Facts & Figures about AI and Complex Change
A running catalog of the facts & figures we publish every week in our newsletter.
Our meta-research across disciplines: behavioral economics, cognitive science, complexity science, computer science, decision science, design, neuroscience, philosophy, and psychology. Science is changing because boundaries between disciplines are dissolving. Our research dissects the latest books and papers. Highly curated, an antidote to information overload.
This research shows how flexible these models are: meta-prompting aids in decomposing complex tasks, engages distinct expertise, adopting a computational bias when using code in real-time which further enhances performance, then seamlessly integrates the varied outputs.
The introduction of Gemini 1.5 Pro's ability to handle unprecedented context lengths, its superior performance compared to its predecessors, and the sustained relevance of power laws in its design underscore the breadth and depth of Google's long term capabilities.
Apple researchers recently published a paper describing a new architecture for vision models. The paper's unique approach to vision modeling hints at Apple's likely strategic imperative towards heavily integrating vision models in spatial computing environments.
Our World of Workflows research discovers that the benefits of AI support are not evenly distributed but rather significantly skewed toward businesses and entrepreneurs that are already succeeding.
Seven books to read to understand theories of consciousness and its implication for how it might be built in AI.
A recent study from MIT has been grabbing attention with its unconventional take: don't worry about AI snatching your job, it's not cost-effective.
Chain of thought, tree of thoughts, and now graph of thoughts—a progression that may lead to agentic AI.
Does consciousness attribution hold the key to funding AI futures? The shift towards AI intimacy might reclaim our attention but at the potential cost of human-to-human connections.
Evolution, AI, and the Five Breakthroughs That Made Our Brains by Max Bennett.
The emergence of complexity from simple algorithms is a phenomenon we see in both natural and artificial systems. It's a classic example of complexity: even straightforward algorithms can lead to immense complexity over time.
The Artificiality Weekend Briefing: About AI, Not Written by AI