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"title": "270亿参数塞进iPhone！苹果洽谈AI新创 54GB大模型缩至不到4GB",
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"description": "《CNBC》周二 (14 日) 报导，苹果 (AAPL-US) 正与矽谷人工智慧 (AI) 新创 PrismML 进行初步洽谈，评估一项能将大型 AI 模型大幅压缩、直接在 iPhone 上运行的技术。PrismML 声称，已成功将阿里巴巴(BAB",
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"content": "<p>《CNBC》周二 (14 日) 报导，苹果 (AAPL-US) 正与矽谷人工智慧 (AI) 新创 PrismML 进行初步洽谈，评估一项能将大型 AI 模型大幅压缩、直接在 iPhone 上运行的技术。PrismML 声称，已成功将阿里巴巴 (BABA-US)(09988-HK) 开源通义千问 (Qwen) 模型从约 54GB 压缩至不到 4GB，使拥有 270 亿个参数的完整模型得以在 iPhone 15 或更新机型上运行，有望突破苹果 AI 策略长期面临的记忆体与运算能力限制。</p>\n<p style=\"text-align:center;\"><img src=\"https://cimg.cnyes.cool/prod/news/6534926/l/291e0608ccd62093f5ef1f0329dff4ad.jpg\" alt=\"270亿参数塞进iPhone！苹果洽谈AI新创 54GB大模型缩至不到4GB\" style=\"width:50%;height:auto;border-radius:6px;margin:15px auto;display:block;\"></p>\n\n\n<p>PrismML 执行长哈西比 (Babak Hassibi) 向《CNBC》表示，苹果及其他企业目前正评估该公司的模型，测试其在装置上的速度、能源效率及效能。他形容双方讨论仍处于非常初期阶段，未来结果尚不明朗，但「进展相当顺利」。</p>\n\n<p>苹果并未立即回应置评请求。PrismML 则在周二公开发布两个免费的压缩模型版本，可在 iPhone、MacBook 及搭载辉达 (NVDA-US) 晶片的个人电脑 (PC) 等一般消费性装置上运行。</p>\n\n<h6>270 亿参数塞进 iPhone AI 模型记忆体需求大减</h6>\n\n<p>PrismML 是由加州理工学院 (Caltech) 研究团队衍生的新创公司，获 Khosla Ventures 支持，今年 3 月完成 1,625 万美元种子轮融资。</p>\n\n<p>该公司的核心技术在于大幅简化 AI 模型内部资讯的储存方式，将每个数值从原本 16 位元 (bit) 降低至仅 1 位元，或只使用三种可能数值，借此大幅降低储存及运行模型所需的记忆体。</p>\n\n<p>根据 PrismML 说法，经过压缩的模型可减少 10 至 15 倍记忆体需求，生成回应速度提高 6 至 8 倍，能源消耗则降低 3 至 6 倍。以阿里巴巴通义千问模型为例，原本约 54GB 的模型可缩小至不到 4GB，让全部 270 亿个参数直接在 iPhone 15 或更新机型上运行。</p>\n\n<p>不过，压缩并非毫无代价。哈西比坦言，PrismML 模型的整体效能通常会损失几个百分点，其中事实记忆能力较早受到影响，但推理、数学及程式设计等能力相对能够保留。</p>\n\n<p>PrismML 目前已免费发布两个压缩模型版本，可在 iPhone、MacBook 及搭载辉达晶片的 PC 等一般装置上运行，下一步则计划挑战 Google(GOOGL-US) 开源 Gemma 模型，以及目前通常需要资料中心硬体才能运行的更大型模型。</p>\n\n<h6>苹果寻找 AI 突破口 更多 Siri 功能有望留在 iPhone</h6>\n\n<p>这项技术正值苹果寻求强化 AI 竞争力的关键时刻。苹果日前开放 iOS 27 公开测试版，让更多 iPhone 用户首次接触延宕已久的 Siri 重大改版。面对 OpenAI 及 Anthropic 等业者的 AI 助理竞争，苹果正试图提升 Siri 能力，同时维持将个人资料与更多 AI 运算留在装置端的隐私策略。</p>\n\n<p>目前最强大的 AI 模型通常需要大量记忆体及运算能力，难以直接在智慧手机运行。若能将更多 AI 功能直接搬进 iPhone，不仅可以降低资料传送至远端伺服器造成的延迟及云端运算成本，也能强化隐私保护，甚至让部分功能在没有网路连线时正常运作。</p>\n\n<p>分析师认为，更小型的模型可能让苹果把运算摄影、影片生成，以及涉及敏感个人资料的健康与健身工具等更多高运算需求功能移至 iPhone 端。</p>\n\n<p>苹果同时设计 iPhone 晶片与软体，因此能更精准控制 AI 模型在装置上的运行方式，相较其他业者可能具有软硬体垂直整合优势。不过分析师也警告，PrismML 提出的惊人效能数据仍需接受真实世界的大规模测试，包括长提示词下的模型表现、多工处理时的电池消耗，以及面对数百万次查询时的可靠性。</p>\n\n<h6>AI 模型愈来愈省记忆体 晶片需求会被颠覆吗？</h6>\n\n<p>PrismML 的技术突破也正值市场激烈争论 AI 效率提升是否最终会降低记忆体晶片及昂贵资料中心基础设施需求之际。</p>\n\n<p>记忆体已成为消费电子产品与 AI 伺服器最大的供应瓶颈及成本来源之一。摩根士丹利估计，苹果 2027 会计年度平均 DRAM 每位元成本可能较去年同期飙升约 190%，NAND 成本则可能增加约 180%。为保护利润率，大摩预期苹果可能将同级 iPhone 18 机型起售价提高约 200 美元。</p>\n\n<p>PrismML 声称，其技术可以让原本需要 8 颗 GPU 运行的云端模型缩减至仅需 1 颗，甚至让过去必须依靠伺服器的 AI 模型直接移至手机及笔电，因此可能降低完成特定 AI 任务所需的记忆体或运算能力。</p>\n\n<p>不过，这并不必然代表整体晶片需求将下降。D.A. Davidson 分析师卢里亚 (Gil Luria) 指出，缩小 AI 模型并不会消除对处理器或记忆体的需求，而可能只是将更多晶片需求从资料中心转移至手机及其他终端装置。</p>\n\n<p>此外，AI 效率提升也可能刺激更多使用需求，而非降低整体支出，因为更便宜、更快速的 AI 将催生新产品，并鼓励消费者更频繁使用模型。</p>\n\n<p>对苹果而言，如果能将更强大的 AI 直接放进 iPhone，可能有助于改善 Siri，同时保留隐私与软硬体整合两项核心优势。未来更可能形成云端与装置端 AI 分工模式：复杂任务交由云端处理，涉及敏感资料、低延迟及高度隐私需求的工作，则直接在装置端执行。</p>\n<div class=\"related-articles seo-links\">\n <h4>相关阅读</h4>\n <ul>\n <li><a href=\"/new/mg/article-4148.html\" title=\"矽谷大转向！美国科技巨头悄悄将中国AI模型纳入核心基础设施 GLM与Kimi受青睐\">矽谷大转向！美国科技巨头悄悄将中国AI模型纳入核心基础设施 GLM与Kimi受青睐</a></li>\n <li><a href=\"/new/mg/article-9608.html\" title=\"台积电ADR涨2.7% Wedbush：3奈米产能扩张可望提前达标\">台积电ADR涨2.7% Wedbush：3奈米产能扩张可望提前达标</a></li>\n <li><a href=\"/new/mg/article-6467.html\" title=\"SK海力士ADR暴跌逾9% 费半下杀近5% 美韩科技股波动「正加速连动」\">SK海力士ADR暴跌逾9% 费半下杀近5% 美韩科技股波动「正加速连动」</a></li>\n <li><a href=\"/new/mg/article-4126.html\" title=\"美银示警「避险夏季」来了 紧盯二大关键防线\">美银示警「避险夏季」来了 紧盯二大关键防线</a></li>\n <li><a href=\"/new/mg/article-4621.html\" title=\"航空股迎暑假旺季强势起飞 低油价、旅游热成双引擎\">航空股迎暑假旺季强势起飞 低油价、旅游热成双引擎</a></li>\n <li><a href=\"/new/mg/article-10719.html\" title=\"辉达Rubin Ultra「降规」反成利多 瑞银看好美光受惠\">辉达Rubin Ultra「降规」反成利多 瑞银看好美光受惠</a></li>\n </ul>\n</div>",
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