The New Digital Divide: "Visible" vs. "Invisible" AI (Analysis of Sept 2025 Pew Data) The "Digital Divide" is back. But this time, it is hitting the boardroom. According to the latest September 2025 Pew Research Center study , we are seeing a familiar pattern. There are distinct "haves" and "have-nots" in AI adoption, mirroring the early curves of the Internet in the 90s and Social Media in the 2010s. The data shows a public split by education and exposure. But the corporate story is even more fascinating. The "OpenAI Moment" didn't just democratize access; it forced a massive, often frantic, strategic pivot in the enterprise. ❖ The Invisible Era: Machine Learning Before November 2022, AI was already ubiquitous. We just called it Machine Learning . It lived in the basement of the enterprise—boring, profitable, and invisible. It was the engine behind medical research, eCommerce recommendatio...
The "Periodic Table" of Agent Adaptation: A New Taxonomy from Stanford & Princeton Static agents are dead. The future belongs to agents that adapt. A new, comprehensive 65-page survey from top research institutions—including Stanford, Princeton, Harvard, and the University of Washington —has just provided the industry's first full taxonomy for Agentic AI Adaptation . The paper argues that "Agentic AI" (large models that use memory, call tools, and act over multiple steps) is no longer just about execution . It is about evolution . The researchers map almost all advanced systems into just four basic patterns of adaptation. ❖ The 4 Ways Agents Adapt (The Taxonomy) The framework divides the world based on two questions: What gets updated? (The Agent or The Tools) and What is the signal? (Direct Results or Evaluations). Type A1: The "Trial & Error" Agent Mechanism: The agent is updated based on tool results . ...