在中国投资界，但斌始终处于舆论的中心。他曾因重仓茅台成名，也因业绩波动和风格转换备受争议。从 业三十四载，从白酒赛道到精准捕捉全球AI科技浪潮，他的投资哲学在变与不变中不断进化。 近日，券商中国记者走进东方港湾，与但斌面对面交流，围绕AI时代的投资逻辑、全球资产配置以及A股的投 资机会展开深度对话。在全球地缘冲突频发、资本市场波动加剧的背景下，如何抓住真正决定未来十年的投资 主线？但斌给出了明确判断—人工智能是影响未来长期格局的"主因"，而战争与宏观波动可能带来短期扰动。 从昔日因重仓白酒成名，到近年大举转向AI科技赛道，但斌将这一转变称为一次"二次创业"。在他看来，中国 白酒行业正在从供不应求走向供需再平衡，而人工智能则可能开启长达二三十年的超级产业周期。 谈及个人认知进化，但斌坦诚复盘了对A股行情的判断，并分享了他对牛市的见解：真正健康的长牛，需要能 够不断突破前期高点，创出新高。他坚定看好AI产业链，认为当前的横盘震荡类似于互联网时代的1994年， 是为更大周期的爆发积蓄能量。 精彩观点： 人工智能是未来十年甚至更长周期的"主因"，地缘冲突只是历史中的小插曲。 白酒是"世界改变不了"，但需求总量见顶和老 ...

At present, Nvidia's graphics processing unit (GPU) is the primary bit of hardware used by the artificial intelligence (AI) industry. But there are signs that won't be the case for too much longer. Google's parent company, Alphabet, has introduced its own competitor to the GPU with its Tensor Processing Unit (TPU), which is better suited to Google Gemini, the company's premier AI program. Will AI create the world's first trillionaire? Our team just released a report on the one little-known company, calle ...

以下文章来源于槽值 ，作者槽值小妹 槽值 . 网易文创旗下新情感消费品牌，倡导更有情调、有质感的生活方式。 你的冲锋衣或许要跟着涨价了。 文 ｜ 槽值小妹 来源｜ 槽值（ID：caozhi163） 封面来源 ｜ IC photo 自中东地区 冲突爆发， 原油价格快速大幅攀升 后，油 价的上涨可谓有目共睹。 就在这几天， "黄金别再跌了，油价 别再涨了 ""排队加油" 又 成 为新的热门话题。 国际原油价格上涨直接抬升我国进口和用油成本。/ 图源 ：每日 经济新 闻 但千万别以为，"加油贵了"就是全部。 继"猪肉越便宜，羽绒服越贵"后，又一个让人困惑"啊？这也有关系？"的暴击来了—— 油价涨了以后， 你的冲锋衣，可能也会涨价。 图源：微博话题 油价涨了， 关我冲锋衣啥事啊？！ 不论是肉价影响羽绒服，还是油价影响冲锋衣， 说到底，都是原材料价格的事。 比如，猪肉价格下跌，鸭肉、鹅肉的需求就会减少，再叠加养殖行业产能调 整，羽绒产量就会减少。 羽绒产量越少，供不应求，价格也随之上涨，进一步推高羽绒服成本。 冲锋衣和油价的 关系，大 抵也类似。 一切还要从石油对纺织业的影响说起。 比如羊毛、蚕丝、棉、麻都是。 化学纤 ...

This year has been a pretty wild ride for the stock market so far. Both Nvidia (NVDA +1.95%) and Alphabet (GOOG +0.14%)(GOOGL +0.14%) are down this year.Alphabet has tumbled 6.6% this year while Nvidia is down 6.38%.You might think this looks like a good buying opportunity, and you'd be right. But which dip should you consider buying? Spelling it outAlphabet looks like the stronger of the two from where I'm standing. Financially, both companies are doing quite well, but Alphabet is in the stronger position ...

Core Insights - The dialogue between NVIDIA's Bill Dally and Google's Jeff Dean at GTC 2026 highlighted significant advancements in AI and machine learning, particularly in model capabilities and agent-based workflows [2][4][5]. Group 1: Model Advancements - The past year has seen rapid improvements in model capabilities, particularly in areas requiring verifiable rewards, such as mathematics and programming [7][8]. - Models like Gemini have achieved remarkable success in complex tasks, winning gold medals in competitions like IMO and ICPC, showcasing their enhanced abilities [8][9]. - There is a notable shift towards agent-based workflows that can autonomously handle longer tasks without constant human supervision, indicating a significant evolution in AI capabilities [9][11]. Group 2: Inference and Latency - A critical focus is on achieving ultra-low-latency inference to enhance the efficiency of autonomous systems, as inference latency directly impacts problem-solving efficiency [12][14]. - Dally emphasized the need to redesign architectures to minimize communication delays, which are a major source of latency in large language models (LLMs) [18][19]. - Innovations in on-chip communication and physical interfaces are being pursued to reduce latency from hundreds of nanoseconds to approximately 30 nanoseconds [20][21]. Group 3: Future of AI and Hardware - The discussion touched on the potential for AI to autonomously design future models, with Dean noting that while the complete closed-loop system is not yet realized, early forms are emerging [27][29]. - The hardware landscape is expected to evolve, with a clear distinction between training and inference hardware, as inference becomes increasingly critical in data centers [78][80]. - Dally highlighted the importance of future-proofing hardware to adapt to rapidly changing model requirements, emphasizing the need for efficient resource allocation [43][46]. Group 4: Data Utilization and Scaling - There is a belief that there is still a vast amount of untapped data available for training models, particularly in video and real-world scenarios [57][58]. - The conversation also explored the challenges of scaling models when data availability becomes constrained, with Dean suggesting that synthetic data generation could fill this gap [60][61]. - Techniques like data augmentation and regularization are seen as valuable methods to enhance model training without overfitting [67]. Group 5: AI in Chip Design - AI is increasingly being integrated into the chip design process, with systems like NVCell significantly reducing the time and effort required for tasks that previously took months [104][106]. - The use of AI in design verification and bug reporting is also improving productivity, allowing junior designers to access information without constantly consulting senior staff [112][116]. - The potential for AI to automate various stages of chip design is recognized, with aspirations for a future where design can be initiated with simple commands [122]. Group 6: Societal Impact of AI - The dialogue concluded with reflections on the positive societal impacts of AI, particularly in education and healthcare, where personalized learning and health coaching could revolutionize these fields [160][161]. - Both Dally and Dean expressed excitement about the potential for AI to provide personalized tutoring and health advice, enhancing individual learning and health outcomes [162][178].

Jensen Huang walked off the GTC stage on Monday having just projected at least $1 trillion in chip revenue through 2027. Wall Street analysts spent Tuesday calling it a floor, not a ceiling. And Nvidia (NVDA) stock sat there, barely moving, trading right where it was before the whole thing started. That disconnect tells you something important about where the Nvidia story stands right now. The bull case is not in dispute. What analysts are now zeroing in on is the next battle Nvidia has to win, one it ha ...

Market Overview - China has become the world's largest producer and consumer of polyurethane products, with a production volume of 16.5 million tons in 2023, accounting for nearly 50% of global output[2] - The polyurethane market in China is expected to reach approximately 165 billion yuan in 2024, representing a year-on-year growth of 10%[2] Price Trends - Major global isocyanate companies have frequently raised prices since December 2025, with Hunstman increasing MDI prices by $260/ton in the US and $350/ton in Europe, Africa, and the Middle East[2][7] - As of March 13, 2026, TPU film prices in Shandong rose to 16,000 yuan/ton, marking a 20% increase from 13,300 yuan/ton on November 12, 2025[22] Company Performance - The company Yinuowei is positioned to benefit from rising prices in the polyurethane industry, with projected revenues of 7.5 billion yuan in 2025, a year-on-year increase of 9.37%[32] - Yinuowei's net profit for 2025 is expected to reach 190 million yuan, reflecting a year-on-year growth of 7.75%[34] Market Dynamics - The median price-to-earnings (P/E) ratio for the North Exchange consumer service sector increased from 40.7X to 41.6X this week[39] - The total market capitalization of the North Exchange consumer service sector decreased from 111.24 billion yuan to 109.09 billion yuan[40] Risk Factors - Potential risks include changes in the macroeconomic environment, market competition, and statistical data inaccuracies[55]

Core Viewpoint - The latest research from TrendForce indicates that TSMC continues to benefit from advanced processes driven by demand for AI server GPUs, Google's TPUs, and ASICs, achieving a global market share of 70.1% in the foundry industry, solidifying its position as the leader in the sector [1] Group 1: Industry Overview - The total output value of the top ten foundry companies is projected to reach approximately $169.5 billion in 2025, representing a year-on-year increase of 26.3%, setting a new record [1] - Despite some pre-stockpiling of consumer products in the first half of 2026 stabilizing capacity utilization, there are concerns about order volumes and capacity utilization in the second half due to rising memory prices and shrinking demand [1] Group 2: Company Performance - TSMC's wafer shipments are expected to slightly decrease in Q4 2025, but the launch of flagship products like the iPhone 17 will boost 3nm wafer shipments, leading to a 2% revenue growth to $33.7 billion, maintaining a market share of 70.4% [1] - Samsung Electronics, excluding System LSI performance, is projected to achieve a revenue increase of 6.7% in Q4 2025, reaching nearly $3.4 billion, turning from loss to profit, with a market share increase from 6.8% to 7.1% [2] - SMIC is expected to benefit from local market advantages, with a revenue increase of 4.5% in Q4 2025, reaching nearly $2.49 billion, driven by increased wafer shipments and a slight rise in ASP [2] - UMC's revenue in Q4 2025 is projected to grow by 0.9% to approximately $2 billion, maintaining its fourth position in market share [2] - GlobalFoundries is expected to see an 8.4% revenue increase in Q4 2025, reaching $1.8 billion, driven by demand for data center components [2] - Hua Hong Semiconductor Group's revenue is projected to increase by 3.9% in Q4 2025, reaching nearly $1.22 billion, supported by demand for MCUs and PMICs [3] - Tower's revenue is expected to grow by 11.1% in Q4 2025, reaching $440 million, moving up to seventh place in market share [3] - Vanguard's revenue is projected to decrease by 1.6% in Q4 2025 to $406 million due to reduced DDIC orders [3] - Nexchip's revenue is expected to decline by 5.3% in Q4 2025 to $388 million, as some products are postponed to Q1 2026 [3] - PSMC's revenue is projected to grow by 2% in Q4 2025 to approximately $37 million, ranking tenth [3]

LPU 会带来哪些增量？20260311 摘要 LPU 采用片内集成大量 SRAM 替代片外 HBM，通过近存计算与编译器 预调度消除延迟瓶颈，核心解决 AI 推理中 Decode 环节的内存密集型瓶 颈。 LPU vs GPU/TPU：LPU 追求极致确定性，更接近特定模型定制 ASIC；GPU 侧重通用性依赖 HBM；TPU 侧重矩阵乘法效率，LPU 在低 时延推理上具代差优势。 推理市场呈现"PD 分离"趋势：Prefill 环节为计算密集型，适用高算力 CPX；Decode 环节为内存密集型，LPU 的 SRAM 架构可显著降低 KVCache 读取时延。 NVIDIA 存储布局多元化：SRAM（收购 Groq/LPU）攻低延迟场景， HBM4 攻高性能训练，GDDR 攻高性价比计算，SSD 探索独立 KV 缓存 机柜。 Groq 产业化提速：2025 年三星代工订单预计从 0.9 万片增至 1.5 万片； 技术增量指向 SRAM 3D 堆叠、背部供电 PCB、高速 Switch 及液冷方 案。 LPU 局限性：SRAM 成本远高于 DRAM，大模型推理需多芯片堆叠推高 初始成本，且软件栈灵活性不足， ...

Investment Rating - The report does not explicitly provide an investment rating for the semiconductor industry Core Insights - The semiconductor industry is experiencing unprecedented opportunities and challenges due to rapid technological advancements and increasing ESG (Environmental, Social, Governance) concerns [15][41] - ESG has become a critical standard for evaluating and managing sustainable development capabilities in the semiconductor sector, influencing operational and strategic decisions [15][41] - The global semiconductor market size has grown from $139 billion in 2001 to $526.9 billion in 2023, with a compound annual growth rate (CAGR) of 6.0% [23] - Despite a decline of 8.2% in sales from 2022 to 2023, a strong rebound is expected in the second half of 2023, with predictions of double-digit growth in 2024 [23] - Key drivers of market growth include smartphones, cloud computing, IoT, AI, and automotive electronics, with 5G technology further propelling expansion [23] Summary by Sections 1. Global Development Overview - Semiconductor technology is foundational to modern electronics, impacting various sectors from smartphones to aerospace [22] - The industry has a strategic and innovative role in global economic growth, with the U.S. holding a 50.2% market share in 2023 [24] 2. ESG Development Trends - The semiconductor industry faces significant ESG pressures due to its resource-intensive nature, requiring substantial water, electricity, and chemicals [41] - Companies are increasingly recognizing the benefits of sustainable practices, which can enhance brand reputation and operational efficiency [41][44] 3. Climate Change and Energy Consumption - Climate change is a primary concern, with semiconductor manufacturing contributing significantly to greenhouse gas emissions [48] - The industry is under pressure to reduce emissions while also facing opportunities through energy management innovations and the development of high-performance computing chips [49][51] 4. Pollution Prevention - Semiconductor manufacturing generates substantial waste and emissions, necessitating investment in green technologies to mitigate environmental impact [62] - Companies like TSMC are implementing advanced pollution control technologies to enhance sustainability [66] 5. Water Resource Management - The semiconductor industry is highly water-intensive, with significant risks related to water scarcity and regulatory compliance [73] - Innovations in water recycling and management can provide competitive advantages and improve environmental performance [73] 6. Sustainable Supply Chain Management - The complexity of the semiconductor supply chain presents various ESG challenges, including environmental and social risks [81] - Effective supply chain management can enhance resilience and ensure compliance with environmental regulations [81] 7. Talent Attraction and Retention - The semiconductor industry faces challenges in attracting and retaining skilled talent due to high competition and job pressures [92] - Companies can enhance their appeal by offering attractive compensation, development opportunities, and fostering a positive workplace culture [92]