{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/746733de54554b8cab625f275adbc267\" frameborder=\"0\" width=\"1264\" height=\"948\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":948,"width":1264,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":948,"thumbnail_width":1264,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/746733de54554b8cab625f275adbc267-ac0a8700510619e4.gif","duration":229.536,"title":"Anchoring New AI Categories with Familiar Ones","description":"This Loom explains how Sandbox introduces a new product category, large quantitative models (LQMs), by anchoring them to the already understood concept of large language models (LLMs). The author describes how the site repeatedly compares the two, stating that LLMs are cost competitive and cutting tools, while LQMs are value creation engines for use cases like drug discovery and battery chemistry. The Loom emphasizes that education is needed because LQMs are likely less known, and that linking a new category to an existing one helps people grasp the difference. The key takeaway is that this anchoring approach makes a new technology category easier to understand than creating it from nothing."}