unfortunately, tricked many poor PMs, Sales Reps, Investors, etc into doing AI Certifications.

How we feeling about Naruto? Imo, very overrated show (Bleach is the best of the Old Big 3, fight me), but this meme format is still elite

The “learn to build things from scratch” mentality is propagated by people with nothing better to do and colleges that want to overcharge students for minimally “new” versions of textbooks w/o taking the time to update their courses. It is generally a massive waste of time and energy for anyone, but it is especially harmful to non-technical folk. Time is our most scarce resource and many of you won’t benefit from learning every little detail about the algorithm.

From our how I learnt AI article mentioned earlier. Courses, which are slow to adapt truly relevant ideas in modern AI will be even less useful to non-technical people who will 1) often lack background to fully appreciate the prereqs like brackprop 2) won’t interact with the low level enough for the time ROI to be worth it.

The purpose of this article is to give you a more efficient learning guide that will trade-off mathematical rigor for a massive time/mental effort saving. Following this guide will not allow you to start replacing developers or reading papers with the same depth as a researcher. It will help you with the following-

1. Developing enough insight to better interface with users, industry trends, and developers.

2. Being able to sniff out BS and be more robust to the AI Hype (both positive and negative).

3. Developing a practical framework to keep up with AI and its developments without turning into an Eren Yeager style crash out.

To do so, I will give you 3 action-based learning techniques that will tie into each other combined will give you a strong background in learning how to use AI.

If that interests you, keep reading.

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