[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"content-doc-dcio96e63f68":3},{"user":4,"document":8,"mainDocument":27,"columnUrl":29,"subscription":30,"footer":42,"text":80},{"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,"useContentVideo":5,"duration":24,"price":24,"priceText":25,"priceBadgeText":25,"priceBadgeClass":26,"freeForMinGroupLevel":24,"redirectUrl":6,"readyToStream":5},"dcio96e63f68","美国软件公司通过折扣AI产品防止客户流向OpenAI和Anthropic","\u002Fdoc\u002Fdcio96e63f68","col18178739ee","美股资讯","\u002Fcol\u002Fcol18178739ee","\u003Cp>\n\u003C\u002Fp>\u003Cp>\u003Cspan>Workday \u003Cspan>最近给部分大客户免费开放一年\u003C\u002Fspan> Sana Enterprise\u003Cspan>，很多人第一反应是：它是不是自己搭了\u003C\u002Fspan> AI \u003Cspan>基础设施，所以推理成本很低？\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>其实不是。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>美股投资网认为，\u003C\u002Fspan>Workday \u003Cspan>的路线更像是：\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>它把\u003C\u002Fspan> Gemini\u003Cspan>、\u003C\u002Fspan>GPT\u003Cspan>、\u003C\u002Fspan>Claude \u003Cspan>这类大模型，当成未来可以随时替换的“\u003C\u002Fspan>AI \u003Cspan>算力层”。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>目前\u003C\u002Fspan> Sana \u003Cspan>默认接入的是\u003C\u002Fspan> Google Gemini\u003Cspan>，但\u003C\u002Fspan> Workday \u003Cspan>真正掌握的核心不是模型，而是：\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>企业\u003C\u002Fspan>HR \u003Cspan>数据\u003C\u002Fspan> + \u003Cspan>财务数据\u003C\u002Fspan> + \u003Cspan>公司权限\u003C\u002Fspan> + \u003Cspan>工作流\u003C\u002Fspan> + \u003Cspan>审批规则\u003C\u002Fspan> + AI Agent\u003Cspan>。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>比如员工问：\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>“我刚生了孩子，帮我添加家属、更新福利，再告诉我还有多少产假。”\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>Gemini \u003Cspan>负责理解和推理，但真正知道员工身份、福利计划、公司政策、审批流程，并能执行操作的，是\u003C\u002Fspan> Workday\u003Cspan>。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>所以它的产品更像：\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>Gemini \u002F GPT \u002F Claude\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>↓\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>Workday Sana\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>↓\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>企业数据\u003C\u002Fspan> + \u003Cspan>权限\u003C\u002Fspan> + \u003Cspan>工作流\u003C\u002Fspan> + Agent\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>↓\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>真正执行\u003C\u002Fspan> HR \u003Cspan>和财务任务\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>这也是为什么\u003C\u002Fspan> Workday \u003Cspan>没必要自己训练一个\u003C\u002Fspan> GPT-5 \u003Cspan>级大模型。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>未来它甚至可以做模型路由：\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>简单任务\u003C\u002Fspan>\u003Cspan>→\u003C\u002Fspan>\u003Cspan>小模型\u003C\u002Fspan> \u002F \u003Cspan>开源模型\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>复杂任务\u003C\u002Fspan>\u003Cspan>→\u003C\u002Fspan> Gemini \u002F GPT \u002F Claude\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>谁更便宜、更强，就用谁。\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>所以\u003C\u002Fspan> Workday \u003Cspan>免费送一年\u003C\u002Fspan> Sana\u003Cspan>，重点未必是“\u003C\u002Fspan>AI \u003Cspan>成本有多低”，而是先让客户把更多工作流搬进\u003C\u002Fspan> Sana\u003Cspan>。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>一旦\u003C\u002Fspan> HR\u003Cspan>、财务、审批和\u003C\u002Fspan> Agent \u003Cspan>都开始围绕\u003C\u002Fspan> Sana \u003Cspan>运转，客户以后换掉的就不只是一个软件，而是一整套\u003C\u002Fspan> AI \u003Cspan>工作方式。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>\u003Cspan>这才是\u003C\u002Fspan> Workday \u003Cspan>真正想赌的未来。\u003C\u002Fspan>\u003C\u002Fspan>\u003C\u002Fp>\n\u003Cp>\u003Cspan>$WDAY $GOOGL 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src=\"\u002Fimg\u002Fstockwewebfiles\u002Fweb-202408-stk\u002F1586109431mceclip0.jpg\">\u003C\u002Fa>\u003C\u002Ffigure>\u003Cdiv class=\"text-center\">\u003Ch2 class=\"card-title mx-auto\">\u003Cbr>\u003Ca rel=\"noopener noreferrer\" href=\"https:\u002F\u002Fstockwe.com\u002Fdoc\u002Fdcio537efad5\">案例介绍：英伟达深度研究报告\u003C\u002Fa>\u003C\u002Fh2>\u003C\u002Fdiv>",[33,37],{"productId":34,"serviceName":35,"priceText":36},"prod_PPxdDdK87QaiLv","月付","$12.95美元",{"productId":38,"serviceName":39,"priceText":40},"prod_PPxeMs3bix1da5","年付","$149.00美元",[],{"links":43,"images":71,"summaryHtml":76,"aboutTitle":77,"aboutHtml":78,"copyrightHtml":79},[44,47,50,53,56,59,62,65,68],{"label":45,"url":46},"深度报告","\u002Fcol\u002FdepthReport",{"label":48,"url":49},"VIP会员","\u002Fvip",{"label":51,"url":52},"期权推荐","\u002FOption",{"label":54,"url":55},"低价暴涨股","\u002FPenny",{"label":57,"url":58},"AI智能体","\u002FAiAgent",{"label":60,"url":61},"常见问题","https:\u002F\u002Fstockwe.com\u002FFAQ",{"label":63,"url":64},"美股课程","\u002Fcol\u002Fvideos",{"label":66,"url":67},"免责声明","\u002Fdisclaimer",{"label":69,"url":70},"联系我们","\u002FContactUs",[72,73,74,75],"\u002Fimg\u002Fstockwebsiteblob\u002Fweb-202509-stk\u002FUploaderzic2tuwsol2_2025_09_11_18_21_07.gif","\u002Fimg\u002Fstockwebsiteblob\u002Fweb-202509-stk\u002FUploadercakzdvydksw_2025_09_03_09_00_56.png","\u002Fimg\u002Fstockwebsiteblob\u002Fweb-202509-stk\u002FUploadergtjyagwvoyk_2025_09_14_08_32_05.png","\u002Fimg\u002Fstockwebsiteblob\u002Fweb-202509-stk\u002FUploader3u0tt4jhlqh_2025_09_23_22_30_48.png","邮箱: buy@TradesMax.com 美国电话 626-378-3637","公司介绍","\u003Cp class=\"MsoNormal\">美股大数据 \u003Ca href=\"https:\u002F\u002Fstockwe.com\" rel=\"noopener\">StockWe.com\u003C\u002Fa> 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，每天处理海量股票数据：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，美股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":81,"search":82,"searchPlaceholder":82,"hotContent":83,"draft":84,"noData":85,"searchNoData":86,"courseContent":87,"more":88,"buyNow":89,"subscribeNow":90,"encoding":91,"paidContent":92},"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","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"]