[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"content-doc-dcio6a5b2869":3},{"user":4,"document":8,"mainDocument":27,"columnUrl":29,"subscription":30,"footer":42,"text":77},{"isAuthenticated":5,"isAdmin":5,"displayName":6,"avatarUrl":6,"nid":6,"groupLevel":7},false,"",-10,{"id":9,"fullTitle":10,"subTitle":6,"url":11,"columnId":12,"columnName":13,"columnUrl":14,"summary":6,"contentHtml":15,"mainContentHtml":6,"posterUrl":16,"createDate":17,"displayDate":18,"displayDateSlash":19,"pageviews":20,"tags":21,"hidden":5,"isSubContent":5,"replyDocOrTargetId":6,"contentType":23,"videoId":6,"liveVideoUrl":6,"duration":24,"price":24,"priceText":25,"priceBadgeText":25,"priceBadgeClass":26,"freeForMinGroupLevel":24,"redirectUrl":6,"readyToStream":5},"dcio6a5b2869","美股存储芯片股SNDK为何今日重挫？","\u002Fdoc\u002Fdcio6a5b2869","col18178739ee","美股资讯","\u002Fcol\u002Fcol18178739ee","\u003Cp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">周三美股盘中，存储芯片板块遭遇显著回调。西部数据（\u003C\u002Fspan>WDC\u003Cspan style=\"font-family: DengXian;\">）和美光科技（\u003C\u002Fspan>MU\u003Cspan style=\"font-family: DengXian;\">）均跌超\u003C\u002Fspan>4%\u003Cspan style=\"font-family: DengXian;\">，希捷科技（\u003C\u002Fspan>STX\u003Cspan style=\"font-family: DengXian;\">）跌幅超\u003C\u002Fspan>5%\u003Cspan style=\"font-family: DengXian;\">。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp> \u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cstrong>\u003Cspan style=\"font-family: DengXian;\">引发这一轮集体走弱的直接原因，是谷歌刚刚发布了一项名为\u003C\u002Fspan>TurboQuant\u003C\u002Fstrong>\u003Cstrong>\u003Cspan style=\"font-family: DengXian;\">的新型\u003C\u002Fspan>AI\u003C\u002Fstrong>\u003Cstrong>\u003Cspan style=\"font-family: DengXian;\">内存压缩技术，引发了市场对存储硬件中长期需求前景的担忧。\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp> \u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">要理解为什么一个\u003C\u002Fspan>“\u003Cspan style=\"font-family: DengXian;\">软件算法\u003C\u002Fspan>”\u003Cspan style=\"font-family: DengXian;\">的进步会吓坏\u003C\u002Fspan>“\u003Cspan style=\"font-family: DengXian;\">卖硬件\u003C\u002Fspan>”\u003Cspan style=\"font-family: DengXian;\">的公司，我们得先搞清楚大模型运行时最占资源的地方\u003C\u002Fspan>——\u003Cspan style=\"font-family: DengXian;\">键值缓存（\u003C\u002Fspan>KV Cache\u003Cspan style=\"font-family: DengXian;\">）。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp> \u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">当你在和\u003C\u002Fspan>AI\u003Cspan style=\"font-family: DengXian;\">对话，或者让它处理长文章时，为了记住前面的内容（上下文），\u003C\u002Fspan>AI\u003Cspan style=\"font-family: DengXian;\">必须在内存里实时暂存大量数据。这就像一个人为了记住长篇大论，脑子里得塞满临时的笔记。这些\u003C\u002Fspan>“\u003Cspan style=\"font-family: DengXian;\">临时笔记\u003C\u002Fspan>”\u003Cspan style=\"font-family: DengXian;\">不仅极其占用昂贵的存储空间，还拖慢了\u003C\u002Fspan>AI\u003Cspan style=\"font-family: DengXian;\">的反应速度，限制了它能同时服务多少人。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp> \u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">谷歌推出的\u003C\u002Fspan>TurboQuant\u003Cspan style=\"font-family: DengXian;\">技术，正是为了精准攻克这一硬件痛点。根据公开测试数据，该技术能够在完全不损失大模型准确性、且无需重新训练的前提下，\u003Cstrong>将键值缓存直接压缩至原先的六分之一。\u003C\u002Fstrong>\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp> \u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cstrong>\u003Cspan style=\"font-family: DengXian;\">同时，在英伟达\u003C\u002Fspan>H100\u003C\u002Fstrong>\u003Cstrong>\u003Cspan style=\"font-family: DengXian;\">加速器上，处理性能最高提升了\u003C\u002Fspan>8\u003C\u002Fstrong>\u003Cstrong>\u003Cspan style=\"font-family: DengXian;\">倍。\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan style=\"font-family: DengXian;\">这意味着，原本需要大量高昂内存硬件才能支撑的长上下文推理运算，现在通过底层数据结构的\u003C\u002Fspan>“\u003Cspan style=\"font-family: DengXian;\">瘦身\u003C\u002Fspan>”\u003Cspan style=\"font-family: DengXian;\">，用极少的内存空间就能高效完成。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">面对这种\u003C\u002Fspan>“\u003Cspan style=\"font-family: DengXian;\">以软代硬\u003C\u002Fspan>”\u003Cspan style=\"font-family: DengXian;\">的技术跨越，资本市场的第一反应往往是高度防御性的。既然单张显卡的内存吞吐效率被成倍放大，市场自然会推演：各大云服务商和企业客户未来对存储芯片的物理采购总量，是否会因此出现断崖式下滑？\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp> \u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cstrong>\u003Cspan style=\"font-family: DengXian;\">叠加存储板块今年以来已经累积了较为可观的涨幅，整体估值处于相对高位。\u003C\u002Fspan>\u003C\u002Fstrong>\u003Cspan style=\"font-family: DengXian;\">在当前容错率极低的市场环境下，任何可能削减底层硬件采购量的边际技术进展，都足以促使机构资金选择提前获利了结。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp> \u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">尽管投行如摩根士丹利随后指出，这种效率提升主要集中在推理阶段的缓存压缩，并不影响模型权重所需的高带宽内存（\u003C\u002Fspan>HBM\u003Cspan style=\"font-family: DengXian;\">）。且从长远经济学角度看，这可能触发\u003C\u002Fspan>“\u003Cspan style=\"font-family: DengXian;\">杰文斯悖论\u003C\u002Fspan>”\u003Cspan style=\"font-family: DengXian;\">：\u003C\u002Fspan>AI\u003Cspan style=\"font-family: DengXian;\">运行成本的大幅降低将使规模化部署门槛骤降，进而激活更多应用场景，最终反而推升硬件总需求。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\r\n\u003Cp> \u003C\u002Fp>\r\n\u003Cp>\u003Cspan style=\"font-size: large;\">\u003Cspan style=\"font-family: DengXian;\">但对于当下的盘面而言，远期的产业推演往往让位于短期的\u003C\u002Fspan>“\u003Cspan style=\"font-family: DengXian;\">削减需求\u003C\u002Fspan>”\u003Cspan style=\"font-family: 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buy@TradesMax.com 美国电话 626-378-3637","公司介绍","\u003Cp class=\"MsoNormal\">美股大数据 StockWe.com 是一个美国领先的金融和美股信息大数据提供商，紧盯华尔街金融市场和行情，2008年成立于美国硅谷，创始人是前纽约证券交易所资深分析师Ken，联合多位摩根斯坦利分析师，谷歌 Meta工程师利用AI和大数据，配合十多年美股实战经验和业内量化交易模型，每天处理千万级股票数据：挖掘潜力大牛股，捕捉期权异动大单，实时主力资金流向、机构持仓变化、川普突发新闻，精准买卖信号第一时间发到您手机APP。\u003C\u002Fp>","专业美股投资者都在这里",{"loading":78,"search":79,"searchPlaceholder":79,"hotContent":80,"draft":81,"noData":82,"searchNoData":83,"edit":84,"editVideo":85,"courseContent":86,"more":87,"buyNow":88,"subscribeNow":89,"encoding":90,"paidContent":91},"Loading...","搜索","热门内容","草稿","目前没有任何内容公布","当前检索内容没有数据","编辑","编辑视频","课程内容","更多","立即购买后观看","- 立即订阅 -","视频编码中...","付费内容"]