This week we are leaning into multiple metaphors: AI as a mirror, UX design as a window or room, and life as information. Plus: read about Michael Levin's upcoming presentation at the Imagining Summit, Helen's Book of the Week, and our upcoming events.
It’s easy to fall prey to the design illusion that because LLMs look sleek, they must be well-designed. But aesthetics alone do not equal design. As Steve Jobs once said, “Design is not just what it looks and feels like. Design is how it works.”
It’s curious that these two papers, tackling such similar ideas, came out at the same time. Is this coincidence, or does it tell us something about where the study of life and intelligence is heading?
In this episode, we provide updates from our Artificiality Pro presentation, including key developments in mechanistic interpretability for understanding AI models and considerations around the costs of large language models: aka memory vs margins.
Developing expertise now requires fluency in both core disciplines and leveraging AI for insights, posing an uneasy paradox.
In this episode, we speak with cognitive neuroscientist Stephen Fleming about theories of consciousness and how they relate to artificial intelligence.
Our obsession with intelligence: AI that promotes collective intelligence, not collective stupidity.
In this episode, we dive into the exciting announcement of Google's new foundation model for AI, Gemini, exploring three key aspects of this important, new technology.
An interview with Steven Sloman, professor of cognitive, linguistic, and psychological sciences at Brown University, about LLMs and deliberative reasoning.
Before AI can reason and plan, it needs some "system 2" thinking.
New research reveals that large language models can generate superior prompts for themselves through automated techniques, reducing reliance on specialized fine-tuning.
Our obsession with the parallels between human and machine intelligence.
The Biden Administration's Executive Order has stirred up discussion about the regulatory capture in AI. For good reason.
Rather than reactively banning technology or doubling down on ineffective surveillance, we must proactively develop new pedagogical muscles for this algorithmic age—scaffolding metacognitive discernment and critical thinking while leveraging AI as a valuable asset.
The Artificiality Weekend Briefing: About AI, Not Written by AI
