In This Issue: * Bubbles. Are We? Aren't We? Read more below for my current take... * On Unpredictability and
We act in the parts of reality AI can’t predict because they don’t yet exist.
Three Things Thing One: Summit 2026 Tickets for the Artificiality Summit 2026 are now available! Same place (Bend, Oregon) and
An interview with Omri Allouche, the VP of Research at Gong, an AI-driven revenue intelligence platform for B2B sales teams.
Explore Apple's AI research strategy, focusing on privacy, efficiency, and seamless user experiences. Discover advancements in context understanding, model compression, multimodal interactions, and reference resolution that could revolutionize Siri and AI-driven features across Apple's ecosystem.
Why the world feels more complex—and why that feels hard. Why more problems are complex problems. Why organizations struggle with complexity.
A Skeptic's Guide to How Cognitive Biases and Reasoning Errors Fuel AI Hype, Social Learning, The Hidden Cost of ChatGPT is the Erosion of the Digital Commons, and more.
What is complexity? How do complex problems and opportunities differ from simple & complicated? Where do we find complexity?
The #UnthinkingAIEnthusiast's are on fire these days! Here we provide a skeptic's guide to help you separte the reality from the hype.
An introduction to our new video series: Exploring Complexity
On a surface level, AI might seem like the perfect solution to the challenges of social learning. But is this really true? Is it actually what we want?
A new study suggests that the rise of ChatGPT may be eroding the digital commons. If users turn more and more to ChatGPT and other AI models for answers and assistance, rather than posting their questions and solutions publicly, the digital commons that these models rely on will begin to decline.
AI & Scientific Discovery, Agentic AI, Intimacy & Transcendence, Susannah Fox, and more.
In science, traditional human search strategies are like wandering through a wilderness with limited visibility, relying on intuition and serendipity. AI, in contrast, can take in the whole landscape, quickly and effectively exploring the vast range of possible combinations.
New research on developing AI that builds robust world models shows an AI's ability to seek out surprise, motivation, and novelty, enabling it to navigate and understand the complexities of the world through self-driven exploration rather than just following predetermined reward pathways.
