Cognition

Opening — Why this matters now The race to build smarter AI agents has mostly followed one instinct: remember more. Bigger context windows. Larger vector stores. Ever-growing retrieval pipelines. Yet as agents move from demos to long-running systems—handling days or weeks of interaction—this instinct is starting to crack. More memory does not automatically mean better reasoning. In practice, it often means clutter, contradictions, and degraded performance. Humans solved this problem long ago, not by remembering everything, but by forgetting strategically. ...

Opening — Why this matters now Phishing is no longer about bad grammar and suspicious links. It is about plausibility, tone, and timing. As attackers refine their craft, the detection problem quietly shifts from raw accuracy to judgment under uncertainty. That is precisely where today’s AI systems, despite their statistical confidence, begin to diverge from human reasoning. ...

Embodied Intelligence: A Different Kind of Smart Artificial intelligence is no longer confined to static models that churn numbers in isolation. A powerful shift is underway—toward embodied AI, where intelligence is physically situated in the world. Unlike stateless AI models that treat the world as a dataset, embodied AI experiences the environment through sensors and acts through physical or simulated bodies. This concept, championed by early thinkers like Rolf Pfeifer and Fumiya Iida (2004), emphasizes that true intelligence arises from an agent’s interactions with its surroundings—not just abstract reasoning. Later surveys, such as Duan et al. (2022), further detail how modern embodied AI systems blend simulation, perception, action, and learning in environments that change dynamically. ...