When I first started exploring the possibilities of AI, I thought acquiring new skills, especially in fields like programming, would be much quicker. The idea of using AI tools to speed up the learning process seemed like a game-changer. I imagined that understanding complex concepts and mastering new languages or techniques would take far less time. However, practice has taught me that it’s still not as easy as it seems.

While AI certainly makes knowledge more accessible, the journey to truly mastering a skill still requires a great deal of effort. This has its ups and downs. On the positive side, it means that brain workers—those who can think critically, solve problems, and apply knowledge—are more valuable than ever. On the downside, it also means we need more patience and a sharper approach to using AI tools effectively. It’s not just about using them, but using them cleverly, to truly unlock their potential.

In the future, I believe we’ll see even more radical polarization among people. There will be a small group of individuals—“superhumans”—whose intelligence will far surpass that of their peers. These people, much like intellectual giants such as Dirac and Einstein, will possess cognitive abilities that seem almost otherworldly in comparison. Meanwhile, the majority will fall increasingly behind. Even though AI will be accessible to everyone, many will struggle to leverage its true potential, using it only for mundane tasks like booking hotels, rather than tapping into its capacity for deeper learning and problem-solving.

This growing divide between the “superhuman” few and the rest of society could redefine what it means to be truly innovative, as those with the ability to use AI creatively will shape the future, while others may find themselves left behind, unable to catch up.

At its core, the future of problem solving will revolve around tackling the world’s most pressing challenges: curing cancer, developing sustainable energy solutions, and exploring space beyond Earth. As technology, particularly AI, advances, these monumental problems will require innovative thinking, collaboration, and the ability to harness new tools in ways we haven’t yet imagined.