J. Craig Wheeler: The Path to Singularity
An interview with J. Craig Wheeler, Professor of astronomy of the University of Texas at Austin about his book, The Path to Singularity.
Artificiality Co-founders, Helen and Dave Edwards, were podcast guests on the Worlds of Possibility podcast, talking about AI Change Management.
Elon Musk's lawsuit against OpenAI and Sam Altman is the one time I would like to be on jury duty.
A review of research by Phil Tetlock and other experts on crafting better prompts by investigating if human forecasting can be improved through the use of a large language model.
This research opens up vast possibilities for AI's role in solving complex problems but also underscores the importance of understanding and this emergent behavior especially as we head towards a world of multimodal models and agentic AI.
An inteview with Angel Acosta, founder of the Acosta Institute.
ChatGPT and similar tools can significantly alter workflows by changing how we match tasks with skills. Think of a two-by-two matrix: on one axis, you have the skill needed for a task; on the other, the worker's proficiency level.
This week: Generative AI's Undesirable Unpredictability, Sensemaking & AI, Meta-Prompting, Doug Belshaw: Serendipity Surface & AI, Pro: Conversing with AI, Part 1-3, and Pro: February Update.
Explore all digitized human knowledge by exploring with generative AI. Part 3 in our How to Use Generative AI series.
Developing the skill to craft effective prompts is a critical aspect of working with generative AI. It's about understanding what you want, knowing how to articulate that desire in a way the machine understands, and strategically using the AI's strengths to your advantage.
How to go beyond prompting and develop your conversational AI skills. Now, as more AI collaboration is designed inside of applications, do you still need to learn how to prompt? If you want to get the most out of AI, we would say, yes.
Sensemaking is going to change. AI will allow us to find story-less, a-narrative yet meaningful correlations. Our minds will have to be open to a new kind of awe: that which a machine can make sense of that we cannot.
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.
Writing and Conversations About AI (Not Written by AI)