Kasper Jordaens

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... 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.

model-agnostic meta-learning, or MAML, it trains a model using two machine-learning processes, one nested inside the other.[...] setting his AI the challenge of learning more than one task led it to come up with its own version of a sparse model that outperformed human-designed ones.

His point is that if intelligence as we know it resulted from the mindless mutation of genes over countless generations, why not seek to replicate the intelligence-producing process—which is arguably simpler—rather than intelligence itself?

Understanding is beyond GPT-3’s reach because understanding cannot occur in an isolated behavior, no matter how clever. Understanding is not an act but a labor. Labor is entirely irrelevant to a computational model that has no history or trajectory; a tool that endlessly simulates meaning anew from a pool of data untethered to its previous efforts.... See more

“…Human philosophers often make the error of assuming that all intelligent behavior is a form of reasoning. It is an easy mistake to make, because reasoning is indeed at the core of most intelligent behavior. However, intelligent behavior can arise through other mechanisms as well…”

I may be an avid consumer of ac-tion movies and yet consider arthouse films aesthetically superior, eventhough I watch them more rarely. Artificial systems that gather data abouthuman aesthetic consumption should take these issues into consideration ifwe want to avoid overly simplistic models of human aesthetic experienceand judgment

While we are highly uncertain which commercial and non-commercial use cases might get traction and be safely supportable in the longer-term, plausible use cases of powerful image generation and modification technologies like DALL·E 2 include education (e.g. illustrating and explaining concepts in pedagogical contexts), art/creativity (e.g. as a... See more