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Jibe Ho! Artificiality is changing.
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.
For most of our 10+ years in AI, we’ve faced solid headwinds. We tacked back and forth to advance our mission to help people make sense of AI, responding to small changes in technology and interest. AI was considered a relatively isolated technology so advancing the idea that everyone needed to understand AI was definitely challenging. But a year ago, everything changed.
The release of ChatGPT ignited worldwide interest in AI and what it might mean for individuals, organizations, and society. That interest changed our business as well, and we suddenly found ourselves powered by strong tailwinds. While running with the wind makes some things easier, it can also make changing directions more challenging.
Today, we’re making a change and, in a sailor's terms, yelling out: Jibe Ho! For the non-sailors, jibing is a sailing maneuver whereby a sailboat which is sailing downwind changes directions by turning its stern to the wind. Jibing can be a dangerous move as the boom sweeps across the boat and the wind catches the sail. With the kind of winds we’re running with today, that sail can whip across the boat with serious force—you’d better be sure of what you’re doing or else you could get clocked by the boom or capsize altogether.
Our jibe is to change the pace of our publishing. Since we re-launched Artificiality, we’ve followed the pace of the rest of the industry, working to put new content in front of you on a nearly daily basis. While exciting, that pace isn’t true to the direction we think is most important for Artificiality. As artificial philosophers and meta-researchers, we’re interested in a thoughtful approach to the grand change we’re all experiencing. And we think that a thoughtful approach requires us to step back and provide you with considered analysis.
Starting now, we will be releasing Artificiality on a weekly basis. Each week, we’ll publish a handful of pieces—articles, essays, podcasts, research—and we’ll share them with you in a single email. While the quantity of content we produce won’t change, we hope the change in rhythm will help put our ideas in perspective. We believe we are the start of a new multi-decade cycle in our relationship with machines. Daily coverage simply creates noise. And our mission is to help you see the signal in the noise.
Artificiality Pro will remain on a monthly cycle, centered on one of our research obsessions. For instance, February’s Pro release was centered on World of Workflows while March will center on Trust. In addition to our monthly research releases, we are also rolling out new courses for our Pro members on adopting generative AI, making decisions with AI, and complexity science. And we are also responding to our current members interests, working on industry-related research and data products. Join Artificiality Pro to help craft its future.
We are thrilled that you are with us on this journey and would love to hear from you. We hope to make the most of these powerful tailwinds by choosing the course that works best for you. What are you most excited about with AI? What are you most fearful of? What of our content do you find most helpful, most interesting—and what do you find least of each?
We consider feedback a gift and would love to hear any of yours. If you’re willing to share, please use this link to schedule a Zoom chat.
Thanks again for joining us. Catch you each Friday!
This Week from Artificiality
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.