Series Preface to “The Ten Key AI Figures Who Are Changing the World”

This is not a set of biographies, nor a roundup of tech news, and certainly not a list for showing off how well you understand AI. What I really want to write is something else. In the past few years AI has become a word almost every industry cannot get around: listed companies are talking about it, small businesses are talking about it, teachers, creators, governments and investors are talking about it. Everyone knows AI is important, and everyone has a vague sense that this is not an ordinary technological upgrade but a deep change that is rewriting business, work, knowledge, education, power and even the way humans understand themselves. But what is interesting is that few people truly know why AI has come this far, by what forces it has been pushed here, and what worldview each of the different routes represents. Most people see the results: ChatGPT, all kinds of models, the sudden flood of tools, people using AI to write, draw, edit video, make presentations and code, companies beginning to feel anxious, to run courses, to adopt AI and to worry whether they are too slow. But few turn around and ask: how did all of this actually grow? I think this question is important, because if you only see results, it is very easy to treat AI as a fad. You will chase tools, features, model versions and market hotspots, chase this today and that tomorrow, looking very busy while never truly building understanding. But if you start to look back at the people — those standing in different positions, representing different routes, pushing different structures — you will find that AI is not a single story at all. It did not grow from one company, it did not rise on one viral model, it was not stacked up by compute alone, it was not advanced by academic breakthroughs alone and it was not merely hyped by the market. It is in fact a very large map: some people pushed AI into the mainstream market; some pushed the research engine to its depths; some treated AI as civilizational engineering; some put safety and controllability at the core; some pushed research teams toward organization; some turned AI into an entry point and a home field of attention; some brought AI into enterprise workflows; some provided the compute foundation of the whole era; some opened up the open-source ecosystem and the question of sovereignty; and some, many years ago, quietly laid the foundation on which all of this stands today. So what this series, “The Ten Key AI Figures Who Are Changing the World,” really wants to address is not only “who is impressive,” but, through ten people, to show you ten roads — ten roads that are rewriting humanity’s future. I want to write not only what they did, which would be too shallow, but even more: what do they believe? What is the philosophy behind them? Is what they advance only technology or some worldview? What do they mean for the future of humanity? And how should we critique them, understand them and learn from them, rather than worship them blindly? Because any truly weighty figure is not just a résumé; he is himself a route.

In the Sam Altman piece, I wrote not about a CEO but about an accelerator who pushed generative AI into the mainstream market and pushed humanity into a new era of coexistence with intelligence — the force of “throw the future into reality first, then force the world to learn to adapt.”

In the Ilya Sutskever piece, I wrote not about a low-key genius but about a faith in deep research: those who truly change the world are not necessarily the loudest, but often those who, at the bottom layer, push a structure to its critical point.

In the Demis Hassabis piece, what I wanted to discuss was not the leader of a research institution but a long-term vision that treats AI as civilizational engineering; he reminds us that AI is not only an efficiency tool but may also be a new infrastructure for humanity to explore the world.

In the Dario Amodei piece, what I want to discuss is not conservatism but maturity: when everyone is chasing something stronger, he forces us to face one thing — capability without boundaries may backfire on the world.

In the Daniela Amodei piece, I wrote not about a behind-the-scenes manager but about the force of uptake. She reminds us that truly mature AI has never been the lone work of a few geniuses, but depends on whether it can be caught in an institutionalized, organized and scalable way.

In the Elon Musk piece, I did not write only about which model he built but about how he understands entry-point power: AI is not only a smarter tool but may become the new doorway through which humans touch the world, understand information and form a sense of reality.

In the Satya Nadella piece, I wanted to write not about an enterprise-software upgrade but about how the modern organization is redefined: what truly changes the office is not one more AI feature but the rewriting of the starting move of the entire workflow.

In the Jensen Huang piece, I wrote not about a chip star but about infrastructure power: AI is not only a contest of models; behind it lies a contest of structure in compute, energy, scheduling, supply chains and physical reality.

In the Mark Zuckerberg piece, what I really want to discuss is control over intelligence. Is future AI a rental product of a few platforms, or a capability that most companies and communities can also gradually hold? This is not a technical detail but the politics of ownership in the age of intelligence.

And with Geoffrey Hinton, I wanted to write about something deeper: patience. All of today’s AI
enthusiasm ultimately stands on decades of long-term research that was not understood; without such people, civilization would have only wave crests and no foundation.

So if you treat this series merely as an introduction to AI celebrities, you will read it with a lot of regret. What it really wants to do is take you through names to see structure; through events to see routes; through products to see civilization. I especially want to write this series for several kinds of readers.

The first kind is business owners.
Not because business owners understand AI best — quite the opposite — but because business owners most need to make judgments amid chaos. You don’t necessarily have to build models yourself, but you must see clearly which forces are behind this change, which are fireworks and which are skeletons, which are short-term excitement and which are long-term floors.

The second kind is organizations that are adopting AI.
What many companies lack most now is not tools but understanding. When understanding is insufficient, adoption becomes procurement; when understanding is deep enough, adoption can become system rebuilding.

The third kind is everyone whose way of working is being changed by AI.
You may be a creator, consultant, manager, researcher, salesperson, educator or entrepreneur. The earlier you see that this change is not a single product but the convergence of a whole set of civilizational forces, the less likely you are to stay merely in passive adaptation.

The fourth kind is myself.
Because writing this series is, to some degree, also organizing my own understanding of this era.

I have always believed that an article truly worth writing does not merely arrange information neatly; after reading it, the reader should feel their perspective has been lifted one level. You may not immediately get an answer, but you begin to know what questions to ask. I think this matters more than answers, because what the AI era lacks least is answers; what it lacks is judgment. Tools will keep multiplying, models will keep getting stronger, platforms will get better and better at persuading you, and everyone will tell you that they represent the future. But truly mature people are not led around by momentary volume; they look back at structure, at the foundation, at routes, at the distribution of power, at philosophy, and at where humanity will ultimately be taken in this technological revolution.

This series, “The Ten Key AI Figures Who Are Changing the World,” is written along this line. It is not meant to deify these ten people; quite the opposite — it is meant to put them back into the context of history, industry and civilization and see them clearly again. Because only by seeing clearly will you not merely follow the crowd; only by seeing clearly will you have a chance to truly make your own choices. And that is exactly what is most precious in the AI era: to keep your own judgment when the great wave has already arrived. This is the real starting point of this series.