Human cognition is a full-body experience, not just a brain function. Current AIs are 'disembodied brains,' fundamentally limited by their lack of physical interaction with the world. Integrating AI into robotics is the necessary next step toward more holistic intelligence.

Dan Siroker outlines a three-part roadmap for achieving mind emulation: 1) a complete brain map (connectome), now feasible by 2040; 2) sufficient, cheap compute power, estimated to be ready by 2047; and 3) rich behavioral data, which the Limitless pendant is designed to capture.

In a step toward emulating minds, Eon Systems connected the scanned connectome of an actual fruit fly to a physics-simulated body. Dr. Alex Wissner-Gross says the goal is a future where both artificial and emulated biological minds can operate on cloud infrastructure.

A key advantage humans will retain over AI is the ability to translate rich, multi-sensory physical experiences—like touch, smell, and memory—into abstract thought and creative insight. This 'last mile of human experience' is not yet transferable to technology.

Challenging Neuralink's implant-based BCI, Merge Labs is creating a new paradigm using molecules, proteins, and ultrasound. This less invasive approach aims for higher bandwidth by interfacing with millions of neurons, fundamentally rethinking how to connect brains to machines.

The debate over AI consciousness isn't just because models mimic human conversation. Researchers are uncertain because the way LLMs process information is structurally similar enough to the human brain that it raises plausible scientific questions about shared properties like subjective experience.

Consciousness isn't an emergent property of computation. Instead, physical systems like brains—or potentially AI—act as interfaces. Creating a conscious AI isn't about birthing a new awareness from silicon, but about engineering a system that opens a new "portal" into the fundamental network of conscious agents that already exists outside spacetime.

Companies like Cortical Labs are growing human brain cells on chips to create energy-efficient biological computers. This radical approach could power future server farms and make personal 'digital twins' feasible by overcoming the massive energy demands of current supercomputers.

While today's computers cannot achieve AGI, it is not theoretically impossible. Creating a generally intelligent system will require a new physical substrate—likely biological or chemical—that can replicate the brain's enormous, dynamic configurational space, which silicon architecture cannot.