Meta AI战略重组后迎首次关键突破，内部披露迄今最强预训练大模型Avocado

每日硅谷

02/09

每日硅谷 |前沿 ▼SV Daily · FRONTIER本文共2371字阅读需要约10分钟Meta在对内部人工智能部门大刀阔斧的重组改革后迎来重要节点，其新成立的Meta Superintelligence Labs即将推出的新一代大语言模型Avocado，被公司内部定义为“迄今能力最强的预训练基础模型”。一份1月20日由该实验室产品经理Megan Fu发布的内部备忘录，向部分员工披露了这一重磅...

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Fu发布的内部备忘录，向部分员工披露了这一重磅...</p>\n\n<a href=\"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20260209141733a48dcf10&s=b\">网页链接</a>\n\n</div>\n\n\n</article>\n</div>\n</body>\n</html>\n","isBrief":false,"type":0,"news_type":1,"symbol":"LU2322448957.HKD","symbol_name":"ALLIANZ GLOBAL INTELLIGENT CITIES INCOME \"AMG\" (HKD) INC","start_time":0,"source_url":"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20260209141733a48dcf10&s=b","article_id":"2610686183","we_media_id":null,"thumbnails":[],"rights":{"source":"tencent","url":"http://gu.qq.com/resources/shy/news/detail-v2/index.html#/?id=nesSN20260209141733a48dcf10&s=b","rn_cache_url":null,"customStyle":"body{padding-top:10px;}#news_title{font-weight:bold;#titleStyle#;}#news_description span{font-size:12px;#descriptionStyle#;}.footer-note{#statement#}","selectors":".mod-LoadTzbdNews, body","filters":".relate-stock, .hot-list, .recom-box, 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Fu发布的内部备忘录，向部分员工披露了这一重磅进展，不仅证实Avocado已完成预训练核心阶段，更透露该模型在多项关键能力上实现突破，即便未完成后训练优化，也能与行业内完成后训练的领先模型同台竞争，为Meta此前受挫的AI赛道注入了强劲信心。作为大语言模型开发的初始核心环节，预训练阶段的完成意味着Avocado已通过海量数据学习掌握了通用知识、数据模式与各类事物关联逻辑，这是模型具备后续应用与优化基础的关键一步。据备忘录内容，Avocado的性能已超越当前市面上最优秀的开源基础模型，尤其在知识储备水平、视觉感知能力以及多语言处理表现三大维度上展现出亮眼实力。需要注意的是，基础模型特指尚未经过后训练的预训练大语言模型，而后训练阶段通常会借助人类反馈强化学习等技术，针对特定任务对模型进行精细化优化，让其更贴合实际应用场景，而Avocado能在未完成这一阶段的情况下实现如此表现，足以见得其预训练阶段的技术功底。此次Avocado模型的突破性进展，对Meta而言有着特殊的战略意义，这是其2025年AI赛道遭遇挫折、完成重大战略重组后的关键成果。2025年，Meta原计划推出的下一代大语言模型Llama 4遭遇性能瓶颈，不得不被迫推迟发布，即便后续推出了Maverick和Scout两个版本，其实际软件表现也让不少开发者感到失望。这一系列问题直接推动了Meta整体AI战略的重构，其中最核心的动作便是2025年6月向ScaleAI豪掷143亿美元投资，并邀请该公司CEO亚历山大・王加入Meta，牵头组建整合公司全平台AI业务的全新组织MetaSuperintelligence Labs，这一调整也让Meta开启了对AI领域前所未有的大规模投入。为了支撑AI业务的高速发展，Meta明确预计2026年的资本支出将达到1150亿至1350亿美元，较2025年增长约73%，而这些支出的核心便包括AI计算相关的成本投入。值得一提的是，Avocado模型的研发并非单纯追求性能提升，更在计算效率上实现了质的飞跃，这也为Meta控制持续攀升的AI研发成本提供了关键支撑。据Meta去年12月中旬的另一份内部备忘录披露，相较于Llama 4的Maverick版本，Avocado在文本相关任务上的计算效率提升了10倍；而对比Llama 4至今仍未对外发布、曾被推迟推出的Behemoth版本，其效率提升幅度甚至超过100倍。Meta表示，Avocado能在性能和效率上实现双重突破，得益于多方面的技术积累与研发投入。一方面，公司在训练数据上进行了严格筛选与升级，获取了更高质量的训练数据，为模型性能奠定了基础；另一方面，Meta持续加大对AI模型基础设施的投入，为高效研发提供了硬件支撑；而核心关键则是采用了确定性训练方法，这一方法能确保模型在相同的训练条件下稳定产生一致的结果，大幅提升了训练效率与模型稳定性，有效减少了研发过程中的试错成本。而计算效率的提升，不仅能降低MetaAI开发过程中的能耗，更能从根本上控制研发成本，这对于正加速追赶OpenAI、谷歌等行业竞争对手的Meta而言，无疑是至关重要的核心优势。Meta内部对Avocado模型的乐观态度，也与公司高管近期的公开表态形成呼应。在上个月瑞士达沃斯世界经济论坛期间，Meta首席技术官Andrew Bosworth就在新闻发布会上透露，公司的AI模型取得了不错的进展，整体表现非常出色，同时他也坦言，要让模型真正面向消费者落地应用，还需要完成大量的后训练优化工作。而在Meta上周的财报电话会议上，首席执行官扎克伯格也对MetaSuperintelligence Labs即将推出的首批大语言模型寄予厚望，他表示，预计首批模型会有良好的表现，但更重要的是，这些模型将向市场展现Meta在AI领域快速前进的技术轨迹，且公司计划在接下来的一年里持续推出新模型，不断推动人工智能技术前沿的发展。Avocado模型不仅是MetaAI战略重组后的一次关键成果落地，更折射出大语言模型行业的发展新趋势。从技术层面而言，Avocado在计算效率上的大幅突破，展现了mega在大语言模型研发从单纯的“参数竞赛”“性能竞赛”，转向“性能与效率兼顾”的高质量发展阶段的不断尝试，mega确定性训练等新技术的应用，为行业解决研发成本高、能耗大等痛点提供了新的思路，也让中小厂商看到了在开源赛道实现突破的可能性。而Meta凭借该模型实现的开源基础模型性能超越，也将进一步加剧开源大模型赛道的竞争，推动整个行业在基础模型研发上的技术迭代。对Meta自身来说，Avocado模型是其挽回AI赛道口碑、巩固行业地位的重要抓手，后续若能在后续训练阶段顺利完成优化，实现从技术突破到商业落地的转化，将有效补齐其在生成式AI领域的短板，与旗下社交平台、元宇宙等业务形成协同效应。但同时，Meta也面临着不小的挑战，一方面，当前模型的亮眼表现仍停留在内部测试阶段，能否经得住市场和开发者的实际检验尚未可知；另一方面，后训练阶段的优化工作繁琐且关键，如何根据不同应用场景完成精细化调优，让模型真正实现商业化落地，仍是其需要攻克的难题。此外，AI研发的高资本支出对公司现金流构成考验，后续如何平衡研发投入与商业回报，实现AI业务的可持续发展，将成为Meta后续的核心课题。整体而言，Avocado模型的出现也许可以为大语言模型行业注入新活力，而Meta凭借这一模型在AI赛道迈出的关键一步，也让行业看到了其深耕AI领域的决心。从更宏观的视角审视，Meta的千亿豪赌也折射出科技巨头面对AI变革的集体焦虑。当一项技术可能重新定义所有软件产品的形态时，没有人敢在这场竞赛中缺席。谷歌、微软、亚马逊各自押注，而Meta的选择是将全部筹码推上牌桌，不是因为它胜算最大，而是因为它输不起。Avocado能否终结Meta的AI尴尬期？答案或许要等到模型正式发布后才能揭晓。但可以确定的是，如果Avocado再次令人失望，将会加速耗尽市场对于Meta AI叙事的耐心；而如果它真能兑现内部备忘录中的承诺，Meta或许能够重新加入顶尖AI企业的牌局，甚至凭借其独特的社交生态走出一条差异化道路。在这场关乎未来的较量中，Avocado不仅是一个模型代号，更是Meta转型成败的重要风向标。编译&撰写 / 茹莉编务 / 唐唐每日硅谷  洞见前沿更多精彩▼Read More英国AI独角兽Synthesia12个月估值翻倍至40亿Humans&获4.8亿美元天价种子轮谷歌Gemini狂飙突进：API调用量五个月翻倍苹果加码AI可穿戴赛道：研发AirTag级智能pinOpenAI押注音频交互：加速迭代AI模型xAI购新址建第三座数据中心，算力冲刺2吉瓦英伟达豪掷200亿美元收购Groq核心资产OpenAI拟募资千亿美元巨资：资本从哪儿来？英伟达放弃与AWS正面抗衡，云业务转向内部赋能AI巨头先后加入专业数据争夺战特朗普传媒与核聚变公司TAE达成60亿合并协议Amazon拟豪掷100亿美元押注OpenAI剑桥大学量子衍生公司完成6000万美元A轮融资企业付费意愿遇冷，微软下调AI Agent销售目标估值1340亿！Databricks AI热潮下的双面叙事英伟达斥资20亿美元收购Synopsys贝佐斯“下海”造AI！62亿美元重注“物理智能”2026年AI Agent赛道的真实竞争格局特斯拉芯片计划联动机器人与出租车多领域协同Lambda融资15亿，联手微软建千兆瓦级“AI工厂”Databricks寻求新融资，估值突破1,300亿美元资本关注AI趋势：25亿押注下一代研究型实验室安卓之父Andy Rubin再创业，押注人形机器人Cursor获23亿融资，AI编码赛道竞争全面加速软银抛售英伟达持仓，全力押注OpenAI法律AI巨头Harvey完成1.5亿融资，估值80亿Navan上市首日破发20%，投资者仍获巨额回报OpenAI进军AI音乐赛道，巨头入场Meta完成270亿美元Hyperion数据中心融资交易软银重启机器人战略，9亿收购Agility Robotics牵头财团400亿美元收购Aligned Data CentersxAI非常规融资：马斯克筹建超级数据中心OpenAI布局AI芯片，万亿投入的野心与挑战纽交所母公司预测市场Polymarket与Kalshi竞逐Reflection AI，融资20亿估值80亿软银54亿美元收购ABB机器人，押注物理AIGoogle加速布局TPU，挑战英伟达霸权","kind":"news","is_publish_news":true,"is_publish_highlight":false,"is_publish_live":false,"is_publish_wemedia":null,"editions":null,"column":"","sentiment":"0","news_tag":"","news_rank":0,"symbols":[],"gpt_button":1,"need_auth":false,"code":"91000000","status":"200"}}}