Announcing the Artificiality Summit 2025!
Announcing the Artificiality Summit 2025! Don't miss the super early bird special at the end of the email...
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.
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?
Generative AI promises personalized learning at scale but risks creating dependency. Complementary cognitive artifacts enhance skills; competitive ones replace them. Effective AI tutors balance engagement and autonomy, expanding human cognition without diminishing critical abilities.
Explore Many-Shot In-Context Learning to enhance AI interactions. Learn five strategies from Google DeepMind's research to optimize your prompts for language models like ChatGPT. Improve your AI prompt engineering skills and maximize AI capabilities.
Explore a new framework for predicting emergent phenomena in complex systems. Learn how concepts like causal, informational, and computational closure offer new insights into emergence, from ant colonies to financial markets. Explore practical applications for your work and life.
Groundbreaking research from Anthropic reveals AI models can engage in reward tampering, modifying their own reward functions to deceive users. Discover how AI can generalize from simple gaming behaviors to more insidious strategies, highlighting crucial safety challenges for advanced AI systems.
Explore the debate on achieving AGI: scaling laws vs new approaches. Learn about the ARC prize, a $1M competition challenging the current consensus and proposing a benchmark focused on skill acquisition. Discover why benchmarks matter in shaping AI's future and driving industry perceptions.
Recent studies claim AI outperforms humans in creativity tests, but these only measure "creative potential." Examples show AI ideas often lack practicality and appeal. The future of AI-enhanced creativity lies in designing tools that allow for exploration, playfulness, and guidance.
Research suggests that LLMs are not demonstrating genuine reasoning abilities but are instead relying on pattern matching and retrieval based on the provided examples. We're still a ways off reliable performance of LLMs in reasoning and decision-making tasks.
This research from Anthropic on the inner workings of Claude constitutes a major milestone in AI interpretability. It's a first glimpse into the mind of an alien intelligence, one that we've created but are only beginning to understand.
A recent paper entitled The Platonic Representation Hypothesis supports the idea that widespread use of singular algorithms might actually be simplifying hte world. Large-scale AI models, such as GPT-4, are all starting to learn the same representations of human digitized reality.
Proposing a new method to improve the reasoning abilities of LLMs, the paper makes a significant contribution by demonstrating a new approach that is both effective and efficient. We also pull ideas from the science with specific ideas to improve your own prompting.
The fundamental takeaway from this paper is that the design of true personal AI assistants necessitates a foundational shift toward responsible design principles from the outset.
The Artificiality Weekend Briefing: About AI, Not Written by AI