{"data":{"id":"cb0db498-886b-42b4-a498-6e59e92ef85e","title":"A startup claims it broke through a bottleneck that’s holding back LLMs","summary":"Subquadratic, a Miami-based AI startup, claims to have solved a mathematical bottleneck that has limited large language models (LLMs, which are AI systems trained on text to generate human-like responses) for nearly a decade. The company's new model, SubQ, reportedly runs faster, costs less, uses less energy, and can process up to 12 times more text at once than competing models while matching performance from top companies like OpenAI and Google DeepMind. Initial skepticism has been reduced after independent testing by a third-party firm called Appen validated many of Subquadratic's claims.","solution":"N/A -- no mitigation discussed in source.","labels":["industry"],"sourceUrl":"https://www.technologyreview.com/2026/06/19/1139313/a-startup-claims-it-broke-through-a-bottleneck-thats-holding-back-llms/","publishedAt":"2026-06-19T10:40:24.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"news","affectedPackages":null,"affectedVendors":["Google","OpenAI","Anthropic"],"affectedVendorsRaw":["Subquadratic","Google DeepMind","OpenAI","Anthropic","Appen"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":"2026-06-19T10:40:24.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":"model","llmSpecific":true,"classifierConfidence":0.92,"researchCategory":null,"atlasIds":null}}