Core Viewpoint - Harmonic AI, co-founded by Vlad Tenev and Tudor Achim, aims to develop an AI system capable of solving complex mathematical problems, striving for Mathematical Superintelligence (MSI) [3][20]. Group 1: Company Overview - Harmonic AI has successfully raised $100 million in Series B funding, bringing its valuation to approximately $875 million [4][17]. - The company was co-founded by Vlad Tenev, who previously established Robinhood Markets, and Tudor Achim, an expert in AI and large model training [5][15]. - Robinhood, under Tenev's leadership, achieved a market cap of around $22.7 billion and reported a revenue of $927 million with a net profit of $336 million in Q1 2025 [8][12]. Group 2: Funding and Valuation - Harmonic AI's Series A funding raised $75 million, led by Sequoia Capital, with a post-money valuation of $325 million [15]. - The recent Series B funding was led by Kleiner Perkins, with participation from Paradigm and Ribbit Capital, among others [16]. - The company intentionally set its valuation below the "unicorn" threshold of $1 billion, focusing on long-term growth rather than short-term valuation targets [18][19]. Group 3: Product Development - Harmonic AI announced its first model, Aristotle, which can formalize natural language problems into formal representations, enhancing collaboration with mathematicians [20]. - The model's performance improved from 83% to 90% on the MiniF2F benchmark, which includes various levels of mathematical problems [23]. - The ultimate goal is to create an AI system with mathematical capabilities surpassing human abilities, addressing challenges like the "hallucination" problem in AI [26][28].

Robinhood 联合创始人兼 CEO Vlad Tenev 和 Helm.ai 的联合创始人 Tudor Achim 联合创立的一个新 AI 公司 Harmonic.fun 火了，它以独特的"数学超智 能"（Mathematical Superintelligence, MSI）概念。 今天，Harmonic.fun 宣布完成了 1 亿美金 B 轮融资，由 KP 领投，Paradigm、Ribbit Capita、Sequoia Capital 以及 Index Ventures 跟投，估值近 9 亿 美金。去年 9 月份完成由 Sequoia 领投的 7500 万美金的 A 轮融资，当时估值为3.25 亿美金。 Harmonic 的理念我觉得很有意思： 真正的智能，必须根植于可验证的逻辑与严谨的数学推理 。Vlad Tenev 和 Tudor Achim 认为，当前主流的 AI 模 型，尤其是大语言模型，虽然在生成文本和理解自然语言方面表现出色，但其内在的概率性机制导致了"幻觉"现象的普遍存在。 这意味着这些模型可能会生成看似合理但实际上是虚假或不准确的信息。对于许多高风险、高精度要求的应用场景，如软件 ...