That's a wrap!If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):There's a new way to build production-grade MCP servers.- It takes less than a minute.- You don't have to write any code.- You can integrate from 100k+ tools.Here's a step-by-step breakdown (100% local): ...

For years, big tech companies’ investment into developing large language models have sent asset prices soaring, creating a dynamic in which index funds are heavily weighted to a single industry.@edzitron tells @chafkin and @svaneksmith on the Everybody’s Business podcast what could happen to the economy — and your investments — should the industry falter https://t.co/qSwm0RcP17 ...

Market Trends & Industry Dynamics - Big tech companies' investment in large language models has caused asset prices to soar [1] - Index funds are now heavily weighted towards a single industry (big tech) [1] Investment Risks - The economy and investments could be negatively impacted if the big tech industry falters [1]

Market Trends & Industry Dynamics - Big tech companies' investment in large language models has caused asset prices to soar [1] - Index funds are now heavily weighted towards a single industry (big tech) [1] Investment Risks - The economy and investments could be negatively impacted if the big tech industry falters [1]

🚨 Tesla China Reportedly Integrates DeepSeek Into In-Car Voice Assistant SystemTesla has integrated Chinese large language models from ByteDance and DeepSeek into its in-car voice assistant for customers in China, according to company documents.For voice command functions such as navigation, media playback and temperature control, Tesla relies on ByteDance’s Doubao model, while interactive AI conversations are handled by the startup DeepSeek.The integration is confined to China, where strict data localizati ...

Financial Data and Key Metrics Changes - Total revenue increased by 13.1% year over year to RMB 35 billion in Q2 2025, with adjusted net profit rising by 20.1% to RMB 5.6 billion, achieving a margin of 16% [7][37][38] - Gross profit grew by 13.8% year over year to RMB 19.5 billion, with a gross profit margin of 55.7%, reflecting a 0.4 percentage point increase year over year [40][41] - Selling and marketing expenses rose by 4.6% year over year to RMB 10.5 billion, accounting for 30% of total revenue, down from 32.4% in the previous year [42] Business Line Data and Key Metrics Changes - Revenue from online marketing services reached RMB 19.8 billion, up 12.8% year over year, driven by enhanced AI capabilities [38][39] - E-commerce GMV rose by 17.6% year over year, with the number of average monthly paying users reaching 134 million [22][23] - Revenue from Clean AI surpassed RMB 250 million, indicating strong growth in AI-driven services [12][39] Market Data and Key Metrics Changes - Average DAUs on the Kuaishou app reached an all-time high of 409 million, with MAUs at 715 million, reflecting a year-over-year increase of 3.4% and 3.3% respectively [14][6] - Revenue from external marketing services continued to grow, driven by strong demand from content consumption, local services, and automotive industries [19][20] Company Strategy and Development Direction - The company is focused on integrating AI technology across its business, enhancing user experience, and optimizing marketing solutions [36][37] - The strategy includes expanding Clean AI's applications in gaming and professional film production, aiming to empower creators and enhance operational efficiency [51][53] - The company plans to discontinue separate GMV disclosures starting in 2026, focusing on a more nuanced combination of performance indicators [44][45] Management Comments on Operating Environment and Future Outlook - Management expressed confidence in the company's long-term growth prospects, emphasizing the resilience of its business ecosystem amid macro uncertainties [7][8] - The company aims to maintain high-quality growth while exploring new commercialization opportunities through AI [35][46] - Future investments will continue to focus on AI technology to enhance operational efficiencies and drive sustainable growth [86][87] Other Important Information - A special dividend of HKD 0.46 per share was declared for the first time since delisting, totaling approximately HKD 2 billion [8] - The company has repurchased shares amounting to HKD 1.9 billion, representing about 0.9% of total shares outstanding [43] Q&A Session Summary Question: What are the major use cases for Clean AI users at the moment? - Clean AI's users include mass creators and professional creators, with applications in content creation, advertising, and film production [48][50] Question: What are the AI use cases in the overall business? - AI technology is integrated across various business scenarios, enhancing marketing material generation and improving user engagement [57][59] Question: What verticals are expected to have strong growth in the second half of the year? - Growth is anticipated in local services, automotive, and content consumption industries, with strategies to enhance client outreach and marketing efficiency [66][68] Question: How does Kuaishou maintain momentum in e-commerce amid competition? - The company leverages a synergized ecosystem and tailored initiatives for merchants, focusing on user acquisition and repeat purchases [74][76]

Core Insights - Generative AI and large language models (LLMs) are significantly impacting the open web, leading to a decline in traditional search traffic for publishers and Google [3][4][5] - The shift towards LLM conversations is creating new revenue opportunities, potentially offsetting the decline in search traffic [9][12] Impact on Search Traffic - Traditional search traffic is decreasing, with some publishers experiencing drops of 20% to 50%, resulting in nearly a billion visits lost from the open web [4][6] - The competition for the diminishing search traffic is intensifying, with companies like OpenAI and Perplexity emerging as competitors to Google [3][4] Publisher Business Model Transformation - Publishers are facing a critical challenge as their revenue is closely tied to traffic, leading to a need for rethinking monetization strategies [7][8] - The concept of "zero click searches" is becoming prevalent, indicating that users are not clicking through to publisher sites after using AI search tools [5][6] Emergence of High-Value Conversations - LLM conversations are emerging as a new supply, with nearly a billion users engaging with platforms like ChatGPT and Gemini each month [10] - High-value conversations, particularly in areas like travel and finance, are estimated to represent 10% to 20% of interactions, offering greater revenue potential than traditional search clicks [10][12] Revenue Potential for Google and Publishers - Google's Gemini is positioned to capitalize on these high-value conversations, potentially transforming each interaction from being worth $1 per click to $1,000 per conversation [11][12] - Publishers can also leverage their expertise to create LLMs that facilitate high-value conversations, thus enhancing their revenue streams [13][14] Future Outlook - The shift from pageview-driven models to relationship-driven value is seen as a significant opportunity for both Google and publishers [16] - Trust and expertise will be crucial for publishers to thrive in the evolving landscape, as users will continue to seek informed and trustworthy content before making decisions [14][15]

RAG技术提升 - DeepMind 开发了一种简单的 RAG 技术，将幻觉减少 40% [1] - 该技术将答案相关性提高了 50% [1] RAG系统应用 - 行业正在探索如何在 RAG 系统中使用该技术（附带代码）[1]

That's a wrap!If you found it insightful, reshare it with your network.Find me → @_avichawlaEvery day, I share tutorials and insights on DS, ML, LLMs, and RAGs.Avi Chawla (@_avichawla):Model Context Protocol (MCP), clearly explained (with visuals): ...

Summary of Yelp (YELP) Conference Call - August 12, 2025 Company Overview - **Company**: Yelp (YELP) - **Industry**: Online local business directory and review service Key Points 1. Q2 Results and Outlook - Yelp experienced a lack of seasonal ramp in advertising budgets due to policy uncertainty, affecting both restaurant retail and services sectors [4][5] - Small businesses are facing rising input costs and consumer uncertainty, impacting Yelp's performance [4][5] 2. Strategic Priorities - **Leading in Services**: Yelp aims to deliver value to advertisers by ensuring high-quality leads through tools like "Request a Quote" and "Yelp Assistant" [6][9] - **Delivering Advertiser Value**: The focus is on matching consumers with service providers effectively, enhancing the overall workflow [10][12] - **Yelp Assistant**: This chatbot has shown a 400% year-on-year increase in generated projects, indicating its effectiveness in consumer interaction [15] 3. Monetization Opportunities - The "Request a Quote" feature generates four times the monetization compared to a single search click, enhancing advertiser value without increasing perceived ad load [17][18] - Yelp is exploring monetization outside its platform, with a tenfold increase in API calls for AI search providers and an annual recurring revenue (ARR) run rate exceeding $10 million [46][47] 4. Acquisition Strategy - The acquisition of RepairPal aims to strengthen Yelp's position in the auto services category, aligning with its goal to lead in various service sectors [31][33] - The integration of RepairPal is progressing well, enhancing Yelp's capabilities in matching consumers with qualified local businesses [32][34] 5. Consumer Experience Transformation - Yelp has modernized its home feed to be more visual and engaging, aiming to provide relevant content to users [35][36] - The company is leveraging AI and chatbots to enhance user engagement and streamline the consumer experience [44] 6. Challenges in Restaurant and Retail Segment - The restaurant sector is under pressure from rising costs and changing consumer behavior, but Yelp remains confident due to its authoritative content and brand recognition [43][44] - The company is modernizing its experience and utilizing chatbots to improve engagement in this segment [44] 7. Internal Efficiency and AI Utilization - Yelp is developing AI voice products for service businesses and restaurants, which will enhance customer interaction and internal processes [49][51] - The company has reduced the time to market for new features by 60% through improved processes and the use of AI [54] 8. Financial Discipline - Yelp is committed to maintaining flat headcount and has a $250 million share repurchase run rate, emphasizing financial discipline in its growth strategy [61][62] 9. Future Outlook - The integration of AI across various business functions is expected to drive significant improvements in efficiency and consumer engagement [60][62] - Yelp is focused on leveraging emergent technologies while ensuring financial success and relevance in the market [62] Additional Insights - The conversation highlighted the importance of human-generated content and its role in Yelp's strategy to maintain authority and relevance in the local business directory space [41][42] - The company is exploring the potential of large language models (LLMs) to enhance internal processes and improve developer productivity [53][54]