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There is a lot of noise around AI. Even though it was an ambiguous topic in the past, it has become unbearable nowadays. People throw AI in their startup names, and companies rebrand their products…

The whole situation is very similar to what I’ve seen before. It reminds me of two technological shifts. The first was Agile, which appeared after many project failures caused by limitations with the previous way products were created. The second was Microservices, a revolution built on the Cloud trend. Sadly, both concepts were destroyed by marketing and big corporations.

Agile coaches are only hired to mask the inability to identify and fix deeper problems, and microservices are a go-to term for many services floating around with some duplication in functionality. Agile caused a spike in firing architects. On the other hand, microservices and DevOps trends, together with misunderstanding how startup culture can be adapted in tech companies, caused reinventing the wheel and minimized the network effect.

With these two events in mind, I want to avoid even imagining what will happen to AI and all Data Science, Machine Learning things. However, money drives the technology so companies will invest lots of money in AI. I’m expecting AI coaches and certification path soon. Therefore, it is a must to know the fundamentals: of math (probability, statistics, calculus) and python for any engineer working on the same building as Data Scientists.

Another danger I can immediately see is the even lower quality of books, magazines, etc., as most of them will be generated by generative pre-trained transformers. Additionally, all the graphic designs and covers will be too. It is a scary world when we are not any more creative but only blindly consuming what silly algorithms with 60% accuracy offer to us. It does not have to be like that; if we move the time from tedious activities to time devoted to being creative, it can give us a competitive advantage, which would be more accessible than ever, as silly tasks can be outsourced to AI. But to do this, we need to withstand the noise and resist blindly jumping on the bandwagon of AI. Instead, start learning what your company produces in terms of data and treat data as a valuable commodity like gold. Think about where to store and protect them and how to expose them to appropriate users easily. After that, apply the principle of the least power to choose the suitable model to follow.

For creators, it is essential not to ignore “AI” but use it and redefine current workflows. We do not need to apply Chat GPT in anything, but only to some of our less bespoke tasks where we do not require emotions and creativity, keeping the essential parts for humans. For software developers, it means asking your bots about something but still googling the topic simultaneously. In the end, compare your experience + traditional search + bot answers to find the best way to go.

For consumers, it is more romantic, it means still subscribing to authors and companies we like and share values with, even though their emails have typos, and book covers are less shiny than those generated by AI. Even though songs won’t be so readily available on your smartphone, and performances are only viewable in person, Keep doing THAT, even MORE than earlier.