Госдума приняла закон о запрете депортации одной категории иностранцев14:59
Жители Санкт-Петербурга устроили «крысогон»17:52
。业内人士推荐新收录的资料作为进阶阅读
这种不对称性指向了一种更高效的分工方式：模型负责规模与多样性，人类专家负责质量与可验证性。 这正是 UniScientist 数据引擎的核心原则——产出的训练实例既有广泛的专业覆盖面，又有严格的验证保障。，推荐阅读新收录的资料获取更多信息
Each of these data companies touts its stable of pedigreed experts. Mercor says around 30,000 professionals work on its platform each week, while Scale AI claims to have more than 700,000 “M.A.’s, Ph.D.’s, and college graduates.” Surge AI advertises its Supreme Court litigators, McKinsey principals, and platinum recording artists. These companies are hiring people with experience in law, finance, and coding, all areas where AI is making rapid inroads. But they’re also hiring people to produce data for practically any job you can imagine. Job listings seek chefs, management consultants, wildlife-conservation scientists, archivists, private investigators, police sergeants, reporters, teachers, and rental-counter clerks. One recent job ad called for experts in “North American early to mid-teen humor” who can, among other requirements, “explain humor using clear, logical language, including references to North American slang, trends, and social norms.” It is, as one industry veteran put it, the largest harvesting of human expertise ever attempted.