Plato’s Theory of Forms addresses the question of how we know that an object, such as a table, is what it is, even though we may never have seen it before and even though it might look entirely different to any table we have ever seen.
Plato’s answer is that a table gets its “tableness” because it partakes of the perfect Form of a table. This Form is an ideal, absolute, timeless entity that is the essence of tableness but that we cannot experience directly.
In his Allegory of the Cave, Plato famously explained that the world of Forms is not accessible to human senses and that all we experience are the imperfect shadows of Forms, as if they were cast by firelight onto the walls of a cave.
Plato’s Theory of Forms does not figure in the modern view of the universe, which we experience directly and indirectly, and come to understand through the iterative process of science. In this way, humans tend to agree on what makes up the universe and how it behaves.
But artificially intelligent systems, like large language models and machine vision systems, learn about the world in a different way. Everything they know comes from curated sets of words, images and other forms of data.
And that raises the question of whether these systems end up having a similar “view” of the world. And whether these views are converging as AI systems become more capable.
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