Bloomberg: “In the early 1960s, the RAND Corporation, a think tank based in Santa Monica, California, popularized the idea of red and blue teams. The red team had to think like the Soviet military and probe the US for weaknesses. The home team, or blue team, had to counter the red team, with the two often engaged in prolonged war games. The idea is simple: To fight a formidable adversary we need to think like the adversary. Think red or be red. Since then, red teaming has spread to government, business and beyond. The CIA created a new red cell in response to the September 11 attacks, and the US military extended its use of red teaming after the failures of the Iraq War. Red teaming is standard in the world of cybersecurity, where companies use internal hackers to probe their digital infrastructure. Google operates a dedicated AI red team to stress-test large language models for vulnerabilities such as the theft of sensitive data (“data exfiltration”) or using prompts to ignore ethical guardrails (“jailbreaking”). It is time to apply the methodology of red teams to the key institutions of liberalism.”
Cal Newport: “The growth of A.I. has brought new cognitive concerns. A study from January, based on surveys and interviews with more than 600 participants, revealed a “significant negative correlation between frequent A.I. tool usage and critical thinking abilities.” Another recent study, which tracked the brain activity of research subjects who were writing with the help of large language models, found that “brain connectivity systematically scaled down with the amount of external support.” The loss of our ability to think is a big deal. Close to 40 percent of the U.S. gross domestic product comes from so-called knowledge and technology-intensive industries, from aerospace manufacturing to software development to financial and information services. Companies in these fields alchemize advanced human thought into revenue; as we weaken our brains, we also threaten to weaken our economy. It is notable that productivity growth in the private business sector stagnated during the same 2010s period when technology became measurably more distracting. A diminished ability to use our brains also has concerning personal impacts. Thinking is what lets us make sense of information in a complicated world.”
WSJ: “Agents shouldn’t have human names. They shouldn’t be on org charts. And they shouldn’t be given a specific job title, Nickle LaMoreaux, chief human resources officer at IBM said,…at the WSJ Leadership Institute’s Chief People Officer Summit in Menlo Park, Calif. “We learned this the hard way,” she said. IBM used to have a series of agents that went by names like Harry, Hermione, Charlie and Sherlock. But it fell into a trap of focusing too much on each agent’s individual use cases rather than using them for more impactful large-scale process re-engineering. “Too many CPOs are getting so hung up on: what does this agent do, what does this AI do?” she said. The biggest bang for your buck, she said, isn’t in individual assistant-type agents that, say, help write emails. It’s in integrating AI into enterprise workflows.”
FT: “Since February, Chinese AI models made by groups such as DeepSeek and MiniMax have overtaken US rivals in token consumption, according to OpenRouter data, which tracks these units of text, code or data processed by large language models. The shift points to a deeper change in the AI race, with Nvidia’s Jensen Huang saying this month that the production and use of the digital units will drive the AI economy. Because developers are charged per token, it doubles as both a proxy for adoption of models and a pricing battleground between AI companies. As AI agents, such as those built on the open-source platform OpenClaw, consume vastly more tokens than earlier chatbots, the ability to cheaply produce tokens is reshaping global competition — and giving China a new edge.”
