PeopleImages/iStock via Getty Images If You Build It, Will They Come? "Oracle’s stock jumped by 25% after being promised $60 billion a year from OpenAI, an amount of money OpenAI doesn’t earn yet, to provide cloud computing facilities that Oracle hasn’t built yet, and which will require 4.5 GW of power (the equivalent of 2.25 Hoover Dams or four nuclear plants), as well as increased borrowing by Oracle whose debt to equity ratio is already 500% compared to 50% for Amazon, 30% for Microsoft and even less ...

Core Insights - The article discusses the advancements of Google's Gemini 3.0 AI model, highlighting its superior coding capabilities compared to competitors like GPT-5 and Claude [1][3][51] - Gemini 3.0 is reported to generate fully functional web applications, including a macOS-like web operating system, showcasing significant improvements in both functionality and design [6][7][22] - The model's inference speed has also improved, with tasks being completed in 1-2 minutes, which is faster than its predecessors [8][22] Group 1: Model Performance - Gemini 3.0 has demonstrated the ability to generate a fully functional web operating system, allowing users to interact with applications as if they were using a real computer [6][7] - The model's coding capabilities have been tested against various tasks, showing a trend of outperforming GPT-5 and even Claude in certain areas [3][5][51] - Users have reported that Gemini 3.0 can create complex applications, including video editors and interactive games, indicating a leap in its programming abilities [24][44] Group 2: User Experience and Feedback - Feedback from users indicates that Gemini 3.0's design and functionality are impressive, with many noting its ability to create aesthetically pleasing and functional web applications [21][22] - Some users have expressed concerns about the model's default design choices, suggesting that while improvements have been made, there are still areas for enhancement [22][24] - The model's ability to generate unique and creative outputs has led to speculation that it may dominate the front-end development space, similar to its predecessor, nano banana [21][55] Group 3: Competitive Landscape - The advancements of Gemini 3.0 position Google as a strong competitor in the AI space, particularly in coding and application development, challenging the established dominance of OpenAI's GPT-5 and Anthropic's Claude [51][55] - The article notes that while OpenAI continues to leverage its large user base for continuous application development, Google is catching up with innovative features in Gemini 3.0 [51][55] - The competitive dynamics in the AI industry are shifting, with Gemini 3.0's capabilities potentially altering user preferences and market positioning [55]

美股科技"七姐妹"盘前多数上涨，特斯拉、英伟达涨1%，亚马逊涨0.6%，苹果、谷歌A涨0.1%，微软 持平。 来源：滚动播报 ...

Group 1 - The company primarily provides thermal management products to Google [2]

India’s second-largest telecom operator, Bharti Airtel, has partnered with IBM (NYSE:IBM) to offer the U.S software firm’s services through its recently launched cloud platform, as demand for cloud computing grows. Airtel Cloud Gets A Boost Months After LaunchThe deal will allow Airtel Cloud’s customers to leverage IBM’s offerings, including AI-ready servers for applications, particularly in regulated sectors such as banking, healthcare, and government, Bharti Airtel announced in a regulatory filing on Wedn ...

Core Viewpoint - The article emphasizes the importance of reading and learning from the experiences of successful investors, particularly focusing on the transition from instinctive trading to disciplined trading, highlighting that mistakes are an integral part of the investment process [2][12][25]. Group 1: Importance of Reading and Learning - The article references Charlie Munger's belief that wisdom cannot be achieved without reading, underscoring the value of continuous learning [2][12]. - The company encourages readers to engage in discussions about books related to investment strategies, fostering a community of learning [3][5][6]. Group 2: Insights from Successful Investors - The book "From Instinctive Trading to Disciplined Trading" focuses on the failures of 16 investment masters, including Warren Buffett and Benjamin Graham, to illustrate that understanding mistakes is crucial for improving investment decisions [12][25]. - The article discusses the significant returns of companies like Amazon, Netflix, and Google, while also highlighting the volatility and risks associated with their stocks, emphasizing that high returns often come with substantial risks [13][14][15]. Group 3: The Nature of Investment - The article states that every investor will face losses and that accepting this reality is essential for achieving long-term success in the market [20][22]. - It mentions that the stock market has historically experienced significant downturns, and investors must be prepared for such fluctuations to avoid being forced sellers [21][24]. Group 4: Lessons from Charlie Munger - Charlie Munger's investment philosophy emphasizes focusing on understandable opportunities and avoiding distractions from complex investments [16][19]. - The article highlights Munger's experience with significant losses during market downturns, illustrating that enduring such challenges is part of the investment journey [20][23].

Core Insights - Independent Software Vendors (ISVs) are becoming key players in driving the commercialization of generative AI from experimentation to practical application [1][2] - The generative AI software market in the Asia-Pacific region is projected to grow to $27.6 billion by 2029, with a compound annual growth rate (CAGR) of 52.3% [1][5] - Collaboration between ISVs and cloud vendors will be crucial for the successful commercialization of generative AI [1][2] Market Opportunities - Omdia predicts that generative AI will create up to $158.6 billion in new opportunities for partners by 2028, with ISVs being among the most significant beneficiaries [2][13] - The global generative AI software market is expected to grow from $26.3 billion in 2025 to $101.3 billion by 2029, with a CAGR of 48.1% [5] Challenges Faced by ISVs - High computing and integration costs pose significant barriers for ISVs, who must invest heavily in model selection and data preparation before market validation [8] - Many ISVs lack brand recognition, making sales cycles unpredictable and complicating international market expansion due to compliance and local visibility issues [8] - The current pricing models are immature, with many projects remaining in pilot phases or highly customized deployments, hindering scalable and profitable growth [8] Cloud Vendor Strategies - Major cloud vendors are adjusting their strategies to assist ISVs in overcoming challenges, but their approaches vary [9][10] - AWS emphasizes modular combinations and a mature marketplace to help ISVs quickly build and promote AI solutions [10] - Microsoft Azure integrates AI deeply into enterprise suites but has higher entry barriers for partners [10] - Google Cloud focuses on engineering-driven paths, requiring higher self-expansion capabilities from ISVs [10] - Alibaba Cloud activates local ecosystems with low-code development tools but has a more fragmented marketplace [10] ISV Growth Stages - ISVs' growth in the generative AI space can be categorized into four stages: 1. AI Ready (Exploration Stage): Testing feasibility through APIs or demos [11] 2. AI Embedded (Deepening Stage): Integrating generative AI into existing products [11] 3. AI Native (Co-creation Stage): Embedding intelligent capabilities and enhancing market visibility [11] 4. AI Driven (Ecosystem Stage): Becoming ecosystem leaders with replicable solutions and international expansion [11] Future Outlook - Most ISVs are currently in the first two stages, focusing on reusable application scenarios and sustainable pricing models [12] - To unlock the potential of generative AI, ISVs and cloud vendors must collaborate to create scalable and practical solutions that businesses can adopt confidently [13]

机器之心报道 编辑：冷猫 先给各位读者看个视频： Prompt : Design and create a web os like mac os full functional features from text editor , to dile manager to paint to video editor and all important mac os pre bundled software Use whatever libraries to get this done but make sure I can paste it all into a single HTML file and open it in Chrome.make it interesting and highly detail , shows details that no one expected go full creative and full beauty in one code block 这条视频在海外平台爆火，这条推文已经获得了 140 多万的浏览。 看上去没什么特别的，只是一个复刻苹果 MacOS 的操作系统 ...

Core Insights - Google's Gemini 3.0 Pro has demonstrated the ability to create a fully functional web-based operating system that mimics macOS, Windows, and Linux environments using simple prompts [2][8][14] - The AI's capability to generate complex user interfaces and functionalities has led to significant excitement among users, with many considering it a potential game-changer in programming models [7][8] - Despite the impressive results, some users caution that the generated environments are merely simulations and not true operating systems, highlighting the distinction between emulation and actual implementation [14] Group 1: Gemini 3.0 Pro Capabilities - Gemini 3.0 Pro successfully replicated macOS features, including animations, window minimization, and a functional terminal, all within a single HTML file [2][3] - The AI was also able to create a web version of Windows with similar functionalities, including a text editor, terminal with Python, and a game [8][9] - Users have reported that the AI can generate a fully functional Linux desktop environment as well, showcasing its versatility [12][13] Group 2: User Reactions and Comparisons - Users expressed amazement at the capabilities of Gemini 3.0 Pro, suggesting it could become the strongest programming model to date if the final version meets expectations [7] - Comparisons were made with Claude 4.5 Sonnet, which failed to deliver similar results under the same prompts, emphasizing Gemini's superior performance [10] - The excitement surrounding Gemini 3.0 Pro has led to increased anticipation for its official release, with speculation that it may be announced in the coming months based on the frequency of demo videos [14][15]

Core Insights - Google's AI, Gemini 3.0 Pro, has demonstrated the ability to create a fully functional macOS-like web operating system from simple prompts, showcasing its advanced capabilities in UI design and functionality [2][3][4] - The AI's success in generating operating systems for macOS, Windows, and Linux within a single HTML file indicates a significant leap in programming models, potentially positioning Gemini 3.0 Pro as a leading tool in the field [10][12][15] - Despite the impressive results, some experts caution that these creations are merely simulations and not true operating systems, emphasizing the distinction between emulation and actual implementation [18] Group 1: Gemini 3.0 Pro Capabilities - Gemini 3.0 Pro can replicate macOS UI features, including animations, window management, and bundled software, all functioning correctly [4][10] - The AI can also generate a web-based Windows environment with integrated Python and gaming capabilities, demonstrating versatility across different operating systems [12][11] - A successful attempt to create a Linux desktop environment further highlights the AI's comprehensive capabilities in UI and functionality [16][15] Group 2: Community Reactions and Comparisons - Users have expressed excitement over the potential of Gemini 3.0 Pro, suggesting it could become the strongest programming model to date if the final version meets these expectations [9] - Comparisons with other AI models, such as Claude 4.5 Sonnet, reveal that Gemini 3.0 Pro outperforms its competitors in generating functional applications [13] - The community acknowledges the impressive nature of the AI's output while also recognizing the limitations of its current capabilities, particularly in terms of true operating system functionality [18] Group 3: Future Prospects - Although Google has not officially announced the release date for Gemini 3.0 Pro, industry insiders speculate it may debut in the coming months based on previous patterns [19][20] - Increased visibility through demonstration videos from influencers suggests a strategic marketing approach by Google, reminiscent of past successful campaigns [22] - The anticipation surrounding Gemini 3.0 Pro raises concerns about potential disappointment if expectations are set too high, similar to the reception of previous AI models [22]