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50亿红包AI战之后:谁在退场,谁能留下
3 6 Ke· 2026-02-27 11:20
Core Insights - The AI competition during the recent Spring Festival has significantly transformed social interactions, with major companies investing heavily to capture market share and educate users about AI [1][2][3] - The total investment from major players like Tencent, Alibaba, ByteDance, and Baidu exceeded 5 billion yuan, surpassing previous years' spending on similar promotional activities [1][2] Group 1: User Engagement and Market Dynamics - The engagement on social media platforms surged, with over 371 trending topics related to AI models on Weibo, accumulating 12.7 billion views and nearly 26.9 million interactions during the festival [1] - The rapid adoption of AI applications was evident, with significant increases in app downloads and user activity, such as the "Yuanbao" app reaching a peak of 1.2 billion in WeChat index within hours of its launch [3][5] - The competition among major players led to a dramatic increase in daily active users (DAU), with "Doubao" achieving 145 million, "Qianwen" at 73.5 million, and "Yuanbao" at 40.5 million during the festival [11] Group 2: Competitive Strategies and Outcomes - Companies aimed to replicate the success of past mobile payment wars by heavily subsidizing user acquisition, but the challenge remains whether these users will continue to engage post-subsidy [2][21] - "Qianwen" emerged as a dark horse, experiencing a 940% increase in user participation after launching its "Spring Festival Treat Plan," which significantly boosted its DAU [15][16] - "Doubao" maintained its lead due to effective marketing strategies, leveraging its parent company ByteDance's ecosystem for user acquisition and retention [15][16] Group 3: Industry Trends and Future Outlook - The AI industry is witnessing a clear bifurcation, with large companies focusing on user engagement and ecosystem integration, while smaller firms concentrate on technological advancements and B2B services [22][23] - The competition is expected to shift from casual interactions to solving real user needs, as companies like "Qianwen" and "Antifor" integrate AI into practical applications like e-commerce and health services [23][25] - The high operational costs associated with AI applications pose a challenge for sustainability, as the industry grapples with the balance between user growth and profitability [25]
消息称 DeepSeek V4 模型打破惯例:华为等国内厂商可早期访问,不让英伟达 AMD 先用
Xin Lang Cai Jing· 2026-02-27 10:36
IT之家 2 月 27 日消息,据路透社 2 月 26 日报道,两位了解情况的消息人士表示,DeepSeek 在即将进行重大模型更新之前,未向美国芯片制造商展示其即 将推出的旗舰模型,这打破了行业标准做法。 相反,DeepSeek V4 向国内供应商 —— 包括华为技术有限公司 —— 提供了早期访问权限。 报道提到,AI 开发者通常会将主要模型的预发布版本分享给英伟达和 AMD 等芯片制造商,以确保其软件在广泛使用的硬件上高效运行。DeepSeek 之前曾 与英伟达的技术人员密切合作。 对于其即将推出的模型,DeepSeek 没有向英伟达和 AMD 提供访问权限,而是给予包括华为在内的中国厂商几周的时间来适配其芯片。 英伟达和 AMD 拒绝评论。DeepSeek 和华为没有回应评论请求。 消息源 @legit_api 于 2 月 26 日在 X 平台发布推文,报道称 DeepSeek 正在测试 V4 Lite 模型,代号为"Sealion-lite",上下文窗口为 100 万 tokens,并是原生 支持多模态推理。 IT之家注意到,本月早些时候,DeepSeek 更新之后开始灰度测试最高 1M(百万)Tok ...
DeepSeek发布下一代技术,北大实习生立功
3 6 Ke· 2026-02-27 09:09
DeepSeek又找到突破大模型推理瓶颈的新方法了! 智东西2月27日报道,昨天,DeepSeek发布了一项名为DualPath的全新推理系统方案,直指当前大语言模型在智能体应用场景下遭遇的短板 ——KV缓存存储I/O瓶颈。该方案通过引入双路径加载机制,显著提升系统吞吐量,基本消除了KV缓存的I/O开销。 DualPath的核心创新在于开辟了一条从存储直通解码引擎的新通道。KV缓存不再仅由预填充引擎加载,而是可以加载至解码引擎,再通过计 算网络中的RDMA高效传输至预填充端。这一设计不仅缓解了存储端的压力,还避免了网络拥塞,确保延迟敏感型任务不受干扰。 与全局调度器协同后,DualPath实现了动态平衡两端负载,进一步提升资源利用率。在真实智能体工作负载测试中,DualPath将离线推理吞吐 量提升最高达1.87倍,在线服务吞吐量平均提升1.96倍。 在大规模可扩展性方面,DualPath系统在最多1152张GPU上进行了验证。离线推理从2P4D(2K智能体)扩展到48P96D(48K智能体)实现近 线性扩展,任务完成时间基本保持一致。 值得一提的是,与之前DeepSeek发表的许多研究论文类似,这篇论文的第 ...
DeepSeek 有新消息!
Mei Ri Jing Ji Xin Wen· 2026-02-27 09:06
据媒体2月27日报道,在业界对新一代旗舰模型DeepSeek V4的翘首期盼中,DeepSeek团队却悄然放出了一篇新的学术论 文。 这篇论文由DeepSeek联合北大、清华共同撰写,将研究方向投向了决定大模型实际应用落地的关键一环——推理速度,为 日益复杂的AI智能体,提供一套高效的底层系统解决方案。 具体来说,新论文介绍了一个名为DualPath的创新推理系统,专门针对智能体工作负载下的大模型(LLM)推理性能进行 优化。通过引入"双路径读取KV-Cache(类似记忆缓存)"机制,重新分配存储网络负载,将离线推理吞吐量最高提升 1.87 倍,在线服务的每秒智能体运行数平均提升 1.96 倍。 论文在引言部分提到,大模型正从单轮对话机器人和独立推理模型,快速演进为智能体系统 ——能够自主规划、调用工 具,并通过多轮交互解决实际任务。这种应用范式的转变,推动大模型推理工作负载发生重大变革:从传统的人类-大模型 交互,转向人类-大模型-环境交互,交互轮次可达数十甚至数百轮。 面对传闻,DeepSeek依旧保持其一贯的沉默,目前并未进行任何回应。 此前,DeepSeek被大量用户吐槽风格突变,"变冷淡",从原本细 ...
Anthropic指控中国AI“抄袭”,背后有何资本算计?
Sou Hu Cai Jing· 2026-02-27 08:32
图源:网络 需要说明的是,"蒸馏"是全球部分AI公司训练自家大模型的常用手段,而Anthropic自己,恰恰是"蒸馏"技术的使用者,甚至存在更激进的数据抓取行为。 值得一提的是,Anthropic如今却成了人工智能领域对中国最不友好的公司之一。2025年9月,Anthropic在官方文件中明确封禁对中资企业的服务。其实指 责中国企业进行数据蒸馏,已经成了美国企业惯用套路。就在2026年2月12日,OpenAI向美国国会提交内部备忘录,明确指控DeepSeek通过复杂的混淆手 段,绕过其安全防护对GPT系列模型实施蒸馏行为。 Anthropic这次直接对中国企业"高调指控",一个重大背景是进入2026年2月,美国AI概念股出现多轮明显下跌,资本市场对人工智能的未来产生了"颠覆传 统商业模式"的担忧。CNN评论也指出,不少所谓大模型,其实只是精心包装过的搜索引擎。 马斯克嘲讽、资本变脸,中美AI大战升级,中国凭什么破局? 开工第一天,AI圈就上演"大戏"!美国AI独角兽Anthropic突然发难,指控DeepSeek、月之暗面(Kimi)等3家中国AI企业,靠"蒸馏攻击"抄袭技术。 "蒸馏攻击"是什么?先按下不表 ...
海外价值获验证,国内市场开启高增长周期
Dongguan Securities· 2026-02-27 08:04
AI 编程行业深度报告 2026 年 2 月 27 日 卢芷心 S0340524100001 电话:0769-22119297 邮箱: luzhixin@dgzq.com.cn S0340521020001 电话:0769-22110619 邮箱: luoweibin@dgzq.com.cn S0340520060001 电话:0769-22119430 邮箱: chenweiguang@dgzq.com.cn 超配(维持) 海外价值获验证,国内市场开启高增长周期 深 度 资料来源:iFind,东莞证券研究所 投资要点: 本报告的风险等级为中高风险。 本报告的信息均来自已公开信息,关于信息的准确性与完整性,建议投资者谨慎判断,据此入市,风险自担。 请务必阅读末页声明。 SAC 执业证书编号: 罗炜斌 SAC 执业证书编号: AI Coding向"自主型Agent"跃迁,未来市场空间广阔。AI Coding已 成为众多AI应用领域中落地速度最快、发展潜力最大的细分赛道之一, 其产品或功能演进高度依赖底层大模型能力的发展。当前,国际前沿编 程大模型发展由海外厂商引领,而国产大模型正展现出强劲的追赶态 势。在发展趋 ...
DeepSeek联合北大、清华发布新论文
Cai Jing Wang· 2026-02-27 08:04
Core Insights - The article discusses a new academic paper released by the DeepSeek team in collaboration with Peking University and Tsinghua University, focusing on inference speed optimization for large language models (LLMs) [1] Group 1: Innovation and Technology - The paper introduces an innovative inference system named DualPath, specifically designed to enhance the inference performance of LLMs under agent workloads [1] - The DualPath system implements a "dual-path reading KV-Cache" mechanism, which reallocates storage network load [1] Group 2: Performance Improvements - The offline inference throughput is reported to have increased by up to 1.87 times [1] - The average number of agent operations per second for online services has improved by 1.96 times [1]
DeepSeek又一论文上新
Di Yi Cai Jing Zi Xun· 2026-02-27 07:58
Core Viewpoint - The DeepSeek team has released a new academic paper focusing on optimizing inference speed for large language models (LLMs), which is crucial for the practical application of AI agents [4][5]. Group 1: Research and Innovation - The paper, co-authored with Peking University and Tsinghua University, introduces an innovative inference system called DualPath, designed to enhance the performance of LLMs under agent workloads [4]. - The DualPath system employs a "dual-path reading KV-Cache" mechanism, redistributing storage network load, resulting in an offline inference throughput increase of 1.87 times and an average increase of 1.96 times in the number of agent operations per second for online services [4][5]. Group 2: Industry Context and Expectations - The introduction of DualPath addresses the significant changes in inference workloads as LLMs evolve from simple dialogue systems to complex agent systems capable of multi-turn interactions, which can reach dozens or even hundreds of rounds [4]. - There is a growing expectation for the release of DeepSeek's next flagship model, DeepSeek V4, with various rumors about its launch timeline ranging from early February to March [6]. - Recent leaks suggest that DeepSeek is testing a V4 Lite model, codenamed "Sealion-lite," which supports a context window of 1 million tokens and native multimodal inference [6]. Group 3: Market Reactions and Concerns - Despite the technical advancements presented in the paper, there is a sentiment in the industry that such optimizations are seen as a necessity due to GPU shortages, with some viewing it as "dirty work" rather than innovative [5]. - Concerns have been raised among investment institutions that the release of the new model could lead to significant market volatility, similar to the previous year's model launch [6].
DeepSeek又一论文上新!新模型V4更近了?
Di Yi Cai Jing· 2026-02-27 07:01
论文延续DeepSeek一贯的风格,在工程化层面将性能优化推向极致。 在业界对新一代旗舰模型DeepSeek V4的翘首期盼中,DeepSeek团队却悄然放出了一篇新的学术论文。 这篇论文由DeepSeek联合北大、清华共同撰写,将研究方向投向了决定大模型实际应用落地的关键一环——推理速度,为日益复杂的AI智能体,提供一套 高效的底层系统解决方案。 论文在引言部分提到,大模型正从单轮对话机器人和独立推理模型,快速演进为智能体系统 ——能够自主规划、调用工具,并通过多轮交互解决实际任 务。这种应用范式的转变,推动大模型推理工作负载发生重大变革:从传统的人类-大模型交互,转向人类-大模型-环境交互,交互轮次可达数十甚至数百 轮。 上下文会跨轮次累积,最终长度可能达到极值。此时模型不需要大量计算,反而需要频繁从硬盘读取历史上下文的 KV-Cache;现有系统中,只有负责预处 理的引擎会读取KV-Cache,它的网卡带宽被占满,而负责生成内容的解码引擎,网卡带宽基本闲置,导致整个系统速度被卡脖子。 因此,论文提出的DualPath,针对智能体工作负载、重新设计现代推理架构中 KV-Cache加载逻辑,解决大模型做智能 ...
688118,4分钟20%涨停!人工智能板块,主力资金净流入超100亿!
Xin Lang Cai Jing· 2026-02-27 04:30
今日早盘,A股继续小幅震荡,上证指数红绿间转换超10次,中证1000表现较强,连续第4日上涨,创 2017年4月以来近9年新高,深证成指、沪深300等则小幅下跌,市场成交保持平稳。 盘面上,稀有金属、人工智能、超临界发电、酒店餐饮等板块涨幅居前,玻璃玻纤、通信设备、消费电 子、航空装备等板块跌幅居前。 超临界发电项目持续推进 春节后,超临界发电概念频频走强,板块指数连续4日创历史新高。金现代早间仅约6分钟就垂直20%涨 停,豫能控股秒速涨停,连续第7日涨停,赣能股份亦秒板,连续第3日涨停,华银电力1分钟涨停,连 续第2日涨停。 近来,超临界发电领域利好不断。继去年底全球首台商用超临界二氧化碳发电机组在贵州六盘水首钢水 城钢铁(集团)有限责任公司成功商运后,贵州能源大方2×66万千瓦超超临界燃煤发电项目,也于今 年2月上旬完成全部27项前期核准及开工手续,主厂房基础浇筑全面启动。 项目2026年计划完成投资23.49亿元,计划于2027年底建成投产,年发电量约60亿千瓦时,配置新能源 指标290万千瓦,推动"火电+新能源"多能互补。 此外,中核集团50兆瓦"熔盐储能+超临界二氧化碳发电"示范项目已入选国家能源领 ...