There’s no question that the world looks different than it did just a few short years ago, and that a lot of this has to do with the awe-inspiring power of AI. Now, experts and analysts from all sorts of places, from business and government and academia, are trying to figure out how our collective landscape has changed, and how that’s going to continue in the future. You can get a sense of this from private businesses like Nvidia, which is responsible for the lion’s share of AI hardware, or from institutions like the IMF (this post is from last year) or from a broadside from the U.S. White House referencing a “Great Divergence” and promising that we will be led to the front of the global race for AI.
All of this shape-shifting begs the question: how? And why? And through what avenues will we behold the greatness of future models and agents? How will they be powered? And how will they be trained?
You can also check out recent panels like this one from Imagination in Action at Davos, where David Rubenstein of Carlyle Group met with Eric Schmidt from Google and Joe Ucuzoglu from Deloitte to talk about the “rewiring” of our world with AI.
Early Business Efforts
Since Schmidt hails from Google, which was a front-runner in the AI race, and banked on its prior dominance of text-based internet search, he was asked when Google actively started working on AI.
“Larry Page’s PhD subject was AI,” Schmidt said. “So even when Larry started the company, he wanted to do relatively interesting things with AI. And the first real use of AI was: we used AI to improve our ad system performance. This is before LMS and so forth, and that worked. That was the first time I saw it used inside the business.”
Then, Schmidt was asked why he co-wrote a book on AI with Henry Kissinger, who has no tech credentials. He revealed that Kissinger, having read the work of the philosopher Immanuel Kant, was worried about the impact of AI on the human mind.
The Next Wave
With Rubenstein posing the question: ‘where do investors go from here?,’ Schmidt suggested we’re still in the AI era, “at the top of the first inning” in terms of where this technology will take us.
“If you really want to make money, it’s actually easy,” he said. “Found an agentic AI company. And I don’t mean one designing agents. I mean, build an agent to do something. This is the agentic period in AI and for the next year or two, everyone’s going to build agents. The agents are all going to compete. If you build a better agent than anyone else, you can probably build one incredible company and own it yourself.”
Schmidt quantified the impact in America this way:
“AI is, at the moment, contributing more than 1% to the GDP of America, largely because of the data center buildout, and I just started a data center company, so I’ve been studying this: the demands from the hyperscalers, the big companies, Google and so forth, are immense.”
Humans And AI Together in the Real World
Throughout the conversation, there was the sense that AI is about to meet us in our world, and a curiosity about what that may look like. The panel reviewed the thoughts of Yann LeCun, former head of research at Meta, who earlier in the conference spoke at length about the value of helping AI to understand the physical environment that we live in.
Rubenstein asked Ucuzoglu about job displacement, acknowledging that the workforce at Deloitte is about half a million people.
“Will there be some displacement and shifting in certain functions that one did manually?” Ucuzoglu responded. “Of course, as with every wave of technology adoption. But we’re still a big believer that great people, great professionals with domain expertise, are actually the key to unlocking the technology, and that as with every prior wave of technology change, on a net basis, you actually create more jobs than you disrupt.”
All About People
Going back again, to the meatspace, the real world, where physics is king, and humans have the intuitive edge, the panel thought about LeCun’s propositions.
“The real world is far more complicated than text,” Ucuzoglu said. “And so those who have an appreciation for the context and who can work with the technologists to bring it to life, that’s where the real value is being created.”
Then Rubenstein did something really interesting. He went further, describing the actual person who might be struggling with this issue. I found this to be tremendously useful, because you can talk about job displacement all you want, but actually sketching out the issue gives it dimension, and that’s what we need, in my opinion. Now, he was also asking a question, answered by Schmidt, so here’s how that went.
“Let’s suppose somebody in the audience here is 40 years old,” Rubenstein began. “They majored in humanities in college. They have a job that’s a non-tech job, but they really want to learn about AI so they can talk about it intelligently with their children, if not somebody else. What’s the best way for a middle-aged, non-technology person to actually learn something about AI to sound reasonably intelligent on it?”
“So, let me turn the question around,” Schmidt said. “We have MIT and Stanford here. The most important new course … is the freshman class on prompt engineering. Because if you think about it, the student that is entering MIT or Stanford, their entire life is going to be prompt engineering as it evolves, because everything they do will be with a computer assisting them. So the same applies to the 40-year-old, right? So the 40-year-old needs to get good, too.”
The Rest of the Conversation
There was more, on hiring Olympians, free food, sandbagging (not telling the truth) and territorial office wars. You can see it all on the video. But I thought that this was one of the most revealing talks that we had at the IIA event, partly because it did have that focus on people. After all, what is the “global landscape?” You have the topography of the earth, but that’s not really central to our view of the world. We live in a human world, and AI, in the end, will have to meet us there.
