China's tech giants kicking off the Lunar New Year with a new wave of AI competition. Major AI model releases from both Alibaba and Bite Dance. Our DBosa has more in today's tech check.Hey D. >> Hey Carl. Good morning.So there's just been a blitz of AI announcements. Time to what is the biggest consumer window of the year. Together they reveal something the market may be underestimating.China isn't just competing on one slice of the AI race. It's building out the entire ecosystem. from frontier models to ho ...

Core Insights - China's rapid advancements in AI are challenging U.S. dominance, with analysts predicting a significant tech shock is underway [1][2] - The emergence of a "China tech sphere" could attract developing economies due to lower costs compared to U.S. and European alternatives [7][8] Industry Developments - China has launched a national AI fund worth 60.06 billion yuan ($8.69 billion) and an initiative called "AI+" to integrate AI across various sectors [4] - The country is leveraging its supply chain and low production costs to enhance its tech capabilities, particularly in AI and electric vehicles [3][6] Competitive Landscape - Huawei is narrowing the gap with U.S. chipmakers like Nvidia by utilizing homegrown chips and cheaper energy sources for AI model training [6] - U.S. hyperscalers, including Amazon and Microsoft, are projected to spend up to $700 billion on AI this year, raising concerns about the return on investment [10][12] Market Implications - The choice for developing economies may lean towards affordable Chinese technology, potentially leading to a global shift towards a Chinese tech ecosystem in the next 5 to 10 years [8][9] - There is growing nervousness regarding U.S. tech exceptionalism, especially following significant market cap losses in the U.S. software sector [11][12]

Core Insights - The report by Global Info Research focuses on the global NVMe-oF storage area network systems market, providing comprehensive analysis and insights into market size, key regions, major manufacturers, and industry trends [1][4] - The global NVMe-oF storage area network systems revenue is projected to reach approximately $9,775 million by 2025 and is expected to grow to $54,273 million by 2032, with a compound annual growth rate (CAGR) of 27.6% from 2026 to 2032 [1][3] Market Size and Growth Potential - The report aims to determine the total market size of NVMe-oF storage area network systems globally and in key countries/regions [3] - It assesses the growth potential of the NVMe-oF storage area network systems market and forecasts future growth for various products and end markets [3] Competitive Landscape - The report analyzes major participants in the NVMe-oF storage area network systems market based on parameters such as company profile, sales volume, revenue, pricing, gross margin, product portfolio, geographic distribution, and key developments [3] - Key companies covered in the report include Dell Technologies, Hewlett Packard Enterprise, Netapp, IBM, Huawei, Hitachi Vantara, Pure Storage, Inspur, Lenovo, Fujitsu, Oracle, Broadcom, Marvell, Micron Technology, Samsung Electronics, Western Digital, Kioxia, Vast Data, Weka, and Lightbits Labs [3][4] Market Drivers and Challenges - The report provides insights into the driving factors, constraints, opportunities, and key developments such as new product launches or approvals affecting the NVMe-oF storage area network systems market [4]

Open AAI is unveiling its first model to run entirely on chips from the startup Cerebras. It's a sign of companies diversifying beyond Nvidia's GPUs. Dear Jabosa has more in today's tech check.Very important story here. Deerra. Yeah.So, Kelly, this look, this is not OpenAI's flagship model. This is GPT 5.3% Codex Spark. It's a stripped down coding model built for speed.But an AI speed and cost that can beat raw power. And if the high volume everyday workloads, if they're moving off of Nvidia hardware, that ...

Core Insights - OpenAI is diversifying its chip usage by introducing a model that runs entirely on chips from the startup Cabus, moving away from sole reliance on Nvidia GPUs [1][4] - This trend is part of a broader industry shift where major AI companies like Google, Meta, and Microsoft are developing and utilizing their own AI chips, indicating a move towards self-sufficiency in AI infrastructure [2][6] - OpenAI's focus on inference, which incurs recurring costs as opposed to one-time training costs, highlights the financial implications of this shift, as inference is expected to consume the majority of compute resources as products scale [3][5] Company Strategies - OpenAI's new model, GBT 5.3% Codex Spark, is designed to be lighter and faster, catering to the revenue-generating segment of the market while still acknowledging Nvidia's foundational role [4][5] - There is reported dissatisfaction from OpenAI regarding some of Nvidia's latest chips for inference, reflecting a growing tension in the industry as companies seek to reduce dependency on a single supplier [5][6] - The competitive landscape is evolving, with companies like Cerebras, Broadcom, and AMD gaining traction in the inference market, which is perceived as less complex than training [9] Market Dynamics - Nvidia has historically held a near monopoly in the high-end GPU market, but as demand increases, companies are looking to diversify their chip suppliers to mitigate risks associated with pricing power and supply constraints [8][9] - The shift in infrastructure spending is expected to impact Nvidia significantly, as the company may lose ground in the volume game while still maintaining dominance in high-end offerings [7][8] - The memory chip market is also experiencing changes, with American companies showing interest in Chinese memory chips, indicating a broader trend of diversification and competition in the semiconductor space [10][11]

🚨JUST IN: PENTAGON BLACKLISTS ALIBABA AND MAJOR CHINESE COMPANIES SUPPORTING MILITARYThe U.S. Department of Defense has added six major Chinese companies, including tech and EV giants, to its military-linked blacklist.Designated firms face heightened scrutiny, U.S. investment restrictions, and potential federal contracting bans.The Chinese firms included are:Alibaba ( $BABA)BYD ( $BYDDY)Baidu ( $BIDU)COSCO (https://t.co/AZeXGlOBWu)Huawei (private)NIO Inc ( $NIO) ...

Market Overview - The active installed base of smartphones in India exceeds 740 million, representing more than half of the country's population of 1.45 billion [1] - India accounts for 14% of the global installed base of smartphones, while China leads with a 19% share, equating to approximately 1,005 million devices [2] Retention and Longevity - The average smartphone retention period in India is currently 42 months, which is slightly lower than the global average of 47 months [2][6] Brand Leadership - Xiaomi holds the largest active installed base in India, despite a decline in market share as it shifted focus from affordable devices to the premium segment [3] - Xiaomi's older Redmi and Note series continue to be widely used, indicating long shelf lives before users upgrade [3] - Globally, Xiaomi ranks third in terms of active installed base, with only Apple and Samsung surpassing the 1 billion mark [4] Competitive Landscape - Eight brands have active installed bases exceeding 200 million units globally, including Apple, Samsung, Xiaomi, Oppo, Vivo, Honor, Transsion, and Huawei, collectively controlling over 80% of the global smartphone installed base [5] - Motorola, Realme, and Google remain below the 200 million mark, with Motorola and Realme nearing that threshold [5]

Core Viewpoint - The global smartphone production is expected to decline by 10% in 2026 due to rising memory prices, potentially dropping to 1.135 billion units, with a pessimistic scenario predicting a decline of 15% or more [2][3]. Group 1: Market Impact - The significant increase in memory prices, with contract prices for 8GB+256GB models expected to rise nearly 200% in Q1 2026 compared to the same period in 2025, has led to the BOM cost share of memory in smartphones increasing from 10-15% to 30-40% [5]. - Brands are likely to raise terminal prices to maintain operations and may need to adjust product configurations to cope with the ongoing surge in memory prices [5]. Group 2: Brand Performance - Samsung, as the leading smartphone brand and a major player in the memory industry, is expected to see a decline in production, but the drop will be less severe due to its vertical integration advantages [5]. - Apple, with a higher proportion of high-end models, is better positioned to absorb rising memory costs and has a consumer base more accepting of price adjustments, providing some support for its production performance [5]. - Xiaomi and Transsion, which focus on lower-end models, are more sensitive to cost fluctuations and are expected to experience significant production cuts in 2026 due to the ongoing rise in memory prices [5]. Group 3: Competitive Landscape - Vivo, Oppo, Xiaomi, and Honor will face not only memory cost pressures but also strong competition from Huawei, which is expected to have the smallest production adjustment among brands and may even see growth due to its flexible pricing strategy [6]. - The current decline in terminal demand is attributed to rising memory prices, but the overall functionality of electronic devices has reached a level that satisfies most consumer needs, leading to longer replacement cycles and reduced upgrade momentum [6].

Core Viewpoint - The article discusses the competitive landscape of the AI industry, particularly focusing on the advancements in China and the potential implications for the US market, emphasizing that while US companies like Nvidia and OpenAI assert there is no AI bubble, the dynamics in China could challenge this perspective [2]. Group 1: AI Developments in China - China's AI industry is gearing up for significant developments, with reports of new models emerging that could rival US technologies, such as Alibaba's Qwen-3.5 and Zhipu's GLM-5 [4]. - DeepSeek's AI models were developed at a fraction of the cost compared to US leaders, indicating a potential competitive advantage for Chinese firms [3]. - The pace of AI model releases in China may accelerate, suggesting a shift in the competitive landscape [4]. Group 2: Chip Technology and Infrastructure - Nvidia's Blackwell chips are considered state-of-the-art, with rumors suggesting that some may have been made available to Chinese companies, potentially impacting the competitive balance [5]. - China may have access to Nvidia's H200 chip, but the future of this access is uncertain due to the ongoing US-China trade tensions [5]. - China's electricity capacity is double that of the US, which could provide a significant advantage for AI data centers, especially as energy infrastructure becomes a critical factor in AI development [6].

Core Viewpoint - DirectBooking Technology Co., Ltd. has signed a strategic cooperation framework agreement with DeepYou Digital Technology Co., Ltd. to establish a joint venture aimed at creating a next-generation AI-native intelligent hotel booking platform, reshaping the travel and hospitality ecosystem through technological innovation [1][4]. Company Overview - DirectBooking Technology focuses on hotel digital supply chains, direct-connect technologies, and private-domain operations, developing solutions for dynamic revenue management and channel optimization [3]. - DeepYou Digital Technology, founded by Mr. Li Daxue, specializes in industrial digitalization and AI innovation, having collaborated with nearly 1,000 scenic spots in China to create a smart cultural tourism service network [2]. Strategic Goals - The joint venture aims to leverage AI technologies for an enhanced lodging experience, featuring capabilities such as natural language interaction, intelligent recommendation, and end-to-end automated services [4]. - A three-year strategic goal has been set to cover 100,000 hotels with the AI hotel booking platform, promoting fair market competition and reshaping value distribution in the sector [4][5]. Value Proposition - For hotels, the platform will reduce customer acquisition and channel costs, increase direct sales, and enhance revenue and brand reputation through AI-enabled smart pricing and precision marketing [5]. - For users, the platform promises an efficient, convenient, and personalized booking experience, eliminating cumbersome price comparisons and providing intelligent matching [5]. Future Outlook - DirectBooking Technology and DeepYou plan to continue investing in technology R&D and market expansion, aiming to build a transparent, secure, and shared travel-and-hospitality ecosystem [6].