Kasper Jordaens

So: GPT-3 is incredibly powerful, but it’s only as good as its training data. And GPT-3 achieves its power through the vastness of its training data-set. Such data-sets are cannot be hand-picked for some sensitive, subtle value. They are most likely to be built around simple, easy-to-capture targets. And such targets are likely to drive us towards ... See more

It is not hard to imagine that “artificial judgment” systems might be increas-ingly used in the future. These systems would autonomously evaluate cul-tural objects, scoring a design artifact, fashion item, or image with a higheror lower aesthetic value.

The model can generate known entities including trademarked logos and copyrighted characters. OpenAI will evaluate different approaches to handle potential copyright and trademark issues, which may include allowing such generations as part of "fair use" or similar concepts, filtering specific types of content, and working directly with copyright/tr... See more

As for consciousness, I am open to the idea that a worm with 302 neurons is conscious, so I am open to the idea that GPT-3 with 175 billion parameters is conscious too. I would expect any consciousness to be far simpler than ours, but much depends on just what sort of processing is going on among those 175 billion parameters.

Machines learn to recognize increasingly com-plex patterns in data that humans are not able to detect. All this raises thefollowing question: to what extent are machine perception and patternrecognition mechanisms relevant for “aesthetic perception,” and what are thetypically human aspects of aesthetic sensibility that still need to be tackledby ar... See more

GPT-3 has been trained on us—on a lot of things that we have said and written—and ends up reproducing just that, racial and gender bias included.

When you send query text to GPT-3, you aren’t communing with a unique digital soul. But you are coming as close as anyone ever has to literally speaking to the zeitgeist.

quote by GPT3 itself:

The new system, called AutoML Zero, tries to build an AI from the ground up using nothing but the most basic mathematical concepts that govern machine learning.Amazingly, not only did AutoML Zero spontaneously build a neural network, but it came up with gradient descent, the most common mathematical technique that human designers use to train a net... See more