Arnold Kling: “The AI models find patterns that a human would not have spotted. That is why it is wrong to think of them as like a child savant who studies the encyclopedia. As AI models improve, they are going to be better able to find patterns that we as humans would have found. In addition, they will find patterns that we would not have found, and increasingly these will be interesting. At the same time, they will hallucinate less. It is as if their acid trips come with greater and greater clarity over time.”
WSJ: “People who would never post an Instagram video to hawk nutritional supplements or teeth-whitening strips are increasingly striking deals with brands nonetheless. Just don’t call them influencers. They are the “alternatively influential,” according to Figures, a new representation firm for public thinkers and tastemakers who have real clout in their own demesnes despite only modest internet followings—in comparison to the massive online pull of celebrities and big-time creators, the company says.”
Bloomberg: “Decades of research on how markets react to layoff announcements have established a consistent pattern: Investors punish companies that frame cuts as a response to problems. But when a company frames the same cuts as proactive restructuring, the penalty disappears. The stated reason for the layoff matters more than the fact of the layoff. AI has become the most powerful proactive frame available. “We’re restructuring around AI” is a growth signal. “We over-hired during the pandemic and revenue softened” is an accountability signal. In a market where artificial intelligence is the black hole around which everything orbits, swathing your cuts in AI-labeled wrapping paper lets you tap the valuation boost of an AI adoption story. The technology doesn’t need to work if the belief that it will does.”
FT: “Given the speed of recent rollouts, China will probably be both the testing ground and a leading indicator for agentic AI. In the US, the different parts needed to run AI systems are often controlled by separate companies. AI model developers, cloud providers and apps are separated as are payments, commerce and messaging services. A similar dynamic exists in Europe, where regulatory constraints can make integration harder. That fragmentation makes agentic AI harder to deploy at scale, as systems must navigate across multiple providers. Until now, much of the conversation about who leads the AI race has focused on model capability: who scores highest on controlled benchmarks. The US still holds the lead in models. But once AI begins to act, benchmark scores matter less than the ability to get things done. By that standard, China may already have an edge.”
