Group 1 - Zhipu released the open-source GLM-5 model with a parameter scale expanded to 744 billion (activated 40 billion), ranking fourth globally in the Artificial Analysis leaderboard and first in open-source, with coding and agent capabilities approaching Claude Opus 4.5 [1] - The model achieved scores of 77.8 and 56.2 in SWE-bench-Verified and Terminal Bench 2.0, respectively, setting new open-source SOTA records, excelling in complex systems engineering and long-range agent tasks [1] - GLM-5 has been adapted to domestic chips such as Huawei Ascend, Cambricon, and Kunlun, and introduced Z Code full-process programming tools and AutoGLM universal agent assistant [1] Group 2 - MiniMax launched the M2.5 model with only 10 billion activated parameters, achieving flagship-level reasoning speed three times faster than Opus [2] - The model completed a full-stack learning website in 9 minutes and can independently perform physical simulations and enterprise-level CMS system setups, supporting cross-platform development for PC/App/React Native [2] - It utilizes a native agent RL training framework and CISPO algorithm, achieving approximately 40 times training acceleration and is compatible with mainstream development tools like Claude Code and OpenClaw [2] Group 3 - Xiaohongshu's foundational model team released the open-source FireRed-Image-Edit, achieving SOTA in multiple authoritative rankings such as ImgEdit and GEdit, with code and technical reports now available [3] - The model employs a three-stage training process to enhance capabilities and innovatively introduces Layout-Aware OCR-based Reward, significantly improving text editing accuracy and style retention [3] - It supports various complex editing scenarios, including instruction-following consistency, text editing, style transfer, multi-image fusion, and old photo restoration, with model weights set to be open-sourced [3] Group 4 - Xiaomi released the open-source VLA model Xiaomi-Robotics-0 with 4.7 billion parameters, excelling in visual language understanding and real-time execution capabilities, achieving optimal results in comparisons across 30 models including LIBERO, CALVIN, and SimplerEnv [4] - The model uses a Mixture-of-Transformers architecture, where the VLM brain understands instructions and the Diffusion Transformer generates high-frequency smooth actions [4] - It addresses action discontinuity issues through asynchronous reasoning and Λ-shape attention masks, enabling real-time inference on consumer-grade graphics cards, and has been open-sourced on GitHub and HuggingFace [4] Group 5 - Gaode launched the ABot series of embodied base models, with ABot-M0 responsible for operations and ABot-N0 for navigation, achieving comprehensive SOTA across 10 global authoritative evaluations [5][6] - ABot-M0 integrates 6 million cross-platform trajectory data through action language and proposes an action manifold learning algorithm, achieving an 80.5% success rate on Libero-Plus, surpassing pi0 by nearly 30% [6] - ABot-N0 unifies five core navigation tasks within a single VLA architecture, constructing 8,000 high-fidelity 3D scenes and 17 million expert examples, with a 40.5% improvement in SocNav success rate [6] Group 6 - Rokid Glasses launched the "customizable agent" feature on the Lingzhu platform, allowing integration with OpenClaw or privately deployed models like DeepSeek R1 and Qwen3 through a standard SSE interface [7] - Users can achieve local closed-loop processing of private data and switch model bases with one click, leveraging the ClawHub skill ecosystem to execute capabilities like file systems, browsers, and IM messaging [7] - The platform empowers users by allowing them to summon private agents via voice commands or shortcuts, creating a 24/7 intelligent assistant [7] Group 7 - Google DeepMind released the AI mathematician Aletheia based on Gemini Deep Think, achieving a score of 91.9% on IMO-ProofBench, setting a new SOTA and capable of independently writing and publishing academic papers [8] - Aletheia systematically evaluated 700 open problems in the Erdős conjecture database and autonomously solved 4 unsolved mysteries, demonstrating self-correction and acknowledgment of limitations [8] - Gemini Deep Think collaborated with experts to tackle 18 long-stagnant research challenges, resolving a decade-long submodel optimization conjecture, with one paper accepted by ICLR 2026 [8] Group 8 - HyperWrite's CEO published an article that garnered 70 million views, stating that the release of GPT-5.3-Codex and Claude Opus 4.6 marks a qualitative change in AI [9] - AI can now independently complete the workload of human experts in 5 hours, with this capability doubling every 4-7 months, and GPT-5.3 plays a crucial role in its self-training process, initiating a recursive self-improvement cycle [9] - Almost all cognitive work performed in front of screens will be affected, and it is advised to spend one hour daily experimenting with AI, as the current cognitive window period will not last long [9] Group 9 - Anthropic released a 53-page report warning that the risks associated with Claude Opus 4.6 are approaching ASL-4 levels, outlining 8 potential risk pathways that could lead to catastrophic harm, including autonomous escape and autonomous operation [10][11] - The report concludes that current models do not exhibit "sustained consistent malicious intent," and the risk of catastrophic damage is "very low but not zero," entering a "gray area" of capability assessment [10] - The head of Anthropic's safety research team resigned, stating that "the world is in crisis," and xAI co-founder predicts that recursive self-improvement cycles may be launched within 12 months [11]

Market Overview - The U.S. stock market opened higher but then retreated, with the Nasdaq down 0.71%, the Dow Jones up 0.13%, and the S&P 500 also turning negative, with over 3,200 stocks declining [1] - Last week, initial jobless claims in the U.S. were reported at 227,000, higher than the forecast of 224,000 and the previous value of 231,000 [3] Technology Sector Performance - The performance of the "Magnificent Seven" tech stocks was mixed, with Nvidia and Google slightly up by 0.1%, while Tesla, Microsoft, Meta, Amazon, and Apple saw declines, with Apple nearing a 2% drop and its market cap falling below $4 trillion [3] - Semiconductor stocks experienced volatility, with SanDisk rising over 5% and Micron Technology up over 2% [3] Chinese Stocks - Chinese stocks listed in the U.S. faced widespread declines, with the Nasdaq Golden Dragon China Index dropping nearly 2%. Notable declines included Huya down over 7%, Tencent Music down over 6%, and Beike down over 4% [5] Trading Volume and Market Dynamics - The average daily trading volume in the U.S. stock market reached a record $1.03 trillion in January, a 50% increase compared to the same period in 2025, with over 19 billion shares traded daily, marking the second-highest in history [8] - The rise in trading volume is attributed to increased retail participation, the popularity of "zero-day-to-expiration" options, and a significant shift in investor focus from tech giants to underperforming sectors like energy and industrials [8] Hedge Fund Activity - Hedge funds have significantly increased their short positions in U.S. stocks, with the nominal short selling of individual stocks reaching the highest level since 2016. Short positions are now double the long positions [9] - Concerns over the disruptive impact of artificial intelligence on business models have led to a tumultuous week on Wall Street, with a total market value loss of $611 billion across 164 stocks in software, financial services, and asset management [9] Sector Rotation - The semiconductor and IT services sectors were among the few to see net buying last week, with semiconductor stocks rising, highlighting a divergence between chip stocks and software stocks [10] - Hedge funds are rotating into defensive sectors, with healthcare becoming the most favored sector for fund inflows, surpassing industrials [10]

A Waymo autonomous vehicle outside the Google headquarters in Mountain View, California, US, on Tuesday, Feb. 3, 2026.Waymo on Thursday said it has begun using its sixth-generation driverless system to provide robotaxi rides to employees on Ojai vehicles, which use a base model made by Chinese automaker Geely.By upgrading their driverless tech, and adding more vehicles to its fleet, Waymo aims to extend its U.S. lead and lock in loyal riders. The Alphabet-owned company said its sixth-generation Waymo Driver ...

Core Insights - Alphabet's traditional search engine is experiencing a sustained decline in usage as users increasingly turn to AI chatbots and other AI solutions for their needs [1] Group 1: Company Performance - The decline in search engine usage is a significant concern for Alphabet, indicating a shift in consumer behavior towards AI technologies [1] Group 2: Market Trends - Observing megatrends can provide insights into societal advancements and potential investment opportunities, highlighting the importance of understanding evolving technologies [1] - The focus on macrotrends and emerging technologies is crucial for identifying which companies can capitalize on new opportunities [1] Group 3: Investment Strategy - Emphasis on fundamentals, quality of leadership, and product pipeline is essential for uncovering investment opportunities, particularly in medium-sized companies and startups [1]

Core Insights - Google's capital expenditure is expected to reach between $175 billion and $185 billion in 2026, primarily focused on investing in AI computing capabilities to meet strong cloud customer demand and other strategic projects [1] Company Project Progress - Google is actively promoting the external sales of its self-developed TPU and is in negotiations with Meta for a multi-billion dollar TPU supply, with Meta planning to integrate Google's TPU into its data centers starting in 2027 [2] - The seventh-generation TPU "Ironwood" was released in early November 2025 and is expected to be available in the coming weeks [2] Business Development - The Gemini3 model, released in November 2025, has received positive market feedback, with monthly active users exceeding 750 million by the fourth quarter of 2025 [3] - Google plans to further integrate Gemini into core products such as search and Android, and collaborate with Apple to enhance device penetration, which may drive long-term growth [3] Industry Position - Google Cloud's revenue grew by 48% year-over-year in the fourth quarter of 2025, with a backlog of unfulfilled orders amounting to $240 billion [4] - With the mass production of the TPU v7p chip and collaborations with companies like Anthropic, the cloud business is expected to maintain high growth and become a core engine for the company [4] Institutional Perspectives - Several institutions, including Citigroup and JPMorgan, have identified Google as a key player in the AI sector for 2026, focusing on its capital expenditure efficiency and AI monetization progress [5] - The market is likely to continue monitoring the growth rate and profit performance of the cloud business in quarterly earnings reports [5]

Core Viewpoint - Big Tech's data center expansion is encountering increasing legislative resistance aimed at mitigating the impact of their power consumption on consumer electric bills [1][2]. Group 1: Legislative Actions - Bipartisan legislation has been introduced by Senators Josh Hawley and Richard Blumenthal to prevent data center power usage from affecting consumers' electric bills [1]. - New York has proposed a bill to pause data center construction, potentially excluding the state from future data center developments [2]. - Lawmakers across the country are attempting to regulate an industry that has rapidly expanded and is straining the power grid [2]. Group 2: Industry Impact and Demand - The four major tech companies—Microsoft, Alphabet, Amazon, and Meta—are projected to invest over $650 billion in artificial intelligence this year, significantly increasing data center construction and power demand [4]. - Power demand from U.S. data centers is estimated to have doubled from 2018 to 2024 and could triple by 2028 [5]. - Capacity prices for electricity in the PJM Interconnection region have surged from $28.92 per megawatt-day for the 2024-2025 period to $329.17 for the 2026-2027 period [5]. Group 3: Environmental Concerns - Major data centers consume large amounts of water for cooling, with forecasts indicating they will use over 150 billion gallons between 2025 and 2023, equivalent to the annual water usage of 4.6 million U.S. households [6]. - AI developers have committed to reducing the environmental impact on local communities [6]. Group 4: Corporate Responses - Microsoft has pledged to cover its data center energy costs fully and to replenish more water than its U.S. data centers consume [7]. - Amazon reported a 40% reduction in water use per unit of computing since 2021 and claims that its infrastructure will not increase electricity rates [7].

Group 1 - The core idea of the articles highlights the contrasting approaches to AI shopping between Google and Alibaba, with Google embedding AI shopping features into its search engine while Alibaba focuses on direct purchasing through its AI platform [1][2] - Google leverages its vast search engine capabilities to integrate transaction processes within user queries, following a model of "AI + advertising" for monetization [2] - Alibaba's approach is more pragmatic, allowing users to directly place orders through AI, exemplified by the success of its Qianwen app during the Spring Festival, where users made over 1.2 billion orders [1][2] Group 2 - The success of Alibaba's Qianwen app is attributed to its comprehensive AI technology and a robust consumption ecosystem, integrating various services from its platforms like Taobao and Tmall [2][3] - The differences in AI shopping strategies stem from Google's lack of checkout capabilities and delivery networks, while Alibaba has transformed its extensive logistics and e-commerce infrastructure into a foundation for AI-driven consumption [3] - The initial surge in user engagement during the Spring Festival is seen as just the beginning, with ongoing efforts to retain users and expand the range of products available through AI [4]

Core Viewpoint - Quantum computing stocks experienced a significant decline after peaking in 2025, with investors losing interest in speculative, pre-revenue companies. Rigetti Computing saw a drop of over 70% from its highs, but B. Riley upgraded it to a Buy with a target price of $35, indicating potential for recovery [1]. Group 1: Market Trends - The quantum computing market is projected to reach $4 billion by 2030, suggesting a growing interest and potential for investment in this sector [2]. - Despite the downturn in quantum stocks, the technology continues to advance, with Alphabet making strides in its quantum roadmap, particularly focusing on long-lived logical qubits [1]. Group 2: Company Analysis - Rigetti Computing has been highlighted as a speculative play, currently trading around $16, with analysts suggesting it could more than double to $35 [1]. - Alphabet is positioned as a strong player in both AI and quantum computing, leveraging its resources to advance its quantum research and development efforts [1]. Group 3: Investment Sentiment - The recent sell-off in quantum stocks is attributed more to a shift in investor sentiment rather than the actual performance of quantum technology [1]. - Investors are currently favoring AI investments over quantum stocks, viewing AI as a safer option for earnings growth [1].

Alongside this, Broadcom has built a serious infrastructure software arm, anchored in long-term, mission-critical relationships. That combination of high-margin chips plus sticky enterprise software gives it a deep competitive moat in networking, wireless, and custom silicon.Founded in 1961, Palo Alto-based Broadcom has grown into one of the most dominant forces in global technology. With a market capitalization of over $1.6 trillion, the company now sits firmly among the world’s elite. Its semiconductors a ...

Now you can get access to the latest and highest-quality analysis of recent Wall Street buying and selling ideas with just one subscription to Beyond the Wall Investing ! There is a free trial and a special discount of 10% for you. Join us today!The last time I updated my coverage on Alphabet Inc. ( GOOG ), the stock was trading at ~$335/share. Since then, the firm has reported its fiscal Q4 2025 results, guiding for a massive pick-upDaniel Sereda is chief investment analyst at a family office whose investm ...