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工业AI+“出海”重塑“中国制造”竞争力
Zhong Guo Chan Ye Jing Ji Xin Xi Wang· 2025-07-24 23:23
Core Insights - A recent IDC survey indicates that 77.9% of Chinese manufacturing companies with annual revenues exceeding 1 billion yuan have overseas operations or are actively planning to expand internationally, while 54% are exploring the integration of artificial intelligence (AI) into their operations [1][2] - The current "going global" strategy for Chinese manufacturing companies is categorized into three stages: "Going Global" 1.0 (products), 2.0 (supply chains), and 3.0 (brands and services), with digitalization playing a crucial role in accelerating growth at each stage [1][2] Group 1: "Going Global" 1.0 - In the "Going Global" 1.0 product stage, companies view international expansion as a new growth engine, but compliance is essential for sustainable growth. Cloud-based applications can provide comprehensive solutions for data protection, privacy, and industry compliance [1] - Companies should also focus on channel investment, lead management, customer conversion, logistics, collaboration, and after-sales service to drive growth [1] Group 2: "Going Global" 2.0 - In the "Going Global" 2.0 stage, which involves overseas factories and supply chains, industrial digitalization helps manufacturing companies achieve a balance among efficiency, cost, and quality [2] - 42% of manufacturing companies believe that quality assurance is crucial for establishing trust and building brands in international markets. AI-based industrial inspection solutions are becoming mature in various industries, with large models potentially replacing multiple smaller models [2] Group 3: "Going Global" 3.0 - The "Going Global" 3.0 stage focuses on global innovation in brands and services, utilizing integrated product innovation platforms to achieve local market adaptation while enabling global collaboration in product development [2] - The emergence of domestic large models and open-source technologies is significantly lowering the barriers to AI/GenAI development, accelerating its penetration into the industrial sector. The AI+ industrial software market is expected to grow at a compound annual growth rate (CAGR) of 41.4% from 2024 to 2029, compared to 19.3% for core industrial software [2] Group 4: Future of Industrial AI - Despite the advancements in industrial AI, traditional industrial software will continue to dominate the market, accounting for nearly 80% of the mainstream market, serving as a vital infrastructure for the application of industrial AI [3]
从多模态融合到行业深扎,国内 AI 大模型三大发展方向解析
Sou Hu Cai Jing· 2025-07-07 03:36
Core Insights - The development of AI large models in China is being driven by various institutions such as Baidu, Alibaba, ByteDance, and iFlytek, focusing on technical deepening, application expansion, and ecosystem construction [2][3][4] Technical Deepening - Multi-modal integration is a key focus, with institutions like iFlytek and ByteDance enhancing their models to process and respond to various forms of input, including voice, gestures, and emotions, leading to more natural user interactions [2] - Improvement in reasoning capabilities is being pursued, with ByteDance's Doubao 1.6 - thinking achieving top rankings in complex reasoning tests, while Baidu's Wenxin Yiyan enhances knowledge and reasoning accuracy through external knowledge sources [2] Application Expansion - Industry-specific empowerment is being emphasized, with iFlytek's plans to tailor its models for sectors such as automotive, education, healthcare, and smart cities, while Baidu and Alibaba explore applications in finance, industry, and e-commerce [3] - Innovation in intelligent applications is expected, as ByteDance transitions from an app-centric model to an agent-based model, showcasing the potential for AI to reshape software development paradigms and create new applications [3] Ecosystem Construction - Open-source initiatives are becoming a significant trend, with various models being released by institutions like ByteDance and Baidu, which encourages developer participation and enhances model performance [4] - The establishment of a robust industrial ecosystem is crucial, supported by government policies and local initiatives, such as Shanghai's comprehensive AI industrial chain, which integrates computing power, data, algorithms, and applications [4]
李彦宏:DeepSeek不是万能,最大问题是慢和贵,大多数大模型速度比DeepSeek满血版更快,价格更低【附多模态大模型行业市场分析】
Sou Hu Cai Jing· 2025-04-27 06:28
Core Insights - Baidu's founder, Li Yanhong, emphasized that DeepSeek is not a panacea and highlighted its current limitations, particularly in processing multimedia content [2][3] - DeepSeek achieved significant success by becoming the fastest application to surpass 30 million daily active users and topping the App Store charts in multiple regions, including the US [2] - The AI industry is witnessing a trend towards multimodal models, which are expected to become standard in future foundational models [6] Industry Overview - The training costs for mainstream large models in China typically range from tens of millions to hundreds of millions of dollars, with major players like Baidu, Alibaba, and Tencent investing over $200 million [4] - Startups like Kimi and DeepSeek have managed to reduce training costs to between $30 million and $60 million through technological optimizations [4] - Revenue from multimodal large models in China is concentrated among leading companies, with Alibaba Cloud generating over 110 billion yuan, accounting for about 15% of its group revenue [5] Application Insights - Li Yanhong stressed the importance of applications over models and chips, asserting that the true value lies in the applications that utilize these technologies [6] - Despite DeepSeek's shortcomings, the focus remains on finding the right scenarios and models to create lasting applications [6]
424万家!中国AI公司正在爆发式增加……
混沌学园· 2025-04-17 11:33
据天眼查专业版数据显示,截至目前,我国已拥有 424.3万家人工智能相关企业。 而上个月,这项数据还是 200万家。 一个被严重低估的真相:中国 AI公司正在爆发式增加。 过去一年,关于 "中国AI"的讨论密集涌现。从政策推动到资本狂热,从大模型军备竞赛到终端落地之争, 仿佛整个行业一夜之间集体"觉醒"。一个最直观的标志是:AI创业不再是技术圈的默默耕耘,而是当下媒 体舆论的焦点。 比如,今年年初, DeepSeek(深度求索)发布多项自研模型,并在多个任务上实现领先指标,率先在大 家的朋友圈引爆,随即也迅速在技术圈和投资圈引发轰动。 再比如前日, "AI六小虎(月之暗面、零一万物、MiniMax、智谱AI、百川智能 、阶跃星辰) "之一的智 谱AI,更是迈出历史性一步,向中国证监会北京证监局提交了上市辅导备案,成为国内大模型中首家公开 启动IPO进程的企业。 不在于技术的完美 为什么 AI的火焰在中国迅猛燃起? 是偶然,还是必然? 混沌君向DeepSeek deep seek了一下,大模型的答案很让混沌君意想不到,现在分享给大家: "资本+政策+产业"的高度协同 中国 AI产业在过去两年经历了前所未有的资本 ...
郁亮辞职了
猫笔刀· 2025-01-27 14:22
今晚的热股榜,前六个分别是英伟达、万科、台积电、寒武纪、阿斯麦、中芯国际。1个房地产,5个芯 片股,正好对应了眼下最大的两个热点。 今晚的盘前交易,英伟达目前跌11.5%,台积电跌10.7%,阿斯麦跌7.1%,还有今天已经收盘的a股,寒 武纪和中芯国际都跌了7%,都是deepseek引发的连锁反应,市场对芯片公司暂时祛魅了。 其实我觉得这个逻辑不对,deepseek用普通芯片显卡做出了更好的模型,说明他们的技术方向更先进, 并不代表好的芯片显卡就没用了。好的模型如果再搭配上好的芯片显卡,最后会呈现出更好的表现。 真正让我觉得价值崩溃的是那几个做模型的公司,原先看起来高不可攀的openai,之后想再提高估值融 资就很难了。还有号称国内起步最早的百度文心,以及国内最舍得砸钱的字节豆包,也都变的有些尴 尬。deepseek证明了这个行业的护城河很随意,你起步早,你堆人力,你砸钱多,都不能确保技术领 先,有可能新来的玩家突然一波爆兵就把你家rush了。这对于投资者来说太没有安全感了。 先顺着昨晚的话题聊聊deepseek冲击波。这事真挺突然的,一个国内a股量化基金的私募老板投资做出 来的ai模型,突然就站到了科技风口 ...