Isabelle Levent
@isabellelevent
Isabelle Levent
What do you do when you know that the environment is going to change but you want to have other members of your species that are reasonably well aligned? Caregiving is one of the things that we do to make that happen. Every time we raise a new generation of children, we’re faced with this difficulty of
here are these intelligences, they’re new,... See more
here are these intelligences, they’re new,... See more
Julien Crockett • How to Raise Your Artificial Intelligence: A Conversation With Alison Gopnik and Melanie Mitchell
This builds on a growing body of work that our ‘‘mind perception’’ (which manifests as inferences of intentions, beliefs, and values) meaningfully varies across individuals and shapes our moral judgments
Sydney Levine • Who gets credit for AI-generated art? – MIT Media Lab
“An engine for the imagination”: an interview with David Holz, CEO of AI image generator Midjourney
James Vincenttheverge.com
Creativity and
I am utterly disgusted. If you really want to make creepy stuff, you can go ahead and do it. I would never wish to incorporate this technology into my work at all. I strongly feel that this is an insult to life itself
Vikram Murthi • Hayao Miyazaki Calls Artificial Intelligence Animation ‘An Insult To Life Itself’
A much better way of thinking about them is as a technology that allows humans to access information from many other humans and use that information to make decisions.
Julien Crockett • How to Raise Your Artificial Intelligence: A Conversation With Alison Gopnik and Melanie Mitchell
on metaphors for LLMs
Copyright and
The Lab’s primary focus is on the ways in which artists and designers are adopting, adapting and remaking AI processes, building their own datasets and reaching into the ‘grey box’ of AI technologies.
Creative AI Lab • Creative—Critical—Constructive —Collaborative—Computational: Towards a C5 model in Creative AI
We find that models learn just as fast with many prompts that are intentionally irrelevant or even pathologically misleading as they do with instructively “good” prompts. Further, such patterns hold even for models as large as 175 billion parameters (Brown et al., 2020) as well as the recently proposed instruction-tuned models which are trained on
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