About this content About Emily Jarvie Emily began her career as a political journalist for Australian Community Media in Hobart, Tasmania. After she relocated to Toronto, Canada, she reported on business, legal, and scientific developments in the emerging psychedelics sector before joining Proactive in 2022. She brings a strong journalism background with her work featured in newspapers, magazines, and digital publications across Australia, Europe, and North America, including The Examiner, The Advocate, ...

Core Insights - Generative AI is viewed as a transformative technology by Amazon's CEO Andy Jassy, indicating its potential to significantly enhance customer experiences [1] - Elon Musk predicts that humanoid robots could create a market worth $250 trillion by 2040, representing a major shift in the global economy driven by AI innovation [2] - Major firms like PwC and McKinsey acknowledge the multi-trillion-dollar potential of AI, suggesting a broad consensus on its economic impact [3] Company and Industry Analysis - A breakthrough in AI technology is redefining work, learning, and creativity, leading to increased interest from hedge funds and top investors [4] - There is speculation about an under-owned company that may play a crucial role in the AI revolution, with its technology posing a threat to competitors [4] - Prominent investors, including Bill Gates and Warren Buffett, recognize AI as a significant technological advancement with the potential for substantial social benefits [8] Market Trends - The AI ecosystem is expected to reshape how businesses, governments, and consumers operate globally, indicating a paradigm shift in various sectors [2] - The enthusiasm for AI is reflected in the investments and partnerships being formed by major companies, such as Oracle's collaboration with Nvidia [8]

最近，一篇叫《2028全球智能危机》的文章在美国炸锅了，引发硅谷剧烈波动，尽管作者再三强调它只 是篇推演，却让股市真金白银地抖了三抖，道指暴跌800点，科技股跳水。市场到底在怕什么？我们今 天就用3分钟，拆解这篇推演为何会引发巨震，以及，作为普通人的我们，该思考些什么？ 可问题是，为什么一个"科幻小说"能让市场颤抖？ 因为它的内核，戳中了一个我们正在面对、但还没想透的深层问题。我们整套经济体系，建立在"人类 智力是稀缺资源"这个假设上，分析、决策、创造、说服和协调的能力，是无法大规模复制的。但AI发 展太快了，它弥补了这部分稀缺，假设正在失效。 但别急着恐慌。作者最后把视角拉回现实，我们还没有抵达2028年，负反馈循环还没真正启动。 21世纪经济报道记者孔海丽北京报道 先讲这篇文章到底说了什么。 作者推演了一个细思极恐的未来：2028年美国失业率飙到10.2%，标普从高点跌去38%，AI越繁荣，经 济越萧条。 核心在于，AI带来了一个没有刹车的负反馈循环：AI能力越强，企业裁员越多；省下的钱买更多AI工 具，AI就越强，再继续裁员。问题是，AI和机器不会消费，不推动消费繁荣，最终大量以人类为基础 的商业模式， ...

Core Insights - OpenAI has successfully closed a $110 billion funding round, significantly surpassing its previous record raise of $50 billion from a year ago [1] - The funding round includes major investments from Amazon ($50 billion), Nvidia ($30 billion), and SoftBank ($30 billion), elevating OpenAI's pre-money valuation to $730 billion, up from $500 billion in October [2] - OpenAI aims to expand its global reach and strengthen its infrastructure through these partnerships, enabling broader access to frontier AI technologies [3] Financial Strategy - OpenAI has indicated a target of approximately $600 billion in total compute spending by 2030, following earlier statements from CEO Sam Altman regarding $1.4 trillion in infrastructure commitments [5] - The company is providing a more conservative estimate and timeline for its planned spending amid concerns about the feasibility of its expansion ambitions relative to expected revenue [5] Industry Impact - Since the launch of ChatGPT over three years ago, OpenAI has significantly influenced the technology sector and established the generative AI era [4] - Continuous funding is essential for OpenAI to support its ambitions, particularly in acquiring graphics processing units and enhancing its infrastructure [4]

CoreWeave公布第四季度营收增长110%，达到15.7亿美元，但发布的第一季度营收指引低于市场普遍预 期，并详细说明了为扩展AI基础设施所需的巨额资本支出，导致股价走低。 责任编辑：张俊 SF065 CoreWeave公布第四季度营收增长110%，达到15.7亿美元，但发布的第一季度营收指引低于市场普遍预 期，并详细说明了为扩展AI基础设施所需的巨额资本支出，导致股价走低。 责任编辑：张俊 SF065 ...

Alphabet’s Google (NASDAQ:GOOGL) (NASDAQ:GOOG) and OpenAI employees are raising their voices against the company’s plans to collaborate with the Pentagon on artificial intelligence technology.Over 100 Google staff members penned a letter to management expressing their concerns. They called for the establishment of clear boundaries or “red lines” in government contracts, akin to those pursued by Anthropic, reported the New York Times on Thursday.The employees took issue with the possible use of Google’s Gemi ...

没上市的Kimi刷屏了。 Anthropic在2月24日发文称遭到来自中国的"蒸馏攻击"，点了三家公司的名，Kimi赫然在列；OpenRouter春节期间token调用量周榜，Kimi 2.5排第二； 而 在各路大谈特谈 O pen C law风口的帖子下面， Kimi C law更以"性价比"优势被大批网友追帖提及； 此前，Kimi还在不到2个月时间内完成了12亿美元的融 资，估值超百亿美元。 这个融资规模相当于刚刚完成港股IPO的Minimax和智谱的融资金额之和。 但人家两个上市40多天涨了5倍，杨植麟和他背后的资本能不着急？ "不以上市为目的"前面应该有个"短期"的限定。 杨植麟 在2025 年 末内部信，虽然又谈到到"不着急上市"，但是， 三大战略 又 无一不含着对上市的部署。 要"追平世界前沿模型"，是因为现在K2.5没有比Minimax M2.5和GLM-5有明显优势。所以， 一切都指望K3了，要求具备"其他模型没有定义过的能力",帮 助"营收规模实现数量级增长"。 2026 Kimi-K2.5技术报告 Kimi C law 不上市可以闷声大发财，要上市则不得不造势。 不得不承认，Minimax ...

The conversational AI and AI agent evaluation platform was recognized alongside other major platforms â"¢ NEW YORK, Feb. 27, 2026 /PRNewswire/ -- LivePerson (NASDAQ: LPSN), a leading provider of predictable conversational AI, today announced Aragon Research, Inc. has positioned LivePerson in the Leader section of "The Aragon Research Globe for Agent Platforms, 2026," a report that evaluates 21 major providers of AI agent platforms and examines the shift from chatbot to sophisticated AI agent systems. "We be ...

Core Insights - The AI industry is transitioning from a "technology frenzy" to a "value realization" phase, with a focus on developing specialized intelligent agents to overcome challenges of application homogenization and low ROI [1][4][9] Group 1: Industry Trends - By 2025, China's AI core industry is projected to exceed 900 billion yuan, with over 5,300 companies, making AI applications a crucial driver for digital transformation [2] - The AI application market saw over 23,000 new companies in 2023, with 80% concentrated in common areas like intelligent customer service and voice assistants, leading to a high similarity in product interfaces [2][3] - The market is experiencing a surge in AI shopping, exemplified by Alibaba's 3 billion yuan promotional campaign, which has sparked competition among major players like Tencent and ByteDance [1] Group 2: Challenges in AI Applications - The industry faces three main bottlenecks: application homogenization, difficulties in commercial monetization, and mismatched supply and demand for computing power [2][3][7] - AI applications are struggling with low user engagement, with quality content reaching less than 0.3% of the target audience, resulting in a 65% overall loss rate in the domestic AI application market in 2023 [3][6] - Many AI products rely on similar underlying logic, leading to minimal perceived differences for users, which contributes to the homogenization issue [3][4] Group 3: Financial and Operational Insights - Despite high demand, many AI companies have not achieved substantial financial transformation, with token consumption in industrial AI applications showing significant scale compared to consumer-level products [6] - The average utilization rate of computing power in AI data centers is below 20%, leading to high energy consumption and operational inefficiencies [7] - Companies are currently facing a mismatch between high investment in AI capabilities and low revenue generation, indicating a need for better monetization strategies [7][8] Group 4: Future Directions - Experts suggest a shift from general models to specialized intelligent agents in high-value sectors like healthcare and education to address the challenges of homogenization and improve ROI [7][8] - The future of AI competition will depend on the ability to solve specific problems rather than merely utilizing large models, emphasizing the importance of industry-specific knowledge [9]

Core Insights - The commercialization of general artificial intelligence (AGI) is becoming clearer by 2026, with a focus on building intelligent agent ecosystems and enhancing reasoning capabilities [1][3] - AI is entering the cybersecurity market, reshaping the attack and defense systems, indicating a significant trend in the industry [1][3] Group 1: AGI Development - AGI is being redefined, with current AI capabilities surpassing the average human skill level, rather than requiring a "super genius" [3] - The Seedance video generation model exemplifies AGI capabilities, demonstrating significant potential in the entertainment industry [3] - Effective use of AI involves creating specialized intelligent agents that can engage in deep reasoning through role-playing and collaborative debate [3] Group 2: Intelligent Agents in Internet Economy - The rise of intelligent agents is leading to the emergence of an "agent economy," where agents will facilitate automatic price comparisons and transactions on e-commerce platforms [5] - This new business model raises questions about identity verification and accountability, particularly regarding errors made by deployed agents [5] - Intelligent agents are expected to fundamentally alter existing internet products and business models, potentially leading to parallel systems for human interaction and API access [5] Group 3: Cybersecurity Transformation - AI tools like Claude code security are revolutionizing the cybersecurity industry by efficiently scanning for vulnerabilities and generating patches, causing stock declines for traditional security firms [7] - The efficiency of AI in programming may lead to an overwhelming amount of code that humans cannot effectively manage, necessitating specialized AI tools for security [7][8] - The traditional cybersecurity model, which focuses on post-attack defense, is being challenged as AI can potentially eliminate many vulnerabilities during the coding phase [8] Group 4: Future of Cyber Attacks - Future cyber attacks are expected to evolve into "hacker agents," which will automate and scale attack methods beyond human capabilities [9] - The traditional defense strategies will likely collapse under the pressure of automated hacker agents, necessitating a shift in cybersecurity approaches [9] - Companies like 360 Group are adopting intelligent agents to enhance security operations, including vulnerability detection and automated penetration testing [9]