It is hard to put Peter Diamandis’ Moonshots LIVE into “a box” and just label it as one thing. Imagine one part Star Trek convention, one part XPRIZE competition and one part live taping of the Moonshots podcast, then put 1,500 entrepreneurs, scientists, investors, technologists and creators inside a historic Los Angeles theater to consider what humanity could accomplish as artificial intelligence and other technologies advance exponentially.

Diamandis called it the “Oscars for Optimists.” But after two days of recurring Star Trek references, XPRIZE contestants, along with mind-expanding conversations about all the good things we can do with AI (along with some “moonshot thinking”), I came away believing something more consequential was happening. Moonshots LIVE was making the case for optimism at precisely the moment when optimism can seem in short supply.

To be clear, i’m not encouraging we have blind optimism. I’ve worked in tech long enough to know there are always risks, issues and displacements. And no, I don’t believe that AI will magically solve every problem. AI presents real challenges involving employment, cybersecurity, misinformation, inequality, concentration of power and human agency. The more useful definition of optimism is the one embedded in the Moonshots philosophy: problems are solvable, and we have an obligation to try to solve them.

That distinction matters because we are entering what I think of as the exponential intelligence curve .

For most of human history, intelligence has been scarce. It resided almost entirely in human beings. We educated people, organized them into institutions and built software to make their work more productive. AI changes that equation because we are beginning to manufacture intelligence at enormous scale.

The evidence is increasingly visible. The Stanford Institute for Human-Centered AI’s 2026 AI Index reports that 88% of organizations used AI in at least one business function in 2025, while generative AI reached 53% adoption in three years, faster than either the personal computer or the internet. The economics have become equally consequential. Stanford found that the cost of a model performing at roughly GPT-3.5 level fell from $20 per million tokens in late 2022 to $0.07 by late 2024. That historical comparison does not mean every frontier model is now cheaper than $0.07 per million tokens. Rather, it reveals a new market structure: organizations can reserve premium frontier systems such as GPT-6 for complex reasoning, coding, and agentic work, while routing routine, high-volume tasks to far less expensive models. Current offerings from Chinese providers such as DeepSeek and Qwen can process input at roughly $0.10 to $0.40 per million tokens, with some cached-input rates measured in fractions of a cent; open-weight models add the option to deploy and optimize capability within an enterprise’s own infrastructure. The practical consequence is profound: AI is no longer a scarce resource to be rationed across the enterprise, but an increasingly inexpensive operating layer that can be matched to the risk, value, and complexity of each task.

When the cost of useful intelligence collapses while its capabilities improve, intelligence begins moving from scarcity toward abundance. Every scientist can potentially have AI research assistants. Every entrepreneur can access capabilities that once required an organization. Every student can have a personalized tutor. Every employee can summon specialized expertise. And enterprises may eventually operate with thousands or millions of digital agents working alongside people and other agents.

The implications are much larger than chatbots.

Peter Diamandis And The Architecture Of Optimism

To understand Moonshots LIVE, it helps to understand Diamandis. He is the founder and executive chairman of XPRIZE, executive founder of Singularity University , a physician and aerospace engineer, entrepreneur, investor and co-author of books including Abundance , BOLD and The Future Is Faster Than You Think . He has founded or co-founded more than 25 companies spanning space, health, education, AI and venture capital.

The idea connecting those efforts is straightforward: instead of assuming today’s constraints are permanent, ask what happens when an exponential technology changes the constraint itself.

XPRIZE turns that philosophy into an incentive system. Rather than funding promises, it creates large competitions around measurable outcomes. Over three decades, XPRIZE says it has launched 30 competitions, engaged more than 35,000 innovators across 173 countries and converted $519 million in prize capital into $31 billion in measurable economic and social value.

Moonshots LIVE took that philosophy and turned it into a community.

Diamandis was joined by his Moonshots Mates: Alex Wissner-Gross, Salim Ismail, Dave Blundin and Emad Mostaque . Each approaches exponential change differently. Wissner-Gross brings the perspective of a physicist and computer scientist asking what AI makes scientifically possible. Ismail, author of Exponential Organizations , focuses on the widening gap between exponentially improving technology and organizations that still change incrementally. Blundin brings the entrepreneur and investor’s perspective on where exponential technologies create new markets. Mostaque, founder and former CEO of Stability AI, brings experience from the movement toward open generative AI.

Together, their discussions kept returning to a deceptively simple question: What becomes possible when intelligence itself becomes exponential?

The broader speaker lineup made the question tangible. Palmer Luckey of Anduril, Ben Lamm of Colossal and Astro Teller of X explored what it takes to build ambitious companies. Cathie Wood examined the investment consequences of converging technologies. Circle’s Nikhil Chandhok discussed programmable money and the agentic economy. Anousheh Ansari brought the XPRIZE model back to solving grand challenges. And Neil deGrasse Tyson, Neal Stephenson, Mira Lane and Rod Roddenberry represented something equally important: our capacity to imagine the future before we build it.

What If The Future Goes Right?

That connection became clearer the night before Moonshots LIVE, at the world premiere of The Sixty-Year Mission: How Star Trek Changed Television and the World , marking the 60th anniversary of Star Trek .

Star Trek was never really about spaceships. Its most important technology was its vision of the future.

Gene Roddenberry imagined a civilization in which science and technology had helped humanity overcome many of the material constraints and social divisions of the present. Long before technologies exist, they often appear in stories. Science fiction can become a kind of prototype for civilization.

That made the Future Vision XPRIZE particularly powerful. We have become exceptionally good at imagining how technology might destroy us. From The Terminator to Black Mirror , our cultural imagination is filled with dystopian AI and malevolent machines. Those warnings matter, but there is a cost if dystopia becomes the only future we know how to imagine.

Future Vision reversed the question: What does a future worth building actually look like?

More than 2,500 film trailers and treatments depicting hopeful, technology-enabled futures were submitted. Five finalists screened at Moonshots LIVE before judges including Neil deGrasse Tyson, Neal Stephenson, Mira Lane, John Zissimos and Rod Roddenberry.

The winner was The Gifted , by Jeff “Synthesized” Thomas, which received a $2.5 million equity investment toward production of a feature film and another $100,000 for screenplay development.

The prize money matters, but the mechanism matters more. Imagination creates possibility. Possibility creates ambition. Ambition attracts talent and capital. Talent and capital build things.

That progression connected the seemingly disparate pieces of Moonshots LIVE. Star Trek imagined a future. The Gifted imagined one for the AI era. XPRIZE created incentives to pursue seemingly impossible goals. The Moonshots Mates explored the technologies changing what is possible. Entrepreneurs onstage were actually trying to build at the frontier.

Optimism had been transformed from a sentiment into a system.

Why Optimism Is A Leadership Capability

This is where the experience became particularly relevant for CEOs and boards.

Corporate leaders are being inundated with reasons to worry about AI, many of them legitimate. But risk management cannot become our only framework for thinking about the future. Boards must ask what could go wrong with artificial intelligence. They must also ask: What could go extraordinarily right?

What happens when every employee has access to extraordinary intelligence? What customer experiences become possible when expertise can be delivered instantly at dramatically lower cost? What scientific problems become solvable? How does the structure of a company change when increasingly capable AI agents can perform work that previously required teams of people?

These are governance questions too.

As AI moves from generating information to taking action, the questions become even more consequential. What is an agent authorized to do? Who granted that authority? Which decisions must remain human? Who is accountable for an agent’s actions? How do boards oversee enterprises in which consequential work is increasingly performed by non-human actors?

Stanford’s data captures the transition. While 88% of surveyed organizations now use AI somewhere in their businesses, AI-agent deployment remained in the single digits across nearly all business functions in 2025. We have widespread experimentation with AI, but the truly agentic enterprise is still emerging.

The technology may move exponentially while our institutions move incrementally. We are beginning to insert 21st-century intelligence into organizational structures and governance systems designed for a world in which humans performed the work and software remained a tool.

The bottleneck may eventually be less about what AI can do than whether our organizations can adapt quickly enough to use it responsibly.

That is why optimism matters.

Pessimism sees a problem and explains why it cannot be solved. Naïveté sees technology and assumes the problem will solve itself. Optimism sees the problem clearly and decides it is still worth solving.

Leadership during periods of incremental change is largely an exercise in optimization. Leadership during periods of exponential change requires imagination.

Boards need to manage risk, but they also need to imagine possibility. CEOs need to protect existing businesses while asking what those businesses become when intelligence is abundant. Governments need to protect society from technological harms while preserving the conditions that enable breakthroughs. And those of us working on governance need to ensure that the institutions surrounding increasingly powerful technologies evolve alongside them.

Optimism without accountability becomes hype. Governance without optimism becomes bureaucracy. We need both.

That may be the real lesson of Diamandis’ “Oscars for Optimists.” Civilization advances when people look at constraints everyone else considers permanent and ask whether they still have to exist. Someone imagined reusable rockets. Someone imagined computers that fit in our pockets. Someone imagined machines that could understand language. Someone imagined Star Trek . Then somebody tried to build it.

We are entering an era in which intelligence itself is becoming more capable, accessible and dramatically less expensive. That does not guarantee abundance. It gives us an extraordinary new set of tools with which to pursue it.

The future is not something that simply happens to us. We imagine it, invest in it, invent it, govern it and build it. Optimism is not a prediction that everything will turn out well. It is a decision that the future is still worth working for.