.SUSS

Historically, the two were separate endeavors. AI represented, for example, search-and-calculate algorithms like chess programs that could beat humans, while ML represented statistical techniques to predict responses to new inputs from a training dataset.

The confusion between AI and ML came about because of deep learning, an extension of neural networks to allow for hierarchical connections between layers of neurons, and trained on exponentially more data than before.

Deep learning (DL) was a major innovation and many began to elevate DL out of ML and equate it with AI.

The real interesting G is in artificial general intelligence (AGI). An AGI is more than a generative tool.

It is a person. You might think of it as a digital person or a silicon-based person rather than our more familiar carbon-based people, but it’s literally a person. It has sentience and consciousness. It can generate new knowledge. It can think and feel and joke and love. It has rights. It’s alive.

This is exactly what people used to mean by “AI” until AI beat humans at chess and Go and art and poetry and we kept moving the goalpost. This aspirational “true” AI is now called AGI.

This is what is meant by “the alignment problem.” Unaligned AGI’s may enslave us or kill us, perhaps even thinking it is for our own good. Hinton raises another possibility: they will be so good at persuasion, they’ll be able to convince us to do anything.

We have always been “just one program” away from AGI. But now we know that we are “just one prompt” away.

“The orator persuades by moral character when his speech is delivered in such a manner as to render him worthy of confidence; for we feel confidence in a greater degree and more readily in persons of worth in regard to everything in general…” - Aristotle, Rhetoric

Lisa Lambert

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