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This week is New York Tech Week, and for us at Coeus Collective, it marks the most ambitious chapter in our company’s story to date. Over the next several days, we will host eight official events and welcome more than one thousand founders, investors, and ecosystem allies into New York City.

This lineup is not built on hype. It is built with intention. Events like our Brand Blueprint summit at Pace University and the Coeus Collective Pitch Showcase presented by Seedlegals with support from J.P. Morgan Innovation Economy are designed to help people build with more clarity and connect with more substance. VC and innovation icons like Norma Padrón, Ph. D. of J.P. Morgan, Kindra Tatarsky of Cerity Partners Ventures, and René Bastón of Covenant Venture Capital will be joining us. At our Aperitivo Night, Open Mic Podcast recordings, and Founder & VC Yoga session, we are aiming to create space not just for momentum, but for reflection.

With so much ahead, you might wonder why we chose to release this essay now. The answer is simple. Before we enter dozens of rooms full of new energy and ideas, we wanted to share the one conversation from this season that left us thinking differently. A conversation not just about technology, but about thought itself.

This is our reflection on the conversation we had with Geoff Ralston, the former President of Y Combinator. That title alone carries weight, but the timing makes it even more significant. Geoff succeeded Sam Altman, who left Y Combinator to go all in on OpenAI. In many ways, Geoff inherited the very institution that helped catalyze the modern AI revolution—and then watched it unfold from a uniquely front-row seat. His take on artificial general intelligence is not theoretical. It is shaped by proximity, by experience, and by an unusually clear view of where things are heading.

What started as a discussion about AGI became something more. A challenge to the way we think about our own minds. A reframing of what intelligence really is. A philosophical prompt we could not shake.

This piece is not a summary. It is a lens. We hope it helps you see the future just a little more clearly.

Let’s do it.

The Illusion of Difference

Most debates about artificial general intelligence begin with the assumption that machine intelligence is fundamentally unlike human intelligence. The prevailing argument is that large language models are not truly thinking. They are predictive engines, mimicking coherence based on training data, and dressing up their answers with fluency and surface-level structure.

Geoff Ralston is not convinced by this framing. His counterpoint is both provocative and grounded in observation. What if the difference between machine thought and human thought is smaller than we imagine?