Hallucinations are (almost) all you Need
Fundamental research in science is being transformed by a practice predominantly associated with the arts: namely hallucinations.
This rapid overview of key scientific AI examples (that covers a year loosely defined as starting with the release of GPT-4 on March 14th, 2023) is framed by the hypothesis that fundamental research in science is being transformed by a practice predominantly associated with the arts: namely hallucinations. Hallucinations in people are conventionally associated with mental illness, drugs, and/or genius. Hallucinations in AI (mostly in large language models) have been critiqued as net-negatives: contributing to disinformation, bias, post-truth, deep-fakes, collapse of democracy, copyright theft, etc… Yet at the same time, AI hallucinations (of proteins/crystals/algorithms/circuits etc) pruned down to the feasible, are contributing to a revolutionary acceleration of scientific discoveries in numeric-algorithmic optimizations, AI hardware accelerators, reward mechanism design, non-invasive brain sensors, drug discovery, sustainable deep-tech materials, autonomous lab robotics, neuromorphic organoid computing, and mathematical reasoning. In both art and science, hallucinations are almost enough: without the pruning down to the plausible, there is just a sprawl of potentiality.
Slides (without speaking notes)
PDF [video 0.1] (April 24, 2024, CDN Seminar on AI and Digital Media Aesthetics)
PDF (April 2, 2024, Brain & Consciousness Group (HBF), UiB)
PDF (Feb 24, 2024, ZDHK Immersive Arts)
PDF (Feb 14, 2024, UiB Centre for Digital Narrative)
Based on the enormous mountain of links collected in 2023 in the gdoc AI Spring, this is currently a 30-40 minute talk that will be released in next iteration as an essay, and eventually perhaps as a video.