Vincent
243 posts
I'm a big believer in open source, especially as AI improves. It was a miss to not mention the Kimi base in our blog from the start. We'll fix that for the next model 🙏 Their team clarified our usage was licensed in the tweet below. x.com/Kimi_Moonshot/…
【2026年2月20日 全球财经要闻速递】 1. 全球宏观经济与资本市场 * **经济数据：** 美国去年第四季度GDP增长率修正为1.4%，远低于市场预期的2.5%；核心PCE物价指数上涨3%，仍高于美联储目标。 * **地缘政治风险：** 特朗普总统表示将在10天内决定对伊朗的行动，中东局势再度紧张。布伦特原油及WTI原油价格持续走高，**现货黄金**避险情绪升温，逼近5000美元/盎司大关。 * **政策变动：** 美国最高法院驳回了特朗普政府的全球关税政策。 * **美股承压：** 美股周四集体收跌，道指跌超260点，标普500指数年内涨幅回吐。市场主要担忧**私人信贷领域**的潜在损失（蓝猫头鹰资本出售14亿美元贷款引发连锁反应），导致资金从金融板块流出。 2. 科技与人工智能 (AI) * **英伟达 (Nvidia)：** 股价窄幅波动，黄仁勋预告将在3月的GTC 2026大会上发布“世界前所未见”的革命性芯片。 * **OpenAI：** 传出正在进行新一轮融资，目标筹集1000亿美元，估值已高达8300亿美元。 * **中国AI概念：** 港股AI概念股爆发，智谱、MiniMax、海致科技等市值均突破3000亿港元。 * **前沿模型：** 市场关注谷歌Gemini 3.0与OpenAI GPT-5系列的商业化进程；马斯克旗下xAI计划在Q1推出6万亿参数规模的Grok 5。 3. 加密货币市场 * **市场寒流：** 比特币（BTC）目前在6.7万美元附近震荡，较去年10月12.7万美元的历史高点回落近半。 * **机构动向：** 市场情绪处于“极度恐惧”，部分对冲基金大幅减持贝莱德现货ETF；但Bitwise等机构分析师仍认为目前处于严重低估状态。 * **新趋势：** AI交易平台代币Algos One AI (AIAO) 今日上线，AI与加密技术的融合成为市场新宠。 4. 投资大佬动向 * **板块切换：** Procyon等机构投资者认为市场正处于领导板块切换期，建议关注能通过AI提升效率的**工业与非必需消费品**板块。 * **公募视角：** 多家头部公募基金在最新观点中看好“科技成长、能源转型、消费复苏”作为2026年的核心投资主线。 * **文化主权：** 知名演员马修·麦康纳呼吁艺术家利用“数字主权”对抗AI侵权，引发市场对数字资产确权的关注。 5. 公司要闻 * **亚马逊：** 超越沃尔玛成为全球营收最高的公司。 * **特斯拉：** 首辆无人驾驶电动车Cybercab在得州工厂正式下线，股价微涨。 * **沃尔玛：** 全年盈利指引不及预期，股价走跌。
Next week Friedrich Merz will embark on his first visit to China since taking office. The vibes, as they say, will be off. My piece on a relationship that has become a lot more complicated. economist.com/europe/2026/02…
World champion Alysa Liu won an Olympic gold medal in women's individual figure skating on Thursday. This makes Liu the first American woman to take the Olympic podium in this event since 2006. In an interview with 60 Minutes, Liu said Olympic gold isn’t her goal. She wanted to energize the crowd and give fans an experience. “My goal, honestly, is just to hype people up, give them an experience,” Liu said.
A very insightful interview with an $MSFT employee who works on Copilot on the SaaS disruption debate: 1. According to him, AI doesn't eliminate software value; it redistributes it. He thinks the recent declines in software share prices due to AI risk are partially justified, as it can compress margins, lower switching costs, and shift value from the application layer to the platform or maybe even the model layer. He thinks companies with strong proprietary data, deep workflow integration, and AI execution capability are more likely to expand value rather than lose it. 2. He gives a good example of value for a SaaS provider. The advantage isn't that we host your data, it's that we see patterns like no single customer can see, explaining the value of pattern intelligence across millions of records. He also thinks that in an AI world, owning where revenue decisions happen may be more valuable than owning where attention happens. 3. If SaaS gross margins move from 85% down to 50-60%, the math forces a redesign of the SaaS model. He thinks that if 20-30% of gross margin disappears, the most logical offset is sales and marketing efficiency. The industry will no longer look like the classic SaaS industry, but will more closely resemble an infrastructure economy. Not all players can sustain that 30% operating margin. 4. According to him, $MSFT's Satya always says we're going to have 1.3 billion agents by 2028. He thinks we are rapidly moving from AI that answers to a more agentic mode where AI does. The next 6-12 months are all about orchestration and enterprise control. He thinks the year won't be about AI getting smarter, but more about AI becoming more reliable and integrated into real business processes. 5. He thinks OpenAI and Anthropic realized they can't win enterprise adoption with a raw model alone. They're building distribution, partnerships, and verticalization layers to solve real workflows, not just offer a smart chatbot. The battle is shifting from model intelligence to deployment simplicity and ROI clarity. The winning formula is reducing friction between capabilities and a business outcome. Enterprise adoption accelerates when AI feels like a feature of the existing system and not a science experiment that's just bolted on the side. found on @AlphaSenseInc