Group 1 - Berkshire Hathaway's top five holdings as of the end of Q2 are American Express, Apple, Bank of America, Coca-Cola, and Chevron [1]

伯克希尔哈撒韦A(BRK.A.N)第二季度未进行股票回购。 ...

坦桑尼亚总统萨米娅.苏卢胡.哈桑1日在达累斯萨拉姆出席东非商贸物流中心开业仪式，称赞这一由中国 公司投资建设的重点项目对拉动当地经济具有重要意义。哈桑总统在仪式上致辞时表示，东非商贸物流 中心不仅是商业中心，还涵盖了海外仓和跨境电商以及保税加工，是一个综合性商贸平台。该项目促进 了当地社会、经济的可持续发展和产业升级，将有效增强坦桑尼亚与东南非共同市场成员国之间的市场 联通能力，是推动地区贸易互联互通、深化坦中经贸合作的标志性工程，也展示了坦中合作的显著成 果。(新华社) ...

Group 1 - The article discusses the recent surge in gold prices driven by non-farm payroll data, indicating a significant market reaction [1] - It highlights the strategies that both bullish and bearish traders should consider for the upcoming week in response to the market movements [1] - The TTPS team is conducting a weekend review live session to analyze the current gold market trends and provide insights [1]

伯克希尔哈撒韦A(BRK.A.N)截至二季度末现金及现金等价物达3441亿美元。（截至前一季度末为3477 亿美元） ...

伯克希尔哈撒韦A(BRK.A.N)2025年Q2EPS为8601美元，市场预期7443美元，上年同期21122美元。 ...

Group 1 - Berkshire Hathaway A (BRK.A.N) reported a net profit of $12.37 billion for Q2 2025, exceeding market expectations of $10.703 billion [1] - The net profit for the same period last year was significantly higher at $30.348 billion, indicating a year-over-year decline [1]

市场消息：德国联邦议院议员基泽韦特主张德国退出《渥太华公约》。 ...

伯克希尔哈撒韦A 2025年Q2营收925.15亿美元 高于预期 智通财经8月2日电，伯克希尔哈撒韦A 2025年Q2营收925.15亿美元，市场预期919.63亿美元，上年同期 936.53亿美元；Q2净利润123.7亿美元，市场预期107.03亿美元，上年同期303.48亿美元。 ...

Core Insights - Zhejiang University Brain-Machine Intelligence National Key Laboratory has launched a new generation of neuromorphic brain-like computer named "Darwin Monkey" or "Wukong" [1] - The system supports over 2 billion pulse neurons and more than 100 billion synapses, approaching the scale of a macaque brain [1] - In typical operating conditions, the power consumption is approximately 2000 watts, making it the first neuromorphic computer with neuron scale exceeding 2 billion based on dedicated neuromorphic chips [1] - Neuromorphic computing aims to replicate the efficient computational mechanisms of biological neural networks to create low-power, high-parallel, high-efficiency, and intelligent computing systems [1]