Whatever you are studying right now, if you are not getting up to

When Mark Cuban declared, “Whatever you are studying right now, if you are not getting up to speed on deep learning, neural networks, etc., you lose. We are going through the process where software will automate software, automation will automate automation,” he was sounding a trumpet of transformation, a warning to all who dwell in comfort while the world shifts beneath their feet. His words are not those of mere commerce or competition—they are the words of a seer who perceives the coming age, where intelligence itself becomes the engine of creation. Like the prophets of old who warned kings of storms unseen, Cuban calls out to a generation lulled by habit: awaken, for a new order is rising.

In the modern age, where machines once obeyed and now begin to think, Cuban’s statement takes on the power of prophecy. He speaks of deep learning—the discipline by which machines teach themselves, growing not through commands but through experience. He speaks of neural networks, the architecture modeled after the human mind, where layers of logic and perception weave together to form artificial understanding. And he warns that we are entering an era where automation itself will create new forms of automation, where human invention may no longer be the sole architect of progress. To ignore this transformation, he says, is to fall behind—not in wealth alone, but in relevance.

The ancients, had they seen such times, would have likened this to the forging of fire. When Prometheus brought fire to mankind, it changed the fate of civilization—warming the body, forging metal, birthing the dawn of knowledge. But fire, too, was dangerous; those who feared it were left in darkness, and those who misused it were consumed. So it is with artificial intelligence today. Cuban’s words remind us that this new fire cannot be ignored. The wise will learn to master it, to shape it for creation and compassion; the foolish will stand idle and watch as it reshapes the world without them.

Consider the story of John Henry, the steel-driving man of legend, who raced against the machine and died in the contest. His tale was born in the industrial age, when labor gave way to the power of steam. Henry’s strength was mighty, but the machine’s endurance was endless. In the same way, those who cling to the old ways of learning—who rely only on rote knowledge, who refuse to adapt—will find themselves outpaced by algorithms that learn faster, think deeper, and work without pause. Yet Cuban’s message is not despair, but awakening: he calls not for surrender to the machine, but for humanity to rise with it, to learn, to grow, and to lead in harmony with the intelligence it has birthed.

His warning also carries a moral dimension. For as automation automates automation, as machines begin to create and manage their own systems, the human spirit must evolve beyond mere labor. Cuban’s insight reminds us that our value lies not in repetition, but in imagination. The human gift—the capacity for empathy, for creativity, for moral discernment—must now stand beside the power of computation. The ancients would call this balance logos and ethos—reason and spirit united. To study deep learning today is not simply to learn a trade, but to understand the future language of power. To ignore it is to become voiceless in the councils of destiny.

And yet, beneath the urgency of Cuban’s words lies a deeper hope: that humanity may learn from its own creation. For if software can automate itself, perhaps we, too, may learn to renew ourselves, to shed old ignorance and awaken new understanding. Just as the Renaissance followed the rediscovery of classical wisdom, this age of machine intelligence may yet lead to a renaissance of the mind—a world where knowledge is abundant and creativity unbounded. But such a dawn belongs only to those who prepare for it, who study, adapt, and think not with fear but with vision.

So let this teaching be carried forward: do not flee from the future—learn its language, master its tools, and shape its purpose. The world is entering an age where thinking itself is mechanized, where every discipline—medicine, art, philosophy, and science—will be touched by the hand of machine learning. Those who resist will fade like the artisans of a forgotten craft; those who adapt will stand as pioneers of a new era. Train your mind as Cuban advises: embrace deep learning, understand neural networks, and let your curiosity lead you through the unknown. For the day will soon come when automation creates its own descendants, and when that hour arrives, only those who have learned to grow alongside it will still be truly alive.