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Do you feel that AI is like rocket science? Well, it's not.

Updated: Feb 16

The idea that tools like ChatGPT, Google Bard, and various image generators seem almost alien is quite understandable. However, the reality is that when we peel back the layers, it all makes complete sense. These AI innovations are grounded in principles that are accessible and relatable once demystified. So AI is, in fact, not rocket science.

Written by: Victoria Andersson


A smiling robot with AI written on the chest looking at a laptop.
Image: Unsplash
Unveiling the Friendly Face of AI

Let's clarify one thing before we start: AI isn't about to take over the world. Essentially, AI splits into two types - ANI and AGI. The type of AI that's rapidly advancing today is known as weak AI, or ANI, and it’s exceptionally good at playing by the rules – quite literally. It's specialized, task-oriented, and a bit like that one friend who's an encyclopedia of knowledge on one topic, yet can't seem to change a light bulb. When most people think of AI, they're actually imagining AGI, a theoretical AI that thinks and learns like humans. But this isn't our reality yet, nor the focus of current developments.


It all starts with data, a lot of data

The heart of today's AI systems beats with a rhythm set by data. It's the fuel that powers the intricate engine of ANI. Just like an artist needs paint, AI needs data – and not just any data, but vast, diverse, and quality data. This abundance of data enables AI systems to learn, adapt, and excel in their designated tasks. In the world of AI, data isn't just king; it's the entire kingdom.


Data + Machine Learning = The evolution of digital intelligence

Diving deeper into the AI realm, Machine Learning (ML) stands out as the star player, the most effective technique in building AI systems. ML addresses the critical question: "How do we get computers to learn from data without being explicitly programmed?" It 

empowers AI systems with the ability to learn from experiences, improve over time, and tackle increasingly complex tasks. Crucially, ML isn't a one-size-fits-all solution; it's a diverse umbrella encompassing various techniques, each suited to different challenges.



In the front, a coffecup with the text "This is working. In the back: a person working on a laptop.
Image: Wix
How AI learns to perform tasks independently

Peeling back the layers of AI's complexity, we find its core techniques in ML:

  • Supervised learning is like a guided tour; the model is trained with labeled data, learning to predict outcomes based on past examples. 

  • Unsupervised learning, in contrast, is akin to exploration without a map, where the model sifts through unlabeled data to detect patterns or clusters on its own.

  • Reinforcement learning is the adventurous cousin, learning by trial and error, making decisions and adjusting based on feedback. 


Extending this is generative AI, a sophisticated offspring of supervised learning, which goes beyond prediction to creation. Each technique is a testament to AI's logical foundation: give a model data, and it learns to perform tasks independently, debunking the myth of AI as incomprehensible “rocket science”.


Tech writer or not - embrace AI

AI marks a paradigm shift, redefining problem-solving and innovation. Adopting AI puts us at the forefront of this revolution, beyond just following a trend. In the realm of technical writing, embracing AI means tapping into a suite of smart tools that enhance writing efficiency and content quality. Imagine AI as a behind-the-scenes collaborator, refining language, aiding in creative content generation, optimizing for SEO, and offering insights from user feedback. This integration of AI streamlines the writing process, elevating the technical writer’s role from just crafting words to strategically shaping impactful content.



The words "no fear" written in handwriting on a glass surface.
Image: Wix
Our advice to you:

At the end of the day, AI refers to the development of systems capable of tasks that usually require human intelligence. But here's the twist – whether you're a tech writer, a marketer, or a project manager, instead of fretting that AI will usurp your job, focus on how it can enhance your daily tasks. 

AI isn't here to snatch away our roles; it's here to redefine them.

It's not about AI taking our jobs; it's about AI taking the jobs of those who don't embrace it. 




If you want to learn more about AI: https://www.deeplearning.ai/.


If you're looking to find AI tools tailored to your profession, visit https://genai.works/  - kind of a one-stop destination for all leading AI applications and software.

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