This is a YouTube video titled "How Liquid AI Became a $2B Startup" containing a discussion between two speakers about foundational thinking in AI design, focusing on reasoning from first principles and biological inspirations such as worms and electrophysiology. The content explores scalable models of intelligence based on evolutionary biology. The speakers are not identified as George Bandarian.
For me, thinking from first principles was the most important thing. It's also important to reason from first principles rather than by analogy.
Real lateral thinking that requires wandering, and you have to give yourself permission to wander.
So when you think about how to design AI systems, like I was thinking about, like nature as one of the first places to look at. And then I wanted to see what's the smallest unit that I can find that is scalable. And then the worm itself, a very popular worm. It is one of those worms that won four Nobel Prizes for us so far. And the reason for that is, like, because it shares, I think, 78% genome similarity to humans. So that would allow you to, whatever you discover about the brain of the worm or the cells of the worm, behavior of the worm is scalable to other animals after that, in the tree of evolution, if you actually start modeling intelligence from that level, you can evolve that model of intelligence to larger animals later. Electrophysiology started by frog leg experience, where the scientist, he was hitting the leg of a frog and the leg of the frog was actually like moving. So that was electrophysiology. That was the first discovery of this math that describes liquid AI.
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