Artificial Intelligence Wave: For an extreme person, things couldn’t be better

But the really amazing thing is that we’re building this to turn so much of our world upside down. That’s why I think this is great.

I’m a big proponent of what’s called “maximum thinking”: finding a way to change, and taking the new idea to its greatest useful expression. This has long been a wellspring of great innovation, which is why much of the so-called “disruptive innovation” we have seen in many industries comes from outsiders. The infrastructure we are building today will spark an extreme boom.

I’m not sure anything like that has ever happened before. Major infrastructure projects of the past century have included airports, transnational highways, and deep-water ports that accommodate cargo containers. This has accelerated international trade and enabled things like outsourcing and same-day delivery, with amazing results in countries as diverse (at first) as the US and China. In the nineteenth century, investments in railway infrastructure increased immigration to a mass level, transformed the American Midwest into an agricultural powerhouse, and allowed imperial powers to grow across Africa and the Indian subcontinent.

In all these cases, investments paid off primarily through expanding existing mandates and processes. There were intermittent shocks, of course, as when armies faced industrial violence at the start of World War I, or how government-sponsored computer networks gave way to the Internet. Intentions in previous investments were initially linear, based on what was already there.

Compare that to today, when AI is being scaled specifically to disrupt and change things. Building our global AI will likely launch new industries in robotics, bioengineering, and computing. Today’s self-driving taxis, rapid vaccine manufacturing, and telepresence economies are just the first signs of this discontinuous change. For the first time in history, we are creating major infrastructure to not only expand what we know, but to stimulate non-linear creativity at scale.

Knowledge as a commodity

This investment in infrastructure is already leading to an exciting result: generative AI is rapidly turning knowledge itself into a commodity. Competencies that took years and decades to develop can now be replicated in moments by AI. This challenges traditional paths of experience. We only have to look at the crises witnessed by universities this year and the slowdown in hiring junior graduates to understand this matter.

People will adapt, but with some difficulty. Machines are already doing more things, in ways we couldn’t even imagine at the beginning of this decade. And while you can point to AI-based hallucinations that seem to mock this, it’s good to be reminded that a lot of very smart people are devoting $7 trillion to making new systems bigger, stronger, and more precise. Gen AI is today’s cutting-edge technology, but part of today’s investment is in developing more powerful forms of AI.

Some people despair that humans will make themselves largely insignificant thanks to big machines, and most will have no way to seek their own meaning and fulfillment through work. For them, the networked sky is falling, and not just from satellites connected to data centers.

I think the opposite: if knowledge is turned into a commodity, it does not mean that it has no value. Other commodities, such as oil and agricultural products, fell in price, found new and large markets, and became more valuable. Turning knowledge into a commodity means that people will interact with it in new ways, connecting things that were previously unrelated to create new insights and outcomes that generate value.

As knowledge becomes a commodity, more people will have access to it. This will free us to apply our experience, intuition, and imagination, which are valuable and unique human qualities that artificial intelligence cannot imitate.

A new paradigm is emerging

For an extreme person, things couldn’t be better. Industry insiders, bound by existing rules, often struggle to adapt during major shifts. It usually takes outsiders, sensing new possibilities, to make progress happen. Now, with the release of the latest AI knowledge, we have many more of these productive outsiders ready to move industries forward.

This does not mean that the old model is broken, but that it is no longer suitable for this new world. A new paradigm is emerging. The new infrastructure will enable more thinkers to realize new possibilities and build new systems. Often times, they will do this by identifying new data and facts about the world that do not exist within AI, and this will also give them an advantage.

For corporate leaders in the reshaped knowledge era, where originality and intuition are the ultimate advantage, there will be great management challenges. The questions are no longer just about efficiency, but about strategy: How can I develop more creative thinkers? How can my team connect the dots in new ways? How can we stick to our core value proposition while also expanding it into new areas, and face a changing future with optimism?

For the max, it’s going to be a great time.

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