The Best AI Articles of October 2022

Here are the five articles you have to read if you are learning about artificial intelligence or simply interested in expanding your knowledge in this field.

This article was sponsored by HackerNoon, which means the articles you will see were all published on HackerNoon by amazing individuals, some of them from our community. Still, I carefully selected my personal top five amongst hundreds of other super interesting ones that you might enjoy even more. So please feel free to look at the AI tag on HackerNoon to see similar articles and keep learning!

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Before we get into it, please let me know what you think of this format by liking and commenting if you'd like it to become more regular! One last thing before we get into it, note that this top five is in no particular order, and I just really liked all five articles and wanted to share them with you as I think they are valuable to anyone in the field.

In this article, Berk gives a great introduction and overview of the support vector machine or SVM algorithm. It is something taught in most introduction classes at university and that you should definitely learn about if you haven’t yet.

He goes through the useful terminology, continues with a more in-depth explanation of the most important ones like kernels, and goes further with applied regression and classification examples with the code you can replicate as well in a notebook.

This fourth article is quite different and very interesting as the author covers an application of AI in the real world. And not any application but one of the most important ones to humans: safety.

We learn about a startup called Intenseye, leveraging AI to detect any unsafe conditions using existing cameras and other health and safety use cases, which you will learn about in the article. There are a lot of very interesting applications. It’s a great article to share if someone asks you the question, “AI is cool and all, but what does it really do for us?”.

Yes, this is another article written by Berk. It seems like you should definitely follow him if you want to keep learning important concepts in this field. In this article, Berk covers decision trees. One of the most known and used supervised algorithms.

He once again uses the same format with a clear introduction, going more in-depth with specific terms and code examples you can replicate. It is definitely worth the read, especially if you’ve never heard about decision trees.

In this article, Maximilian covers how much designers and researchers actually use AI tools to support their work. In fact, it seems like most of them do not know which tool can be used to improve either their efficiency or quality of work. This is analyzed through a study the author and his colleagues did with the aim of answering two questions:

Do practitioners indeed not have the time and resources to follow proper design processes? and, more importantly

If you want to know, have a look at Maximilian’s article! It is very interesting and well-written.

Without spoiling the whole article, there seems to be a lack of awareness of how AI-powered tools can help professionals, which is probably generalizable to all fields. Designers are willing to try AI-powered tools and are enthusiastic about them!

The last article of this top five of the month! Here the author covers a recent and very important problem: automatic content generation. Ranging from text to music and art, the author brings us into a thought experience where everything is AI-generated, and no distinction can be made between AI- or man-made content.

He brings up a lot of very interesting points regarding AI-generated content and how powerful, and even dangerous, it will become. I just want to warn that it is definitely towards the pessimistic view. Still, these are very interesting thoughts, and the author is definitely a great writer!

If this topic also interests you, you should definitely read this piece and check out this week's iteration of my newsletter, where the fantastic Lauren Keegan works with me to share opinions and knowledge about the ethical side of the papers that I cover here on the channel. In this week's iteration, Lauren discusses a free topic of her choice relevant to a Hackernoon article as well, and it's captivating as always!

Thank you for watching the whole video, and I will see you next week with another amazing paper! If you can’t wait until then, you can follow me on Twitter and see even more cool AI-related content daily!

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5. What is a Support Vector Machine? by Berk Hakbilen. https://hackernoon.com/what-is-a-support-vector-machine 

4. How AI is Making Workplaces Safer by Aremu Adams Adebisi. https://hackernoon.com/how-ai-is-making-workplaces-safer 

3. What are Decision Trees in Machine Learning? by Berk Hakbilen. https://hackernoon.com/what-are-decision-trees-in-machine-learning 

2. 99.9% of Content Will Be AI-Generated by 2025: Does Anyone Care? by Voozle. https://hackernoon.com/999percent-of-content-will-be-ai-generated-by-2025-does-anyone-care 

1. What Needs to Happen Before AI Becomes a Thing in Design and Research by Maximilian Speicher. https://hackernoon.com/what-needs-to-happen-before-ai-becomes-a-thing-in-design-and-research