From Static Training to Continuous Learning For most of the deep‑learning era, language models have behaved like gifted but forgetful students. They memorize vast libraries of text, shine on day‑one exams, and then freeze in time, unable to integrate new material without a costly retraining cycle. MIT researchers have now upended that workflow with Self‑Adapting […]| NATURAL 20
Automation’s Long Shadow For seventy years, machines have chipped away at human work, one incremental improvement at a time. Mainframe spreadsheets dethroned clerks, industrial robots lightened assembly lines, and, most recently, large language models began writing copy and debugging code. Labor‑force participation in the United States peaked in the 1950s and has slipped ever since, […]| NATURAL 20