Something Ends, Something Begins - Learning ML with Deep Learning for Coders Intro

Embracing Change: Reflecting on the Past and Looking Forward to the Future

Some things come to an end, while other begin - that's what was on my mind when I started writing this blog post. It's also the beginning of a new year, which marks some changes in my life and also the changes in the whole IT industry. What's more, I would like to dedicate this post to my grandmother - who I lost on the day of writing this post. She is a huge inspiration for me as she was World War II survivor, experienced a lot of tragedies in her life, witnessed a lot of changes in the world, but she managed to keep up with her life and constant changes quite well. Born before World War II, in times when still so many people used to ride horses, when cars and TVs were known but they were rather a luxury, and something that only certain people could afford. Now, we have smartphones, smartwatches, smart TVs, and even smart fridges. We have the Internet, social media, and so many things that we couldn't even imagine 50 years ago.

The Rapidly Changing Landscape of the IT Industry

A couple of years ago when I was starting my web-development learning journey, I recall that JavaScript was still very popular, as well as class components in React. Fast-forward to 2024, and I have a feeling that most of the IT industry switched to TypeScript (even though we have some dramas from time to time), as well as I haven't seen much class components in React anymore. Those are just a few examples of how fast the IT industry is changing, and how important it is to keep up with the changes. However, it's also important not to get too much over-hyped about the new technologies, and to be able to distinguish between the hype and the real value. In the recent years we had a several examples of over-hyped technologies, that in the end didn't bring much value, and were just a waste of time. What's more is that especially people with less experience in the industry, tend to get over-hyped about the new technologies, and they tend to jump on the hype train without even thinking about the real value of the technology. It happens especially when we don't have a strong understanding of the programming fundamentals, and a strong understanding of the technology that we are using.

Reflection on Technology Trends: Prioritising Impact Over Hype

Some of you readers may recall my previous articles or YouTube videos, where I enthusiastically embraced various tech trends like blockchain, smart contracts, and cutting-edge frontend frameworks. Despite the valuable lessons learned, numerous hackathon victories, and even co-founding a startup, I can't help but feel that many of these ventures lacked the necessity of reinventing the wheel and failed to deliver significant value. Ironically, one of my earliest creations, the Student Portfolio Grade Calculator, left a more substantial impact and demonstrated a more practical use case than the dozens of sophisticated apps I developed later on. Consequently, after these experiences, I made a conscious decision to step back, maintain a healthy distance from the allure of new technologies, and take an extended break from content creation. Instead, my focus shifted towards reinforcing the fundamentals and closely observing the industry.

Unveiling the Practicality of AI and Long-Lasting Innovations

Over the last couple of years, and even decades, numerous technologies have emerged with promises to revolutionise our world. However, many of them fell short of practicality and failed to address real-world problems. On the flip side, technologies like the Internet, smartphones, and social media platforms have undeniably reshaped our lives, offering efficient tools that prove challenging to replace. Where does AI fit into this narrative? I'll leave that judgment to you, but consider that the concept of AI, particularly the underlying machine learning principles, has been around for years. It didn't materialise suddenly; rather, it has existed in various forms, solving real problems throughout its evolutionary journey.

Taking Action: Navigating the Rapidly Evolving Landscape of Artificial Intelligence

Last but not least, what can be done about this? Should we just ignore AI, go all-in on hype about this technology, panic that it will replace us and even destroy the humanity, or maybe it's better to get to know the concept finally a bit better and prepare ourselves for a new era? I personally think that the last option is the best one, and that's why I decided to write this article. I would like to share with you my journey of learning AI and Machine Learning, and also show you how to build something practical and useful with this technology. Let's get started!