Core Insights - The Generative AI market is evolving from rapid pre-trained responses to more deliberate reasoning capabilities, marking a significant shift in AI applications [1][4] - Major players like Microsoft/OpenAI, AWS/Anthropic, Meta, and Google/DeepMind are stabilizing the foundational layer of the Generative AI market, leading to a competitive landscape focused on scaling reasoning capabilities [2][10] - The introduction of models like OpenAI's o1, which utilizes inference-time compute, represents a leap in AI's reasoning abilities, allowing for more complex problem-solving and cognitive operations [3][8] Foundation Layer - The foundational layer of the Generative AI market is stabilizing with key players and alliances, indicating a shift towards a more structured market [2][10] - The competition among these players is intense, with significant price reductions in token costs, exemplified by a 98% decrease in GPT-4 token pricing [10][11] Reasoning Layer - The focus is shifting to the reasoning layer, where "System 2" thinking is prioritized, enabling AI systems to engage in deliberate reasoning and problem-solving [2][4] - The new scaling law introduced by the o1 model emphasizes the importance of inference-time compute, suggesting that the more compute allocated during inference, the better the reasoning capabilities of the model [8][9] Cognitive Architectures - The development of cognitive architectures is crucial for delivering effective reasoning capabilities, as they allow AI systems to mimic human-like thought processes [12][13] - Companies are increasingly creating sophisticated cognitive architectures that integrate multiple foundation models and application logic to enhance reasoning through workflows [15][22] Application Layer - A new cohort of agentic applications is emerging, targeting specific tasks across various sectors, such as AI lawyers, work assistants, and medical scribes, which leverage the improved reasoning capabilities of Generative AI [18][22] - The application layer is seen as a promising area for investment, with opportunities arising from the need for tailored solutions that address the complexities of real-world tasks [19][21] Investment Landscape - The investment focus is shifting towards the application layer, where companies are expected to create significant value by automating work rather than competing directly with established software companies [21][22] - The potential for AI to transform traditional business models is significant, with a shift from software-as-a-service to service-as-a-software, indicating a broader market opportunity [16][20]

本次会议为洪泽研究闭门会议仅限受邀嘉宾参会未经洪泽研究书面许可任何机构和个人不得以任何形式将会议内容和相关信息对外公布转发、转载、传播、复制、编辑、修改等如有上述未经授权的侵权行为洪泽研究保留追究相关方法律责任的权利洪泽研究不承担因转发、转载、复制、传播引起的任何损失和责任 各位投资人大家好我是宏泽研究的计算机分析师冯冠儒然后因为上周也是美股开始进入财报季了然后我们比较关心的两个软件公司SAP和ServiceNow发了财报之后当然本身基本面表现我觉得报表上的表现其实还是挺好的然后股价上的反应也 也也很猛啊所以刚好这个时间点上面再帮大家去做一个这个这个算是业绩的这个这个情况的这个这个这个处理吧然后再更新一下我们的这两个公司的这个这个面的这个观点啊那说到这两个公司的话我觉得还是先用一下这张图这张这个这个表呢是六月份发的一篇这个整个美股产业跟踪的 这个报告里面的一张表啊这里面汇集了基本上所有的云公司和比较我们比较关心的这个FAX类的这个这个公司啊然后实际上在当时就是六月份的采报的时候就上一上一个季度的这个采报结束的时候啊实际上我们就已经呃在在讲啊在讲的这个这个呃ServiceNow和这个SVP 我觉得在这张表里面其 ...

Investment Rating - The report does not explicitly provide an investment rating for the AI industry but highlights significant revenue gaps and potential for growth, indicating a cautious yet optimistic outlook on investment opportunities in AI [1][5]. Core Insights - The AI ecosystem is facing a substantial revenue gap, now quantified as a $600 billion question, reflecting the disparity between infrastructure investments and actual revenue generation [1][3]. - The supply shortage of GPUs has eased, allowing easier access for startups and companies, which is expected to influence market dynamics positively [3]. - OpenAI continues to dominate AI revenue, with reported earnings of $3.4 billion, indicating a significant gap between it and other players in the market [3]. - The previous $125 billion revenue gap has expanded to $500 billion, suggesting that major tech companies need to generate significantly more revenue from AI to meet expectations [3]. - Nvidia's upcoming B100 chip is anticipated to drive further demand, potentially leading to another supply shortage as companies rush to acquire the new technology [3]. Summary by Sections Supply and Demand Dynamics - The GPU supply shortage has subsided, making it easier for companies to access necessary hardware [3]. - Nvidia's revenue from large cloud providers has increased, with Microsoft contributing approximately 22% of Nvidia's Q4 revenue [3]. Revenue Generation and Market Gaps - OpenAI's revenue growth from $1.6 billion to $3.4 billion highlights its market leadership, while other companies struggle to scale [3]. - The projected revenue gap has increased to $500 billion, indicating a need for major tech companies to significantly enhance their AI-related revenue streams [3]. Technological Advancements - Nvidia's B100 chip promises a 2.5x performance improvement at a 25% higher cost, which is expected to stimulate demand for Nvidia's products [3]. - The report emphasizes the importance of continuous innovation in semiconductor technology, which leads to rapid depreciation of older models [4]. Market Structure and Competition - The report discusses the lack of pricing power in the GPU market, suggesting that it is becoming increasingly commoditized [4]. - Speculative investment trends in technology often lead to capital incineration, highlighting the risks associated with the current AI investment landscape [4].