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The leap from today\\u2019s narrow AI to a more general kind of intelligence seems likely to happen at some point in the next century. But no one knows exactly how: at the moment, AGI remains a significant technical and theoretical challenge, and expert opinion about what it will take to achieve it varies widely. Some think that scaling up existing paradigms \\u2014 like deep learning and reinforcement learning \\u2014 will be enough, but others think these approaches are going to fall short.

Geordie Rose is one of them, and his voice is one that\\u2019s worth listening to: he has deep experience with hard tech, from founding D-Wave (the world\\u2019s first quantum computing company), to building Kindred Systems, a company pioneering applications of reinforcement learning in industry that was recently acquired for $350 million dollars.

Geordie is now focused entirely on AGI. Through his current company, Sanctuary AI, he\\u2019s working on an exciting and unusual thesis. At the core of this thesis is the idea is that one of the easiest paths to AGI will be to build embodied systems: AIs with physical structures that can move around in the real world and interact directly with objects. Geordie joined me for this episode of the podcast to discuss his AGI thesis, as well as broader questions about AI safety and AI alignment.