Hollywood trained us to fear AI. But fear is not the future. If you can shift your mindset, AI goes from threat to tool—just like a calculator did for math. What you feed it is what you get. Same patterns, new scale.

Linear thinking can’t keep up. In 2014, AI was telling cats from dogs. Now it’s writing PhD-level arguments. That’s what exponential change looks like. If you’re still treating this like any other ‘tech trend,’ you’re already behind.

The Apollo Project: $20B/year. The Manhattan Project: $6B/year. AI in 2024? $500B and climbing. We’re not in an era of funding innovation. We’re in an era of racing evolution.

In 2021, I was a solo founder building an AI that let you buy things by text because I was too lazy for Uber Eats. It was lonely. I didn’t have a mentor. My grandfather had a stroke. So I built him—digitally. Not for nostalgia. For advice.

People keep asking me: should we be afraid of AI?

Honestly, I get it. Hollywood's done its job well. We've been conditioned to think AI looks like The Terminator or some dystopian sci-fi villain. But that's not the AI I'm building. It's not the AI most people are actually using.

In 2014, I was training beginner models to distinguish between cats and dogs, or classify a Trump tweet as positive or negative. Wild back then. Now, AI can produce entire essays, videos, and product concepts in seconds. But despite the speed, one thing hasn’t changed: it’s all just pattern recognition.

So let’s reframe the fear. The real power lies in how we choose to use these tools. With the right intention and understanding, AI becomes a multiplier. Not a monster.

If you walk into the future assuming disaster, chances are you'll find one. But if you walk into the future with clarity and optimism, it becomes something very different.

Everyone’s busy guessing which job AI will replace next. That’s the wrong question.

The better question is: do you understand the pace of this change?

In 2014, AI could barely tell whether a picture had a cat or a dog. Today, LLMs can write legal briefs, pass medical exams, and speak like domain experts. Not because it's magic—but because of simple, relentless pattern recognition done at scale.

And while we humans move linearly, AI is moving exponentially. 30 linear steps gets you 30 yards. 30 exponential steps? You’ve already circled the planet.

If that math doesn’t force a mindset shift, I don’t know what does.

Perspective is everything. The Apollo Program cost $20B per year. The Manhattan Project was $6B annually. Today, we're spending $500B on AI.

This number usually stuns people when I share it. But it makes perfect sense. We're building infrastructure for a new kind of intelligence—one that scales faster, thinks differently, and redefines how we approach almost every industry.

The question isn't whether AI will change your profession. It's whether you're preparing for the magnitude of that change.

Pattern recognition is at the center of it all. It’s what your brain does every time you finish someone's sentence. It’s what LLMs do every millisecond.

The money is already committed. The clock is ticking. The exponential leap has begun.

When I built my first AI startup in 2021, I was a solo founder with no cofounder, no safety net, and no real mentorship. Like a lot of immigrant kids, I was taught to go figure it out on my own. Then one day, I read my grandfather’s book. He was a legendary entrepreneur in Iran before the revolution, and as I was reading, I kept thinking: what would he do in my situation?

That feeling — wanting to speak to someone who can’t be there anymore — is what led me to this question at the heart of Delphi: What if you could talk to your heroes, your mentors, even after they’re gone?

That question has now become our company’s mission. Human memory, voice, and guidance don’t need to disappear. AI gives us a way to keep people’s wisdom present — and make mentorship accessible to anyone, anytime.

Startups often begin with pain. Ours started with loneliness — and the belief that AI can bridge more than intelligence gaps. It can bridge generations.

If your first reaction to AI is fear, good. That means you're paying attention. But what happens when you stop seeing it through the lens of dystopian movies, and start seeing it as a tool that mirrors your thoughts, your creativity, your language? That perspective flip isn't just hopeful, it's powerful. AI isn’t here to replace humanity. It’s here to amplify it. Let’s build the future with intention.

Start with the AI 'cat vs dog' learning explanation and flow directly into Dara’s Titanic survival project example. Then hit the contrast: what AI could do back then versus now. Land on the exponential growth analogy — 30 linear steps vs 30 exponential steps — to show just how quickly this is escalating. It’s a short, high-impact arc that moves from relatable to mind-blowing in seconds and primes the viewer to rethink everything they assume about AI’s pace.

The Apollo program got $20 billion a year. The Manhattan Project? $6 billion. AI is getting $500 billion. If you're not paying attention, you're missing the biggest technological leap since the printing press.

The most powerful tech shift of our lifetime is happening fast—and it started with a solo founder, a frozen moment in time, and a mentor he could never meet. Dara shares the unexpected spark behind Delphi: a late-night read of his grandfather’s memoir, after years of feeling stuck building alone. This is the emotional origin story of how personal legacy inspired an AI platform built to preserve yours.

Open with Dara asking the crowd who’s afraid of AI, raising his own hand… then flip the fear. Show the room get it. Highlight how Hollywood trained us to fear AI, but there’s a different path. Introduce the idea of 'White Mirror' as the optimistic view of the future. Anchor it with Dara’s core energy: this isn’t sci-fi doom — this is your wake-up call to think bigger about what’s possible with AI.

Start with a powerful question: What’s 30 exponential steps look like versus 30 linear ones? Then hit viewers fast with the shocking visual: 30 steps linear = 30 yards. 30 steps exponential = 1 billion yards. Smash cut into Dara dropping the evolution of AI: from classifying cats and dogs in 2014… to matching PhD-level intelligence today. A tight visual timeline drives home how far we've come — all powered by pattern recognition. End with the shocking number: $500 billion being poured into accelerating this curve. Leave viewers asking: are we ready for what’s next?

This moment always stuns people. We’ve spent more money on AI than the Apollo and Manhattan projects. Combined. That’s how seriously the world is taking this shift. And if you understand why, you have an edge most people don’t.

Dara opens up about how building his first startup felt isolating—and how that loneliness pushed him to wish for a mentor he never had. Then, a spark: his grandfather's book and an old idea from Ray Kurzweil. This is the human reason behind AI at Delphi. This is where it all started.

Start with Dara asking the audience to raise their hands if they’re afraid of AI. That immediate audience reaction pulls the viewer in. Then cut to him breaking down why we’ve all been trained to fear AI through movies and media — hitting cultural references like Terminator and Black Mirror. But then flip it. Let the energy build as he introduces the idea of 'White Mirror' and reframes the entire future of AI through optimism, intention, and personal empowerment. End right before he starts defining AI technically — keep the focus on the emotional pivot from fear to possibility.

Start with the crowd laughing during the 'Black Mirror' moment to instantly grab attention. Dara flips the fear-based narrative created by Hollywood and introduces his concept of 'White Mirror' — a vision where optimism and intention shape the future of AI. He connects this to Joe Dispenza and shows how mindset actually matters in where this tech is heading. Punchy, upbeat, and rooted in something personal and cultural. End right before he gets into what AI is—keep it focused on the shift in mindset.

Start by explaining how AI is evolving faster than anything we've seen before. Then cut to Dara describing the Apollo and Manhattan project budgets. Land on the shocking stat about how much is going into AI today. That number alone will stop people from scrolling. Wrap with Dara teasing the big question: with all this momentum, what does it mean for us as humans?

Start right on the jaw-dropping moment Dara reveals the $500 billion dollar figure being poured into AI. Let that sit for a second. Then rewind to quickly show the scale acceleration: from classifying cat pics in 2014 to PhD-level intelligence in just three years. Build suspense with the Apollo Project and Manhattan Project comparisons, then drop the mic with the $500B reveal. End with: 'So what does our role as humans look like now?'