Free to Read Does Not Mean Free to Train On
Free-to-read journalism is not free for AI companies to take. Alan Shimel examines copyright, licensing, fair use and the economics of AI training.
Free-to-read journalism is not free for AI companies to take. Alan Shimel examines copyright, licensing, fair use and the economics of AI training.
Alan Shimel examines Alex Karp’s warning that indispensable AI could bring greater liability, oversight and even nationalization—and what that means for control, competition and public responsibility.
President Trump has created the AI Force brand. What he has not yet created is the mission, authority or constitutional foundation that would make it a real and durable institution.
Slowing AI development sounds simple until competition, commercial incentives and geopolitics enter the picture. The real challenge may be making cooperation credible enough that rivals are willing to accept restraint.
If you tell me the technology you are building could […]
A tongue-in-cheek look at six ways AI could supposedly threaten humanity, separating dramatic extinction scenarios from the risks worth taking seriously.
The important AI security question is no longer whether a model can find a weakness. It is whether a goal-seeking agent can turn tools, permissions and reachable infrastructure into a path nobody intended.
The race for AI leadership is becoming a race to turn capital, concrete, copper and power into productive compute.
Alan Shimel reflects on his first day using OpenAI’s Astra, exploring how the model handled complex cybersecurity research, evidence gathering and editorial analysis while highlighting the importance of keeping a human at the helm.
AI is unusual because it occupies two positions at once: It is a workload the enterprise must operate and a worker acting inside the enterprise.