A startup claims it broke through a bottleneck that's holding back LLMs

Miami-based Subquadratic has emerged from stealth claiming to have resolved a mathematical constraint—likely related to the quadratic attention scaling problem—that has limited large language model efficiency for nearly a decade. Initial skepticism was widespread given thin technical disclosures, but the company has since begun sharing supporting evidence. Whether this constitutes a genuine architectural breakthrough or a well-marketed incremental improvement remains to be carefully evaluated by the broader research community.