Core Insights - The article discusses how to maximize the value of AI tools, emphasizing the importance of understanding user patterns and selecting the right AI model based on specific needs [1][3]. Group 1: AI Model Selection - Users have approximately nine choices for advanced AI systems, including Claude by Anthropic, Gemini by Google, ChatGPT by OpenAI, and Grok by xAI, with several free usage options available [3][4]. - For those considering paid accounts, starting with free versions of Anthropic, Google, or OpenAI is recommended before upgrading [4][6]. - The article highlights the differences in capabilities among AI models, such as web search efficiency, image creation, and handling complex tasks, which should guide user selection [4][7]. Group 2: Advanced AI Features - Advanced AI systems require monthly fees ranging from $20 to $200, depending on user needs, with the $20 tier suitable for most users [6][7]. - The article outlines the distinctions between chat models, agent models, and wizard models, recommending agent models for complex tasks due to their stability and performance [9][10]. - Users can choose specific models within systems like ChatGPT, Gemini, and Claude, with options for deeper thinking and extended capabilities [11][13][14]. Group 3: Enhancing AI Output - The article emphasizes the importance of "deep research" mode, which allows AI to conduct extensive web research before answering, significantly improving output quality [16][18]. - Connecting AI to personal data sources, such as emails and calendars, enhances its utility, particularly noted in Claude's capabilities [18]. - Multi-modal input options, including voice and image uploads, are available across various AI platforms, enhancing user interaction [19][20]. Group 4: Future Trends and User Engagement - The article predicts an increase in AI usage, with 10% of the global population currently using AI weekly, suggesting that user familiarity will evolve alongside model improvements [24]. - Users are encouraged to experiment with AI capabilities to develop an intuitive understanding of what these systems can achieve [24]. - The article warns against over-reliance on AI outputs, as even advanced models can produce errors, highlighting the need for critical engagement with AI responses [26].

RT Carlos Acevedo 🧙🏽‍♂️ (@_CarlosAce_)ChatGPT down. Claude down. Perplexity down. You know what's not down? https://t.co/ADvEtF5UzU. Still have questions, get your answers. ...

Core Insights - The Kimi K2 Thinking model developed by Moon's Dark Side has been integrated into the AI search application Perplexity, making it the only domestic model to be included alongside OpenAI's newly released GPT-5.1 [1] Group 1: Company Performance - Perplexity has experienced explosive growth since its establishment in 2022, currently boasting 30 million monthly active users and a valuation exceeding $20 billion, making it the highest-valued AI search application globally [1] Group 2: Product Innovation - Perplexity has pioneered a new category known as the conversational "answer engine," which transforms how users access and research information by providing instant answers based on the latest web information, complete with clear source citations [1] Group 3: Model Integration - Several AI applications, including Cherry Studio, Cline, CoStrict, Cursor, Genspark, Kilo Code, Kortix Suna, RooCode, Trae, Vercel, Visual Studio Code, Windsurf, and YouWare, have previously integrated with the Kimi K2 series models [1]

Group 1: Agentic Commerce Development - Agentic commerce involves consumers utilizing AI models to shop on their behalf, with technology companies like OpenAI investing heavily in this area [1][4] - OpenAI has introduced a feature allowing ChatGPT users to purchase products directly from specific merchants, with partnerships including Etsy, Walmart, and Shopify merchants [4] - Amazon has been developing its own agentic commerce features, such as the "Buy For Me" function, while also exploring partnerships with third-party providers [5][6][7] Group 2: Supply Chain and Customs Enforcement - Exiger has secured a multi-million-dollar contract with U.S. Customs and Border Protection (CBP) to combat illegal transshipment practices that bypass U.S. trade laws [2][3] - Exiger's AI models will assist CBP in enforcing tariff orders, improving data for decision-making, and tracking transshipments, thereby enhancing the efficiency of customs operations [2] - The technology aims to provide CBP agents with additional resources for scanning shipments, addressing the significant volume of goods entering the U.S. annually [2] Group 3: Warehouse Management Innovations - Blue Yonder has enhanced its Warehouse Management System (WMS) by integrating new AI capabilities, including a Warehouse Ops Agent that provides real-time updates [8][9] - The new tools, such as Resource Orchestration and Resource Forecasting, help warehouse operators allocate resources effectively based on task priorities and conditions [10][11] - These advancements aim to improve operational efficiency and effectiveness in warehouses, addressing challenges posed by disconnected systems and reactive processes [12][13]

Core Insights - The integration of AI with e-commerce is evolving, with domestic models like Doubao and Kimi embedding shopping links in their responses, indicating a shift towards AI-driven shopping experiences [1][3][4] - Internationally, platforms like ChatGPT and Perplexity are advancing faster, offering seamless shopping experiences directly within chat interfaces, which could disrupt traditional search engines and e-commerce platforms [1][7][12] - The commercial implications of AI in e-commerce are significant, potentially reshaping advertising models and challenging established players like Google and social media platforms [12][14][15] E-commerce Integration - Doubao has launched a shopping feature that provides product recommendations with direct links to Douyin's marketplace, covering various categories like electronics and beauty products [3][4] - Kimi and Wen Xiaoyan also include purchasing links in their recommendations, showcasing a trend where AI assists in the shopping process [4][8] - The initial merchants connected to these AI platforms are primarily high-rated stores within the Douyin ecosystem, indicating a focus on quality and user satisfaction [3] International Developments - ChatGPT has introduced an instant checkout feature, allowing users to make purchases without leaving the chat interface, partnering with major retailers like Walmart and Shopify [7][12] - Perplexity's "Buy with Pro" feature allows users to complete purchases directly from the AI interface, highlighting a trend towards integrated shopping experiences [7][12] Commercialization and Advertising - The move towards e-commerce integration is seen as a pivotal moment for AI commercialization, with potential shifts in how advertising is approached [12][14] - AI's ability to handle high-value queries could disrupt traditional revenue models for search engines, as it may replace the need for conventional advertising [12][14] - OpenAI's model of charging a commission on sales made through ChatGPT exemplifies a new revenue stream that diverges from traditional advertising [14] Market Dynamics - The entry of AI into e-commerce may pose a threat to traditional search engines like Google, as AI could directly answer commercially valuable queries [14][15] - In the domestic market, AI's role may resemble social media marketing, potentially impacting platforms like Xiaohongshu and Bilibili [14][15] - Despite the potential disruptions, established e-commerce platforms like Amazon and Shopify maintain advantages due to their robust logistics and fulfillment systems [15] Challenges in Domestic Market - The fragmented nature of the domestic e-commerce landscape complicates the establishment of a unified AI shopping interface, as platforms may be reluctant to share data [16][18] - AI's effectiveness as a shopping assistant relies on access to comprehensive product data and user feedback, which remains a challenge in the current market [18]

Core Insights - A large-scale study across 18 countries and 14 languages reveals systemic flaws in mainstream AI chatbots, with nearly half of the responses containing significant issues, posing a serious threat to the quality of public information retrieval [1][4] Group 1: Study Findings - The research, conducted by 22 public service media organizations, tested major AI platforms like ChatGPT, Copilot, Gemini, and Perplexity with 3,000 evaluations, finding that 45% of responses contained at least one major error, while 81% had minor issues [4] - The two main areas of concern were the lack of information sources and insufficient accuracy, affecting 31% and 30% of responses respectively [4] - The study's lead researcher warned that these errors are systemic, cross-border, and multilingual, leading to public distrust in information sources [4] Group 2: Platform Performance - Google Gemini had the highest error rate at 76%, more than double that of other products, indicating significant reliability issues [4] - Despite some improvements in models compared to six months ago, the error rates remain high, particularly in handling breaking news, complex timelines, and fact-based questions requiring viewpoint differentiation [4] Group 3: AI Adoption Trends - In contrast to the reliability issues, the adoption of AI for news consumption has surged, with user numbers doubling within a year, especially among young people aged 18-24 in Argentina and the United States [4] - Alarmingly, 48% of young users rely on AI to simplify news understanding, highlighting a growing dependency on these tools despite their shortcomings [4]

#数据 近一个月以来生成式AI网站流量占比变化：ChatGPT 76.4% → 74.1%Gemini 10.8% → 12.9%DeepSeek 4.0% → 3.7%Grok 2.2% → 2.0%Perplexity 2.0% → 2.4%Claude 1.9% → 2.0%Copilot 1.2% → 1.2%（数据来源：Similarweb） https://t.co/T30ip3GoNF ...

Core Insights - The article emphasizes the transformative potential of AI tools like ChatGPT and Perplexity in conducting deep research, significantly reducing the time required for GTM (Go-To-Market) projects from hours to minutes [2][3]. Group 1: AI Functionality and Use Cases - Deep research is highlighted as a groundbreaking AI feature that can handle complex non-engineering tasks from planning to high-quality output generation [2]. - Despite its capabilities, the adoption of deep research tools is lower than expected, partly due to the term "research" which may deter broader usage beyond academics and investors [2][3]. - The article aims to showcase real GTM use cases to inspire creative applications of deep research tools [3]. Group 2: Best Practices for Effective Research - The quality of output from deep research tools heavily relies on the sources used; AI often misjudges the credibility of sources, leading to potential inaccuracies [3][4]. - Recommendations include specifying preferred source types in prompts and creating high-quality source lists to enhance research outcomes [4][5]. - Providing context is crucial for tailored insights; users should share relevant background information to avoid generic outputs [6][7][8]. Group 3: Structuring Research Requests - Users are encouraged to clarify their research goals and the specific context of their requests to achieve more impactful results [8][9]. - Establishing a project context can streamline future research requests, reducing the need to repeat background information [10]. - Asking for a research plan before the AI begins can help align expectations and methodologies [13][16]. Group 4: Tool Comparisons and Recommendations - ChatGPT is identified as the best general-purpose deep research tool, especially after the release of GPT-5 and Agent Mode, which enhances its capabilities [24][26]. - Gemini is noted as a strong alternative with fewer usage restrictions, while Perplexity excels in specific website-focused research [26][24]. - The article provides various use cases for deep research, including competitor analysis, marketing attribution models, and international market assessments [25][41].

Core Viewpoint - News Corp CEO Robert Thomson criticized AI companies for prioritizing infrastructure investments over content creation, labeling this as a "fundamental miscalculation" [1][4]. Group 1: Investment in Content vs. Infrastructure - Thomson emphasized that AI businesses must invest significantly in "editorial content," which he considers essential for the functionality of AI systems [1][2]. - He pointed out that without substantial investment in content, AI companies risk undermining the value of their operations [1]. Group 2: Licensing and Legal Strategies - Under Thomson's leadership, News Corp has adopted a "woo or sue" strategy, engaging in licensing agreements with companies that respect copyrights while pursuing legal action against those that do not [2][3]. - News Corp's licensing deal with OpenAI, valued at over $250 million over five years, sets a precedent for future collaborations between media organizations and AI firms [3]. Group 3: Accountability and Rights Protection - Thomson highlighted the importance of transparency and accountability in the AI industry, advocating for news organizations to assert their rights proactively [6][10]. - He urged the media to continuously improve and not adopt a defensive stance, as this is not a winning strategy [8]. Group 4: Legal Landscape and Copyright Issues - A wave of copyright lawsuits has emerged against AI firms, with notable cases involving The New York Times and several other publishers [10][11]. - Thomson argued that creators of AI systems must be held responsible for the outcomes of their technologies, regardless of the complexities involved [9][10].

Core Insights - Mozilla's Firefox is integrating the AI-powered search engine Perplexity, allowing users to choose AI for web searches and information retrieval [2][3] - The integration of Perplexity is currently available in select markets, with plans for a global rollout on desktop and mobile devices [3][5] - Positive user feedback has led to the decision to make Perplexity a global search option, providing a conversational search experience with source citations [5][6] Group 1 - Mozilla announced the introduction of Perplexity as a search option in Firefox, enabling users to replace their default search engine with an AI-driven alternative [2][3] - The feature will allow users to switch to Perplexity easily through the unified search button in the address bar, and it can be configured in Firefox settings [5][6] - Mozilla is also testing the integration of Google Lens for visual search for users who have Google set as their default search engine [7] Group 2 - The decision to partner with Perplexity may be influenced by its commitment to not share or sell user personal data [6] - Mozilla has fully rolled out the multi-account configuration feature, allowing users to switch between different browser environments for work, study, or personal use [6]