| | | | --- | --- | | 北京邮电大学 2025年毕业 | | | 人工智能 | | | 类型 | 校招 | | 地区 | 北京市 | | 行业 | 互联网/游戏/软件 | | 公司 | 字节跳动 | | 岗位 | 大模型算法研究员 | | 年薪 | 税前 ¥200万元/年 | | 薪资描述 | IIOK/月 pase | 这薪资按照一天8小时，一月21.75天算的话，一个小时就是 1091.95元 ，太夸张了， 下楼拿个快 递都能赚几百块 。后来我又在招聘网站上查了下，发现大模型算法研究员工资确实挺高，尤其是 字节这种头部互联网大厂，工资开的更高，但学历要求也不低。 | | 匿名70030939 硕 | | --- | --- | | | 北京邮电大学 2025年毕业 | | 人工智能 | | | 类型 | 校招 | | 地区 | 北京市 | | 行业 | 互联网/游戏/软件 | | 公司 | 字节 | | 岗位 | 大模型研究员 | | 年薪 | 税前 4228 加工 | 我现在在做车载上的语音app，很多操作都要和大模型对接，比如语音唤醒，语音识别，自然语言 理解，自然语言处理，对话管 ...

Core Insights - The article discusses the evolution of venture capital in China, emphasizing the significance of "dollars" in its history and the challenges faced as the industry moves beyond the dollar era [4][36] - It highlights the need for a new approach to talent development in venture capital, as the traditional methods associated with dollar funds are no longer applicable [5][36] - The conversation features insights from prominent venture capitalist Zhu Xiaohu, who reflects on the lessons learned from past investments and the changing landscape of the industry [6][36] Group 1: Historical Context - Venture capital in China has its roots in the dollar economy, with early investments primarily coming from dollar funds, which played a crucial role in shaping the industry [4][35] - The initial wave of venture capital in China was influenced by the experiences and methodologies of American dollar funds, which served as a learning platform for local investors [4][35] - The current investment themes, such as semiconductors and commercial aerospace, are seen as new challenges for dollar funds, lacking established success stories [36] Group 2: Talent Development and Investment Philosophy - Zhu Xiaohu states that cultivating a true partner in venture capital may require an investment of at least $100 million to assess their capabilities, indicating the high cost of developing talent in the industry [5][21] - The article discusses the shift in investment strategies, with a focus on the importance of financial data and profitability over brand recognition in making investment decisions [47][49] - Zhu emphasizes the need for a clear investment philosophy, prioritizing projects that demonstrate strong financial fundamentals and sustainable business models [47][50] Group 3: Lessons from Past Investments - Zhu shares experiences from past investments, such as the challenges faced with companies like LaShou and the importance of timing in entering markets [21][23] - The article highlights the pitfalls of investing in advanced technologies without considering market readiness and the maturity of the technology [25][23] - Zhu reflects on the significant returns from investments in companies like Ele.me and Didi, noting the importance of understanding user acquisition costs and market dynamics [49][50]

Core Viewpoint - The article discusses the evolution of venture capital in China, particularly the influence of dollar funds and the challenges faced in the current investment landscape as the industry transitions away from the dollar-centric model [3][4]. Group 1: Historical Context of Dollar Funds - Dollar funds have been pivotal in the development of China's venture capital industry, serving as both a starting point and a learning resource for local investors [3]. - The initial wave of venture capital in China was heavily influenced by successful dollar funds, which provided essential knowledge and experience to local entrepreneurs and investors [4]. Group 2: Challenges in the Current Investment Landscape - The current investment environment presents difficulties in nurturing new talent, as the high costs associated with training potential partners (estimated at $100 million) deter firms from investing in human capital [4][22]. - There is a growing concern about the lack of successors in the venture capital space, prompting a need to revisit and redefine investment strategies and philosophies [4]. Group 3: Investment Philosophy and Strategies - The investment philosophy emphasizes the importance of clear viewpoints over brand recognition, suggesting that a strong personal brand can lead to better investment opportunities [15][16]. - The article highlights the significance of understanding financial data and the risks associated with different investment cycles, particularly in the context of technology and hardware investments [17][21]. Group 4: Lessons from Past Investments - Historical investment experiences, such as the early decisions regarding companies like 拉手网 (Lashou) and 宁德时代 (CATL), illustrate the importance of timing and market readiness in investment success [23][25]. - The article reflects on the lessons learned from past failures, emphasizing the need for a balance between technological advancement and market maturity [27][28]. Group 5: Future Outlook and Investment Trends - The current trend in venture capital is to avoid highly concentrated investment areas, advocating for a strategy that diverges slightly from mainstream consensus to find better value opportunities [35]. - The discussion includes the potential for high-return investments in emerging technologies, stressing the importance of understanding customer needs and pricing strategies [36].

港股市场2025年整体表现突出，恒生指数年内涨幅近30%，但在连续半年的强势上攻后，港股10月以来 步入震荡盘整阶段。对于港股明年行情，近期多家券商基金机构发布了市场展望，多数机构仍看好港股 的估值优势，认为其具备持续配置价值。 日前，国海富兰克林基金权益投资总监赵晓东在接受采访时明确表示："当下最显眼的机会在港股。" 赵晓东指出，这一判断的核心逻辑首先在于港股显著的估值吸引力。"港股最大的优势就是'便宜'，"他 表示，对于同一家优质公司，特别是业务根基稳固的大蓝筹企业，港股价格往往较A股存在明显折价， 构成了天然的"安全垫"。 责任编辑：栎树 在众多板块中，赵晓东尤为看好港股银行与互联网行业。 关于银行股，他认为"港股银行股更有支撑"。赵晓东分析，尽管面临息差压力，但国内银行业整体风险 可控，大型银行经营稳健。"国内的银行以传统信贷业务为主，业务结构相对单纯，出现重大风险的概 率较低。"此外，由于港股银行股估值更低，且是内地保险资金配置高股息资产的重要通道，预计将获 得持续的增量资金流入。在具体选股上，他表示，对于成长性突出、资产质量优异的银行，估值可以适 当放宽；而对于困境反转标的，则必须要求市净率足够低 ...

专题：中国财富管理50人论坛2025年会 杨龙如介绍，工商银行自2023年以来，在传统人工智能应用基础上，围绕算力、算法、知识、应用范式 与模型安全等核心要素，构建了"工银智涌"大模型技术体系，并以此作为全行智能体创新的企业级数智 基础。目前，该体系已在金融市场、市场营销、客户服务、风险管控等20多个领域落地超过400个应用 场景。 他随后重点剖析了当前大模型在金融行业深度应用面临的四大挑战： 一是基模（基础模型）能力发展仍无法满足行业实际需要。 杨龙如表示，基模在通用任务上表现良 好，但在面对高度复杂的特定金融场景时，其专业能力往往不足。例如，直接使用基模预测小微企业违 约风险，其结果的拟合程度通常不如专业模型。因此，对基模进行领域后训练或采用模型组合应用，仍 是需要投入大量精力的重点工作。 二是高质量金融数据集依然稀缺。 他指出，尽管银行数据丰富，但能为大模型训练所用的行业高质量 数据集仍然短缺。银行内部数据分散、口径不一，专家经验与决策逻辑等隐性知识未能系统化沉淀，传 统的专业技能知识转化为大模型可用数据的工程化路径尚不清晰。以风险管理领域为例，支撑深度思维 链推理的训练数据仍显不足。 三是业务模式变革 ...

Core Viewpoint - The article emphasizes that the AI revolution is a significant competition that will impact national fortunes, highlighting the rapid advancements and implications of AI technology in various sectors [2][22]. Group 1: AI Development History - The concept of artificial intelligence was first introduced in 1956 at the Dartmouth Conference, marking the beginning of a long journey in AI research [11]. - Key milestones include the introduction of deep learning by Geoffrey Hinton in 2006 and the launch of GPT-3.5 in 2022, which significantly advanced AI capabilities [17][18]. - The article notes that AI has now entered everyday life and industries, with significant developments in China and the U.S. [18][19]. Group 2: AI Investment Landscape - By 2025, the U.S. is expected to invest over $350 billion in AI infrastructure, while China’s investment is projected to reach 630 billion RMB [41]. - The article highlights that the U.S. currently dominates AI computing power, holding 74.5% of global capacity, compared to China's 14% [43]. - The investment in AI infrastructure in China is compared to the historical investment in high-speed rail, indicating a significant commitment to AI development [41]. Group 3: AI Applications and Innovations - The article discusses the emergence of AI in various industries, including banking, where Shanghai Bank has become the first AI-native mobile bank [75]. - It highlights the rapid growth of AI-driven content production, such as AI-generated comics, which have seen a 600% increase in production [67]. - The use of AI in sectors like healthcare, logistics, and manufacturing is emphasized, showcasing its transformative potential [78][81]. Group 4: Competitive Landscape - The article outlines the competitive dynamics between the U.S. and China in AI, with both countries pursuing different strategies: the U.S. focusing on closed-source models and China on open-source models [54][55]. - It mentions that by 2025, over 80% of the world's large models will be developed in the U.S. and China, with significant advancements in image generation and text capabilities [46][49]. - The competition extends to autonomous driving, with both countries making strides in developing self-driving technologies [57]. Group 5: Future Trends and Predictions - The article predicts that the next decade will see the emergence of four trillion-dollar markets in China, including the robotics sector, which is expected to play a crucial role in manufacturing upgrades [118][120]. - It discusses the potential for AI to redefine personal capabilities and the importance of adapting to new technologies in various industries [72][98]. - The article concludes with a call for recognition of the ongoing AI revolution and its implications for the future [58].

Key Points Summary Industry Overview - The focus is on the semiconductor and computing power industries, particularly in the context of domestic substitution and advancements in technology [1][3]. Core Insights and Arguments - **Domestic Substitution Acceleration**: Domestic equipment manufacturers are enhancing capabilities and expanding cooperation, significantly increasing the domestic substitution rate in semiconductor equipment, especially in applications at the semiconductor level [1]. - **Surge in Computing Power Demand**: Applications such as mobile phones and smart terminals are driving a surge in computing power demand, with liquid cooling and power systems becoming critical components [1][6]. - **Catalysts for Overseas Computing Power Supply Chain**: The overseas computing power supply chain is expected to experience multiple catalysts in Q1 2026, with Nvidia's COWS wafer production capacity projected to grow by 60%-70% in 2026 and by 50%-60% in 2027 [1][7]. - **Profit Forecast for Zhongji Xuchuang**: Market expectations for Zhongji Xuchuang's profit in 2026 are around 35 billion to 40 billion RMB, potentially doubling to 70 billion to 80 billion RMB if Nvidia and Google maintain high growth in 2027 [1][9]. - **Focus on Large Models**: The market is particularly interested in OpenAI's GPT and XAI's Grok large models, with expectations that a new generation of large models will be released in Q1 2026, which could validate the Scaling Law [2][10]. Important but Overlooked Content - **Investment Targets in North America**: Recommended investment targets include optical module-related companies such as NewEase, Zhongji Xuchuang, Yuanjie Technology, and Tianfu Communication, with NewEase showing significant potential due to its relatively small stock price increase [4][11]. - **Liquid Cooling System Price Increase**: The price of liquid cooling systems corresponding to Nvidia's GT300 chip is approximately $1,500, which is expected to rise to $4,000 with the upgrade to Ruby 200, indicating a clear logic of simultaneous price and volume increase [4][12]. - **Key Subfields in the Semiconductor Industry**: Notable subfields include measurement detection, coating and developing, packaging equipment, and materials, with significant market potential due to low penetration rates [5]. - **Future Trends in Computing Power**: The computing power sector is expected to be a major focus over the next three to ten years, with critical supporting facilities like liquid cooling and power systems [6]. - **Investment Recommendations**: The highest certainty investment directions in the overseas computing power supply chain include the optical module industry, with a focus on NewEase, Zhongji Xuchuang, Yuanjie Technology, and Tianfu Communication, as well as the liquid cooling sector led by Yingweike [13].

以下文章来源于黄青春频道 ，作者黄青春Youth 黄青春频道 . 看清流量迁徙的切面 豆包成为字节新"王牌" 出品｜虎嗅黄青春频道 作者｜商业消费主笔 黄青春 题图｜视觉中国 上周，豆包刷足了存在感。 先是有媒体报道，火山引擎将携豆包站上春晚 AI 云独家合作的 C 位；接着豆包 DAU（日活跃用户数）破 1 亿的消息不胫而走—— 若再结合火山引擎披露豆包大模型日均 Token 调用量已超 50 万亿， 一场事先张 扬的 AI 舆论战便在 2026 年前夕打响了。 躁动的不止字节跳动：前脚，阿里调集数百名工程师聚集在西溪园区 C4 楼封闭开发千问；后脚，腾讯成立 AI Infra 部、AI Data 部及数据计算平台部，全面强化 AI 研发体系。 种种迹象显示，互联网巨头正在 AI 赛道不遗余力推进 "模型研发与 ToC 产品落地并行" 的商业化布局。 这恰恰让字节回到了最熟悉的"舒适区"——极致 ROI、极致商业效率早已刻进这家公司的 DNA，从资讯、 短视频到电商、短剧， 字节跳动向来擅长以"闪电战"在军备竞赛中弯道超车；如今，字节跳动正在 AI 混 战中，不动声色完成阶段性成果验收。 字节迎头赶上 与此 ...

Core Insights - The focus in the GenAI sector is shifting from business models to foundational hard technology capabilities, with leading companies leveraging long-term technological accumulation and ecosystem integration to drive rapid industry growth [2][3]. Group 1: Doubao Model Performance and Growth - The Doubao model's daily token usage has surpassed 50 trillion as of December 18, 2025, marking a significant increase from 30 trillion in September 2025, reflecting a growth of 417 times since its launch [20][21]. - The Doubao 1.8 model has achieved notable enhancements in tool invocation, complex instruction adherence, and OS agent capabilities, showing competitive performance against Qwen3 in key areas such as mathematical reasoning and long video analysis [32][33]. - The model's efficiency improvements have led to a clearer commercialization path, with a reduction in unit inference costs and a growing demand for inference-related computing power [21][30]. Group 2: New Product Releases and Features - Fire Mountain Engine has released several upgraded products, including the Doubao 1.8 model, Seedance 1.5 Pro for video generation, and Seedream 4.5 for image creation, enhancing the capabilities of the Doubao model family [32][38]. - The Seedance 1.5 Pro model supports high-quality audio-visual content creation with features that improve synchronization and expression, achieving a 65% increase in creative efficiency [38][43]. - The Seedream 4.5 model has improved image generation quality and stability, while the voice recognition model 2.0 has enhanced context understanding, increasing keyword recall rates by 20% [48][49]. Group 3: Integration of Qianwen APP with Gaode - The Qianwen APP has successfully integrated with Gaode Map, enabling it to transition from understanding user intent to executing specific services, such as intelligent route planning and restaurant recommendations [57][58]. - The Qianwen APP has gained significant traction, surpassing 30 million monthly active users within 23 days of its public testing [56]. - This integration lays the groundwork for future connections with other Alibaba applications, potentially creating a comprehensive super agent ecosystem [3][57].

Core Insights - The Sanya International Forum and the Fifth Sanya Wealth Management Conference highlighted the theme of "Future Positioning of Hainan Free Trade Port and New Opportunities in Sanya" [1] - Financial technology and artificial intelligence are identified as core drivers for the transformation and upgrading of the wealth management industry post-Hainan's customs closure [3] Financial Technology and AI Applications - Financial institutions are expected to gather in Hainan, leading to demands for innovation in financial markets and infrastructure [3] - AI can significantly enhance investment research efficiency, reducing report writing discrepancies from over 25% to around 15% [8] - AI systems can generate personalized asset allocation suggestions based on client profiles, covering various financial products [10] - AI plays a crucial role in risk management and intelligent customer service, enhancing operational efficiency [10] Future Outlook for Sanya - Sanya is projected to become a hub for the globalization of the Renminbi, financial technology applications, and financial data services [3][13] - The wealth management sector is shifting from yield-driven to risk-driven models, increasing the demand for financial technology and data services [6] Infrastructure and Market Development - The influx of investors will lead to the establishment of new financial institutions and innovative market infrastructure [5] - The development of trading systems, including potential 24/5 trading models, is being explored to enhance transaction efficiency [5] Data Utilization and AI Integration - Data is becoming increasingly vital in Sanya, with a focus on providing global data related to the Renminbi [11] - The introduction of AI-friendly databases aims to facilitate easier access to relevant data for wealth management institutions [11] - AI's capabilities are being integrated into customer service processes, enhancing client interactions and satisfaction [10][13]