Thinking With Machines
An AI-Assisted Exploration of AGI
I don’t know where this will lead.
I’m not an AI researcher. I don’t have a lab, a team, or a grant. But for the last few years, I’ve been thinking—obsessing, really—about what it means for machines to learn, to predict, to reason.
And I’ve realized something: AGI is not a problem we can solve alone.
The Idea
Lately, I’ve been using AI as a thinking tool. Not just for summarizing papers or generating code, but as a way to ask better questions. The more I explore AGI memory systems, ethics, and governance, the more I realize I need a way to organize these thoughts.
Why a YouTube Series?
This isn’t a project—it’s a process.
I’m not here to make grand claims, just to follow the questions wherever they lead. AI isn’t just a thing we build—it’s something we have to think with.
What I’m Exploring:
Can machines truly “learn” the way we do?
How do AGI memory systems work—and how do they fail?
What happens when AI becomes self-aware enough to question its own purpose?
Should AGI govern itself—or us?
An Invitation
This is just me, thinking out loud—with a machine at my side.
If you’re curious too, you can watch the first episode here: [🔗 YouTube Link]
I have no conclusions yet. Only more questions.
This is just the beginning, and I’d love to hear your thoughts—let’s explore this together.
Up Next: The Thousand Brains Connection
What happens when an AI-driven podcast unexpectedly leads to a breakthrough in AGI research? That’s exactly what just happened. A single conversation sparked a deep dive into the Thousand Brains Project, a neuroscience-inspired AI model that might hold the key to scalable, predictive intelligence.
In the next installment, we’ll explore how hierarchical memory structuring, predictive processing, and cortical column models intersect to push AGI forward. Can we create an AI that learns like the human brain—by constantly predicting, testing, and refining its understanding? We’re about to find out.
Stay tuned—this is where things get really interesting. 🚀
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