
u/ejpusa

NYT Opinion piece: Which leaves everyone wondering: What are the implications if the administration of the world’s most powerful country is chaotic in its thinking, unpredictable in its actions and not reliably in touch with reality?
There is a silver lining in here somewhere. The Republican administration is a reflection of America. It did not make us. We elected them.
How War in the Middle East Paralyzed an Asian Food Giant: Vietnam, the world’s No. 2 rice exporter, cut production as power prices surged. Even with a temporary cease-fire in Iran, worries linger over the world’s food supply.
The Mekong Delta sprawls across Vietnam’s southern tip, covering an area larger than the Mississippi Delta. Complex irrigation networks run like capillaries through lands where shrimp are farmed, poultry is raised, and citrus, durian and rice grow side by side. Everything, including water and fertilizer, has been costlier to move since the start of the war, and no one knows whether the nations negotiating for peace can be trusted to create stability.
Side Project, AI portfolio of cool stuff. Another AI news scanner. Updates every 60 minutes. It's a bit different, using something I call "Narrative Velocity." Maybe something for Prediction people. The news sources are pretty solid. Link in comments. Feedback welcome.
GPT-5.4
Narrative Velocity is the rate at which a story, theme, or idea is gaining or losing momentum across information streams (news, social, research, markets). Instead of just asking what is being said, it measures how fast the meaning is changing and in what direction.
Mathematically, you can think of it like this:
v(t) = \frac{dN(t)}{dt}
Where: • N(t) = narrative signal strength over time (mentions, sentiment, semantic alignment, etc.) • v(t) = narrative velocity (how fast that signal is changing)
In practice, we extend this by weighting signals:
N(t) = \sum_i w_i \cdot s_i(t)
So the system is really tracking the derivative of a weighted semantic field, not just raw counts.
A new AI system for modeling “Narrative Velocity”: temporal semantic drift + directional signal detection across large text streams. Most LLM pipelines are static (summarization, QA, classification). We’re focused on temporal dynamics: how meaning evolves across consecutive windows.
Site Link: http://preceptress.ai
Input most welcome. Updates every 60 minutes. Day 1.