Colossal hype ensues whenever there's progress or even the slightest shift in the world of machine learning (ML). When it comes to AI, the craze always ends up growing out of proportion and insane claims invariably follow. You've probably noticed this recently as more people are beginning to use Midjourney, ChatGPT, Copilot, and so on.
The truth about these systems, however, is always more prosaic. Machine learning is mathematical, and the real implications of the ML models are not nearly as profound as some bloggers would have you believe. They could be beneficial and, in some cases, transform large portions of workflows in specific areas, but only if the user, whether an organization or an individual, has a sufficient understanding of their inner workings, limitations, capabilities, and potential.