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DeepSeek 策略如何影响半导体链的全面分析

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发表于 2025-1-29 18:27:27 | 显示全部楼层 |阅读模式
My Full Breakdown of How DeepSeek’s Playbook Will Impact the Semiconductor Chain  
Safe from Disruption
• $NVDA -- The adoption of CUDA in generative AI workloads outweighs any risk of commoditization in GPU hardware, as hyperscalers continue to rely on Nvidia’s integrated hardware & software ecosystem for both training & inference.

• $ASML -- The explosive need for advanced AI chips ensures strong demand for ASML’s EUV lithography tools, outweighing any potential decline in high-complexity chip production tied to open-source models.

• $TSM -- Growth in custom AI chip production for inference & proprietary solutions outweighs risks tied to a potential slowdown in advanced GPU demand, reinforcing TSM’s critical role in hyperscaler supply chains.

• $AVGO -- Growth in hyperscaler AI deployments & demand for custom ASICs outweighs any risk from shifts to simpler AI architectures, ensuring Broadcom’s solutions remain foundational to AI ecosystems.

• $ALAB -- The surging demand for real-time AI inference workloads offsets any decline in AI training demand, with Astera Labs’ connectivity solutions bridging critical components like GPUs, CPUs, and memory in hyperscaler data centers.

• $AMD -- The cost-effective MI300X GPUs provide a compelling alternative to Nvidia’s dominance in AI training, allowing AMD to capitalize on hyperscaler demand for scalable, budget-friendly infrastructure tailored to meet the shifting focus toward resource-efficient AI deployments.

• $MRVL -- The rise in AI-driven inference & cloud networking needs outweighs any slowdown in training-related data center upgrades, ensuring continued demand for Marvell’s custom silicon solutions.

• $SNPS -- The need for advanced chip design tailored for resource-efficient AI applications outweighs any shift to simpler architectures, ensuring continued reliance on Synopsys’ AI-enhanced EDA tools.

• $CDNS -- Increased demand for simulation tools in cost-optimized AI chip design outweighs headwinds from open-source architectures, solidifying Cadence’s role in enabling next-gen AI hardware.

• $KLAC -- Demand for precision tools in semiconductor manufacturing, especially for inference-optimized chips, outweighs any potential slowdown in high-complexity chip production for training.Facing Headwinds• $INTC -- Lags behind Nvidia and AMD as hyperscalers shift to proprietary and custom AI hardware solutions.

• $MU -- Memory pricing pressure intensifies as hyperscalers adopt proprietary DRAM and NAND solutions for optimized AI workloads.

• $AMAT -- Declining demand for costly equipment as hyperscalers move toward simpler, proprietary chip designs challenges growth.

• $LRCX -- Deposition and etching tools face headwinds as cost-efficient modular AI hardware reduces demand for adva
nced node production.

• $TXN -- Analog focus limits exposure to the booming digital AI market, sidelining Texas Instruments in hyperscaler-driven growth.

• $SWKS -- RF components fail to capture AI-driven infrastructure growth, leaving Skyworks out of the hyperscaler AI revolution.

• $ADI -- Analog components miss out on high-demand AI connectivity markets, limiting Analog Devices’ growth potential.

• $KLAC -- Reduced complexity in AI chip designs may lower demand for advanced process control tools, despite its essential role in precision manufacturing.

• $AMAT -- Dual pressures from hyperscaler-driven proprietary solutions and reduced reliance on high-complexity equipment weigh on future growth.

我对 DeepSeek 策略如何影响半导体链的全面分析
避免中断
• [url=https://x.com/search?q=%24NVDA&src=cashtag_click]$NVDA
--在生成性 AI 工作负载中采用 CUDA 的价值超过了 GPU 硬件商品化的风险,因为超大规模企业继续依赖 Nvidia 的集成硬件和软件生态系统进行训练和推理。
• $ASML --对先进 AI 芯片的爆炸式需求确保了对 ASML 的 EUV 光刻工具的强劲需求,超过了与开源模型相关的高复杂性芯片生产的潜在下降。
• $TSM --用于推理和专有解决方案的定制 AI 芯片生产的增长超过了与高级 GPU 需求潜在放缓相关的风险,从而增强了 TSM 在超大规模供应链中的关键作用。
• $AVGO --超大规模 AI 部署的增长和对定制 ASIC 的需求超过了转向更简单的 AI 架构所带来的任何风险,确保了 Broadcom 的解决方案仍然是 AI 生态系统的基础。

• $ALAB --对实时 AI 推理工作负载的激增需求抵消了 AI 训练需求的下降,Astera Labs 的连接解决方​​案连接了超大规模数据中心中的 GPU、CPU 和内存等关键组件。

• $AMD --经济高效的 MI300X GPU 为 Nvidia 在 AI 训练领域的主导地位提供了引人注目的替代方案,使 AMD 能够利用超大规模对可扩展、经济实惠的基础设施的需求,这些基础设施旨在满足向资源高效的 AI 部署转变的重点。

• $MRVL --人工智能驱动的推理和云网络需求的增长超过了与训练相关的数据中心升级的任何放缓,从而确保了对 Marvell 定制硅片解决方案的持续需求。

• $SNPS --针对资源高效的 AI 应用量身定制的先进芯片设计的需求,超过了向更简单架构的转变,确保继续依赖 Synopsys 的 AI 增强型 EDA 工具。

• $CDNS --成本优化的 AI 芯片设计中对模拟工具的需求增加超过了开源架构带来的阻力,巩固了 Cadence 在支持下一代 AI 硬件方面的作用。

• $KLAC --半导体制造中对精密工具的需求,尤其是对推理优化芯片的需求,超过了用于训练的高复杂性芯片生产的任何潜在放缓。面临逆风
• $INTC --随着超大规模企业转向专有和定制的 AI 硬件解决方案,落后于 Nvidia 和 AMD。
• $MU --随着超大规模企业采用专有 DRAM 和 NAND 解决方案来优化 AI 工作负载,内存定价压力进一步加剧。
• $AMAT --随着超大规模企业转向更简单、专有的芯片设计,对昂贵设备的需求下降对增长构成了挑战。
• $LRCX --由于成本效益高的模块化 AI 硬件减少了对先进节点生产的需求,沉积和蚀刻工具面临阻力。
• $TXN --对模拟的关注限制了对蓬勃发展的数字 AI 市场的接触,使得德州仪器在超大规模驱动的增长中处于边缘地位。
• $SWKS -- RF 组件未能捕捉 AI 驱动的基础设施增长,导致 Skyworks 无法参与超大规模 AI 革命。
• $ADI --模拟元件错过了高需求的 AI 连接市场,限制了 ADI 公司的增长潜力。
• $KLAC --尽管先进过程控制工具在精密制造中发挥着至关重要的作用,但人工智能芯片设计复杂性的降低可能会降低对先进过程控制工具的需求。
• $AMAT --超大规模驱动的专有解决方案和减少对高复杂性设备的依赖的双重压力影响着未来的增长。



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IvanaSPEAR






下午9:07 · 2025年1月28日
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 楼主| 发表于 2025-1-29 18:33:17 | 显示全部楼层
Why $ALAB Is the Stock I Couldn’t Ignore After Yesterday’s Overreaction  

The meteoric ascent of AI is fueling an unrelenting demand for data processing that is not only faster but also far more efficient. Astera Labs, strategically positioned at the nexus of this seismic shift, is uniquely poised to address the multifaceted complexities that define this evolving ecosystem. Hyperscalers -- colossal architects of cloud infrastructure -- are funneling billions into AI chip development to power generative AI, scientific computations, and intricate data analytics. This unprecedented investment has created an urgent need for advanced connectivity solutions capable of seamlessly bridging CPUs, GPUs, memory, and storage -- eliminating the persistent bottlenecks that plague conventional data centers.

Existing connectivity architectures falter under the massive scale of AI infrastructure, exposing critical vulnerabilities. Astera Labs rises to meet these challenges head-on, pushing the boundaries of what is possible in cloud-scale computing. Their latest breakthrough, the Scorpio Smart Fabric Switches, exemplifies this commitment to innovation. Among these is the industry-first PCIe Gen 6 switch, a technological leap that doubles bandwidth while significantly enhancing power efficiency.

The company’s strategic alliances with giants like $NVDA, $AMD, $INTC & $MU underscore its pivotal role in the AI ecosystem. Already integral to NVIDIA’s GB200 GPUs, Astera Labs’ solutions are expected to power the forthcoming Blackwell GPUs, further entrenching its indispensability. As hyperscalers pivot towards proprietary ASIC programs to reduce reliance on third-party GPUs, Astera Labs is perfectly aligned with this strategic trajectory, cementing its place as a cornerstone of next-generation AI hardware.

Astera Labs operates within a market characterized by explosive growth. Projections indicate that its TAM will expand from $17B in 2023 to $27B by 2027, driven by escalating demand for wired connectivity and CXL memory controllers. Despite its relatively modest revenue, Astera Labs is growing at a rate that dwarfs industry norms. With a 45% CAGR the next four years, the company’s trajectory speaks to its ability to deliver on the exacting demands of hyperscalers and data-intensive applications alike.

Astera Labs’ solutions are meticulously designed to tackle these challenges. The Leo Memory Connectivity Platform optimizes memory pooling and scalability, while Aries Retimers address critical signal integrity issues that are otherwise insurmountable in modern data centers. As generative AI and cloud adoption accelerate, these technologies are indispensable for managing the soaring complexity and speed demands of today’s data infrastructure. Astera Labs delivers with surgical precision, meeting these needs while anticipating the next wave of innovation.

Collaboration is woven into the fabric of Astera Labs’ operational ethos. The company’s deep partnerships with hyperscalers like $AMZN AWS highlight its role as a trusted partner in crafting bespoke solutions. These relationships not only drive adoption but also empower Astera Labs to influence and shape emerging standards in data center connectivity --  ensuring its technologies remain integral to the future of the field.

As AI transforms industries on a global scale, Astera Labs stands resolutely at the forefront. Its ability to address the most pressing challenges in data movement and connectivity gives it a competitive advantage that is both rare and formidable. With hyperscalers embarking on multi-year investment cycles to build next-generation AI infrastructure -- Astera Labs is well-positioned to capture an ever-expanding share of this transformative market.

The magnitude of opportunity facing Astera Labs is staggering. Its advanced connectivity solutions transcend mere support for the AI boom -- they are actively shaping its architecture. By solving fundamental challenges in data center design, Astera Labs is not just a participant in the AI revolution -- it is a defining force, rewriting the narrative of what’s possible in the era of intelligent computing.

翻译自 英语
为什么$ALAB是昨日过度反应后我无法忽视的股票

人工智能的迅猛发展推动了对数据处理速度和效率的持续需求。Astera Labs 战略性地处于这一重大转变的中心,具有独特的优势,能够解决定义这一不断发展的生态系统的多方面复杂性。超大规模企业--云基础设施的庞大架构师--正在向人工智能芯片开发投入数十亿美元,以支持生成式人工智能、科学计算和复杂的数据分析。这项前所未有的投资迫切需要能够无缝连接 CPU、GPU、内存和存储--的高级连接解决方​​案,从而消除困扰传统数据中心的持续瓶颈。

现有的连接架构在大规模 AI 基础设施下不堪重负,暴露出严重的漏洞。Astera Labs 迎难而上,迎接这些挑战,不断突破云计算的极限。他们最新的突破——Scorpio Smart Fabric 交换机,体现了对创新的承诺。其中包括业界首款 PCIe Gen 6 交换机,这是一项技术飞跃,它使带宽翻倍,同时显著提高了能效。

该公司与$NVDA 、 $AMD 、 $INTC和$MU等巨头的战略联盟凸显了其在 AI 生态系统中的关键作用。Astera Labs 的解决方案已成为 NVIDIA GB200 GPU 不可或缺的一部分,预计将为即将推出的 Blackwell GPU 提供支持,进一步巩固其不可或缺性。随着超大规模企业转向专有 ASIC 程序以减少对第三方 GPU 的依赖,Astera Labs 与这一战略轨迹完美契合,巩固了其作为下一代 AI 硬件基石的地位。

Astera Labs 所处的市场呈现爆炸式增长。预测显示,其 TAM 将从 2023 年的 170 亿美元扩大到 2027 年的 270 亿美元,这得益于对有线连接和 CXL 内存控制器不断增长的需求。尽管收入相对较低,但 Astera Labs 的增长速度却远超行业平均水平。未来四年,该公司的复合年增长率将达到 45%,其发展轨迹表明其有能力满足超大规模和数据密集型应用程序的严格要求。

Astera Labs 的解决方案经过精心设计,旨在应对这些挑战。Leo 内存连接平台优化了内存池和可扩展性,而 Aries 重定时器解决了现代数据中心无法克服的关键信号完整性问题。随着生成式人工智能和云采用的加速,这些技术对于管理当今数据基础设施不断飙升的复杂性和速度需求至关重要。Astera Labs 以精准的交付满足这些需求,同时预测下一波创新。

合作已融入 Astera Labs 的运营理念。该公司与 AWS 等$AMZN大规模提供商的深度合作凸显了其在制定定制解决方案方面作为值得信赖的合作伙伴的作用。这些关系不仅推动了采用,还使 Astera Labs 能够影响和塑造数据中心连接领域的新兴标准--确保其技术在该领域的未来中仍然不可或缺。

随着人工智能在全球范围内改变行业,Astera Labs 坚定地站在最前沿。它能够解决数据移动和连接方面最紧迫的挑战,这为其带来了罕见而强大的竞争优势。随着超大规模企业开始多年的投资周期来构建下一代人工智能基础设施-- Astera Labs 完全有能力在这个变革性市场中占据不断扩大的份额。

Astera Labs 面临的机遇之大令人震惊。其先进的连接解决方​​案不仅仅是支持 AI 热潮--它们还在积极塑造其架构。通过解决数据中心设计中的基本挑战,Astera Labs 不仅是 AI 革命的参与者--更是一股决定性的力量,改写了智能计算时代的可能性。
 楼主| 发表于 2025-1-29 18:38:32 | 显示全部楼层
Here's my 2025 outlook I sent to subscribers & it's playing out perfectly.

The first phase of AI in 2023 focused on infrastructure -- GPUs & hardware laying the groundwork.

2025 ushers in a software-driven phase, where AI meets permanence -- it will be the crown jewel of this era & the accelerator of the foundation GPUs & hardware built.

Stage 2 AI Winners: $PLTR, $TSLA, $SNOW, $CRWD, $MDB, $NET, $NOW, $DOCN, $TEM & $GTLB

翻译自 英语
这是我发送给订阅者的 2025 年展望,并且它正在完美地实现。

2023 年人工智能的第一阶段专注于基础设施-- GPU 和硬件奠定基础。

2025 年将迎来软件驱动阶段,人工智能与永久性--相遇,它将成为这个时代的皇冠上的明珠以及基础 GPU 和硬件构建的加速器。

第 2 阶段 AI 获胜者: $PLTR 、 $TSLA 、 $SNOW 、 $CRWD 、 $MDB 、 $NET 、 $NOW 、 $DOCN 、 $TEM和$GTLB
 楼主| 发表于 2025-1-29 18:42:44 | 显示全部楼层
美股周二反弹,投资者终于可以理性思考DeepSeek对AI行业的影响了。
正如昨天所说,模型效率突破导致训练和推理成本降低,对AI市场来说是一个长期利好,将增加需求和普及。
记住杰文斯悖论这个基本经济学原理。这发生在蒸汽机的煤炭使用上,发生在互联网上,现在又发生在AI上。
成本降低刺激了需求。AI的总支出应该会增加,而不是减少。DeepSeek的效率突破某种程度上使AI硬件商品化,使AI软件民主化。
通过部分商品化AI硬件,可能会导致一些高端AI硬件提供商如英伟达失去一些定价和利润能力,但需求仍将保持强劲,总体上不见得就是负分。
同时,通过民主化AI软件,会有更多的AI软件创建和部署,AI应用股表现应该非常强劲。可以参见我过去一年不断推荐的很多AI应用股。
AI建设股下跌20%到30%的完全属于超卖。大科技公司的良好收益、美联储可能的鸽派声明以及白宫对AI基础设施的更多乐观言论,将促使这些股票在未来几周强劲反弹。
 楼主| 发表于 2025-1-29 18:46:20 | 显示全部楼层
deepseek's r1 is an impressive model, particularly around what they're able to deliver for the price.

we will obviously deliver much better models and also it's legit invigorating to have a new competitor! we will pull up some releases.

翻译自 英语
deepseek 的 r1 是一款令人印象深刻的型号,尤其是考虑到它们能够以这个价格提供的功能。

我们当然会推出更好的模型,而且有新的竞争对手也确实令人振奋!我们会发布一些版本。
 楼主| 发表于 2025-1-29 18:50:53 | 显示全部楼层
Seems plausible to me.

"Bears missed the historical rally in tech stocks last 2 years and will miss the next 2 years constantly waiting for the black swan to end the AI Revolution trade. From Fed days, rumors of Nvidia Blackwell delays,Tokyo Black Monday...today no different with DeepSeek..buying opportunity."

@DivesTech

翻译自 英语
我觉得这似乎很有道理。

“空头错过了过去两年科技股的历史性反弹,也将错过未来两年不断等待黑天鹅结束人工智能革命交易的机会。从美联储会议纪要、Nvidia Blackwell 延期的传言到东京黑色星期一……今天的 DeepSeek 也不例外……买入机会。”
 楼主| 发表于 2025-1-29 18:59:14 | 显示全部楼层
DeepSeek is a massive tailwind for software companies -- here are 15 names to monitor  🧐

1. $NOW -- Powers digital transformation through automated enterprise workflows, leading the IT management space.

2. $PLTR -- Transforms massive datasets into actionable insights, driving operational efficiency for enterprises.

3. $ORCL -- Combines AI-driven insights with enterprise resource planning in a unified cloud platform for streamlined decision-making.

4. $SNOW – Redefines data management with a collaborative cloud platform designed to unlock enterprise AI opportunities.

5. $NET -- Handles over 20% of global internet traffic while excelling in web security, content delivery, and edge AI solutions.

6. $MDB -- Enables developers to scale modern applications with a flexible NoSQL database designed for cloud-native architectures.

7. $CRM -- Dominates the CRM market with an AI-powered platform integrating sales, service, marketing, and commerce.

8. $HUBS -- Offers an intuitive CRM that integrates marketing, sales, and service tools for SMB growth.

9. $TEAM -- Dominates team productivity with widely used collaboration tools for software and project management.

10. $CRWD -- Sets the standard in endpoint security with an AI-powered platform delivering proactive threat protection.

11. $CFLT -- Revolutionizes real-time data streaming with an enterprise-grade platform powered by Apache Kafka.

12. $ESTC -- Delivers search-powered solutions for enterprise observability, security, and operational insights.

13. $DDOG -- Provides end-to-end observability to ensure reliability and performance in complex cloud environments.

14. $DOCN -- A pure cloud computing play offering cost-effective solutions tailored for developers, small businesses, and startups.

15. $GTLB -- Automates DevSecOps with an all-in-one solution for the entire software development lifecycle.

翻译自 英语
DeepSeek 对软件公司来说是一个巨大的推动力--以下是 15 个值得关注的名字🧐

1. $NOW --通过自动化的企业工作流程推动数字化转型,引领 IT 管理领域。

2. $PLTR --将海量数据集转化为可操作的见解,提高企业运营效率。

3. $ORCL --在统一的云平台中将人工智能驱动的洞察力与企业资源规划相结合,以简化决策。

4. $SNOW – 通过旨在释放企业 AI 机遇的协作云平台重新定义数据管理。

5. $NET --处理超过20%的全球互联网流量,同时在网络安全、内容交付和边缘 AI 解决方案方面表现出色。

6. $MDB --使开发人员能够使用专为云原生架构设计的灵活 NoSQL 数据库来扩展现代应用程序。

7. $CRM --凭借集销售、服务、营销和商业于一体的人工智能平台占领 CRM 市场。

8. $HUBS --提供直观的 C​​RM,将营销、销售和服务工具集成在一起,促进中小企业发展。

9. $TEAM --通过广泛使用的软件和项目管理协作工具来提高团队生产力。

10. $CRWD --通过提供主动威胁防护的人工智能平台设定端点安全标准。

11. $CFLT --通过由 Apache Kafka 提供支持的企业级平台彻底改变实时数据流。

12. $ESTC --为企业可观察性、安全性和运营洞察提供由搜索提供支持的解决方案。

13. $DDOG --提供端到端可观察性,以确保复杂云环境中的可靠性和性能。

14. $DOCN --纯粹的云计算公司,为开发人员、小型企业和初创企业提供量身定制的经济高效的解决方案。

15. $GTLB --通过适用于整个软件开发生命周期的一体化解决方案实现 DevSecOps 自动化。
 楼主| 发表于 2025-1-29 19:00:18 | 显示全部楼层
network 发表于 2025-1-29 18:59
DeepSeek is a massive tailwind for software companies -- here are 15 names to monitor  🧐

...

Nvidia GPUs aren't just for AI. Repeat after me: accelerated computing is a huge superset of AI.One example of why GPUs are replacing CPUs in data centers:Grace Blackwell outperforms CPUs, specifically Sapphire Rapids, by 18 times and NVIDIA H100 Tensor Core GPUs by 6 times in query benchmarks.
翻译自 英语

Nvidia GPU 不仅仅适用于 AI。跟我重复一遍:加速计算是 AI 的一个巨大超集。GPU 在数据中心取代 CPU 的一个例子是:在查询基准测试中,Grace Blackwell 的性能比 CPU(特别是 Sapphire Rapids)高出 18 倍,比 NVIDIA H100 Tensor Core GPU 高出 6 倍。

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上午4:52 · 2025年1月29日
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 楼主| 发表于 2025-1-29 19:01:00 | 显示全部楼层
Tigress Financial Partners has upgraded $NVDA to a “Strong Buy” from “Buy,” raising the price target to $220.

"We upgrade our investment rating from Buy to Strong Buy and increase our 12-month target price to $220 as NVDA continues to be a core holding in the powerful AI investing theme and the industry-leading beneficiary of the significant capital investment in AI development driving the ongoing acceleration of AI adoption across all industries and enterprises, which will continue to drive significant revenue and cash flow growth and greater shareholder value creation and view yesterday’s selloff as a major buying opportunity,"

翻译自 英语
Tigress Financial Partners 将$NVDA的评级从“买入”上调至“强力买入”,并将目标价上调至 220 美元。

“我们将投资评级从“买入”上调至“强力买入”,并将 12 个月目标价上调至 220 美元,因为 NVDA 继续成为强大 AI 投资主题的核心持股,并且是 AI 开发大量资本投资的行业领先受益者,推动了所有行业和企业不断加速采用 AI,这将继续推动收入和现金流的大幅增长以及更大的股东价值创造,并将昨日的抛售视为重大的买入机会,”
 楼主| 发表于 2025-1-29 19:02:09 | 显示全部楼层
Tonight is the night. Microsoft and Meta will present their earnings. Let's see and hear if they will scale back their Capex or stick to it. Below is an overview of the current estimated Capex of these 4 Big Tech players until 2026. $AMZN $MSFT $GOOGL $META
翻译自 英语

今晚就是关键时刻。微软和 Meta 将公布财报。让我们拭目以待,看看他们是否会缩减资本支出或坚持下去。以下是这四家科技巨头目前预计的 2026 年资本支出概览$AMZN $MSFT $GOOGL $META

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下午5:47 · 2025年1月29日
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