Unknowing and Unknowable | Last Chance for Super Early Summit Tickets
LAST CHANCE FOR SUPER EARLY PRICING FOR THE ARTIFICIALITY SUMMIT 2026!
This week: New research and product previews from Apple, Google, and OpenAI; an interview with Richard Kerris of NVIDIA, crafting better promtps, an interview with Tyler Marghetis, and an exploration of generative AI and flow.
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.
By understanding the principles behind the evolving field of prompt engineering, we can craft better queries and engage more effectively with AI. They're insights we can all use to sharpen our own interactions with AI, even if we're not writing the code ourselves.
An interview with Richard Kerris, Vice President of Developer Relations and GM of Media & Entertainment at NVIDIA, about AI, creators, and developers.
Today, we’re making a change and, in a sailor's terms, yelling out: Jibe Ho! Our jibe is to change the pace of our publishing. Starting now, we will be releasing Artificiality on a weekly basis.
It appears that there is one effect many researchers are finding across multiple fields: generative AI has a significant impact on lower skilled and less experienced people. However, if we automate difficult tasks we cut ourselves off from the essential components for achieving mastery like flow.
An interview with about the lulls and leaps of human imagination with Tyler Marghetis, Assistant Professor of Cognitive & Information Sciences at the University of California, Merced.
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.
Considering Big Tech's longer-term potential, peril, and possibility with AI.
Working with AI requires seeing beyond automation to amplification. If society chooses to complement strengths between humans and machines, more dynamic partnerships become possible.
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.