Group 1 - Apple Inc's iPhone sales in China topped the charts in May, indicating a rebound in growth in its key markets, China and the U.S. [1] - Global sales for Apple increased by 15% during April and May, marking the highest growth since the pandemic began in 2020 [1]. - Discounts of up to 2,530 yuan ($351) were offered on Apple's latest iPhone 16 models in May through Chinese e-commerce platforms [1]. Group 2 - The rebound in iPhone sales was partly driven by tariff evaders and double-digit growth in Japan, India, and the Middle Eastern markets [2]. - The U.S. and Chinese markets are crucial for the iPhone's future prospects, as highlighted by Ivan Lam of Counterpoint [2]. Group 3 - Counterpoint Research revised its growth expectations for global smartphone shipments in 2025 down to 1.9% from 4.2%, citing uncertainties related to tariffs [3]. - Shipment growth from China is expected to be nearly flat, with Apple and Samsung's shipments anticipated to slow due to increased consumer costs [3]. - IDC also lowered its 2025 global smartphone shipment growth outlook to 0.6% from 2.3% [3]. Group 4 - IDC forecasts a 3% growth in smartphone shipments in China for 2025, driven by government subsidies, while Apple is expected to decline by 1.9% due to competition from Huawei and economic slowdown [4]. - U.S. smartphone shipment growth is projected to slow to 1.9% in 2025, down from 3.3% in 2017, primarily due to tariff-related price increases [4]. - As of the last check, Apple stock was down 0.82% to $197.57 [4].

Uh, you know, I had Jensen uh Hang on the BG2 podcast uh last year. It's when people were were saying, "Oh, this training is hitting an upper bound and all this AI is overblown and remember uh Nvidia fell and all these AI stocks were falling and and Jensen Hang said on on the podcast, he said, you know, we are now moving into inference time reasoning where the machines begin to recursively think for themselves." And he said at that moment, inference isn't going to 10x. It isn't going to 100x. It isn't going ...

Nvidia's Jensen Wong issuing a warning to the US when it comes to imposing these chip restrictions on China. Our Arjent Carpal is in Paris at the Viva Technology Conference where he talked to Nvidia's CEO earlier today. Arjun, good morning. Good morning, Carl.It's been Jensen Mania here in Europe for the past few days. He was in London, now he's in Paris. Uh, and there's been a slew of deals announced around Nvidia and infrastructure deals here in Europe.But I had a chance to catch up catch up with Jensen H ...

in video uh CEO Jensen Wong making some new comments on China's progress in the AI race. CNBC uh caught up with Wong at a tech conference in Paris just a few days after Huawei's CEO was quoted by Chinese state media as brushing off the impact of US restrictions on exports uh to China's chip sector. Here's what Wong had to say.The important thing to remember is that AI tech AI is a parallel problem. If if uh each one of the computers are not as capable, just have more computers. And what he's saying is that ...

If the U.S. continues to impose AI semiconductor restrictions on China, then chipmaker Huawei will take advantage of its position in the world's second-largest economy, Nvidia CEO Jensen Huang told CNBC Thursday."Our technology is a generation ahead of theirs," Huang told CNBC at the sidelines of the Viva Technology conference in Paris.However, he warned that: "If the United States doesn't want to partake, participate in China, Huawei has got China covered, and Huawei has got everybody else covered."In the ...

Core Insights - The U.S. export restrictions on advanced semiconductors are pushing China to develop domestic alternatives, with Huawei being a key player in this effort [1][3][6] AI Chip Design - Nvidia is recognized as the leading AI chip designer, but it does not manufacture the chips itself; it relies on foundries for production [5] - Despite U.S. restrictions, demand for Nvidia chips remains high among Chinese customers, although Nvidia has faced challenges in selling its H20 processor to China [6][7] - Huawei's HiSilicon is making progress in GPU design, with its Ascend 910B and upcoming Ascend 910C chips showing significant advancements, though still behind Nvidia [9][10] AI Chip Fabrication - Nvidia's manufacturing is primarily done by TSMC, which is compliant with U.S. export controls, limiting Huawei's access to advanced chip production [11][12] - SMIC, China's largest foundry, is behind TSMC in technology, officially capable of producing 7-nanometer chips but suspected of working on a 5-nanometer chip for Huawei [13] - Huawei is reportedly working on its own fabrication capabilities, but lacks essential manufacturing equipment [14] Advanced Chip Equipment - Export controls from the Netherlands restrict SMIC's access to advanced lithography machines from ASML, which are crucial for producing advanced GPUs [15][16] - SMIC has attempted to circumvent these restrictions using less advanced lithography systems, but this approach has limitations [17] - Chinese companies like SiCarrier Technologies are exploring alternative lithography technologies, but achieving comparable capabilities may take years [18] AI Memory Components - High Bandwidth Memory (HBM) is essential for AI applications, with South Korean companies like SK Hynix leading the market [19][20] - Chinese firms such as ChangXin Memory Technologies are in the early stages of HBM production but face significant challenges, including export controls [21][22] - Huawei relies on foreign HBM supplies for its Ascend 910C processor, highlighting the ongoing dependence on international suppliers despite domestic advancements [24]

Investment Rating - Industry View: In-Line [7] Core Insights - The semiconductor industry is experiencing unprecedented demand driven by AI advancements and geopolitical tensions, particularly in the context of China's push for AI localization [4][8]. - The report highlights a decoupling between broader semiconductor cycles and AI growth, indicating that while overall semiconductor growth was slow at 10% year-over-year in 2024, AI-related demand continues to surge [10][13]. - Logic semiconductor foundry utilization is reported at 70-80% in the first half of 2025, suggesting that recovery is still ongoing [9]. Demand and Supply Dynamics - Significant demand is anticipated from AI, with NVIDIA experiencing booming demand and its Days of Inventory (DOI) reaching a historical low [15]. - The report forecasts that the top six companies' capital expenditures (capex) will grow by 62% year-over-year to RMB 373 billion [30]. - China's GPU self-sufficiency ratio was 34% in 2024, expected to rise to 82% by 2027, with local GPU revenue projected to reach RMB 287 billion by 2027 [32][35]. Market Trends and Projections - The total addressable market (TAM) for cloud AI semiconductors is projected to grow to USD 235 billion in 2025, with edge AI semiconductors expected to grow at a compound annual growth rate (CAGR) of 22% from 2023 to 2030 [49][60]. - Inference AI semiconductors are forecasted to grow at a CAGR of 55% from 2023 to 2030, outpacing training and general-purpose chips [60]. - The report anticipates robust cloud capex spending of nearly USD 789 billion across 2025-2026, driven by major cloud service providers [49]. Supply Chain and Capacity - TSMC is expected to expand its CoWoS capacity significantly, with projections of producing 5.1 million chips in 2025 [61][70]. - AI computing wafer consumption is estimated to reach up to USD 15 billion in 2025, with NVIDIA accounting for the majority of this consumption [73]. - The report indicates that the semiconductor supply chain is under pressure, with GPU supply and demand needing time to align [70].

One of the biggest perceived competitive advantages for Nvidia may backfire. Since 2022 came to a close, shares of Nvidia have advanced by more than 870%, with the company tacking on over $3 trillion in market cap and completing a historic 10-for-1 forward split. Though Nvidia's aggregate percentage return has lagged Palantir Technologies, Nvidia's valuation soared quicker than any megacap stock in history. The advent and proliferation of the internet in the mid-1990s was a can't-miss trend that captivated ...

Core Insights - The article discusses the challenges facing Nvidia, a leading player in the AI semiconductor market, despite its significant stock price increase and market cap growth [5][11]. Group 1: Nvidia's Market Position - Nvidia has become the largest publicly traded company due to its dominance in AI-GPU technology, particularly with its Hopper and Blackwell architectures, which are essential for AI data centers [6][7]. - The company has seen a dramatic increase in market cap, exceeding $3 trillion, driven by high demand for its AI-GPUs, with prices for Hopper chips reaching over $40,000, significantly higher than competitors [9][10]. Group 2: Insider Activity - There has been a notable absence of insider buying at Nvidia for over four years, with the last purchase occurring in December 2020, while insiders have sold more than $3.35 billion worth of stock during this period [12][14][16]. - The lack of insider purchases raises concerns about the future performance of Nvidia's stock, as insiders typically buy shares when they expect the stock to rise [16]. Group 3: Competitive and Regulatory Challenges - Nvidia faces increasing competition from companies like AMD and Huawei, which may impact its gross margins and future demand as customers develop their own AI-GPUs [18][20]. - Regulatory restrictions on exporting high-powered chips to China have also affected Nvidia's sales, as this market has historically generated significant revenue for the company [22]. Group 4: Market Trends and Risks - Historical trends suggest that major technological innovations often experience bubble bursts, indicating that the current AI boom may not be sustainable [23][24]. - Many businesses are still in the early stages of optimizing their AI solutions, which could lead to a decline in investment returns and signal a potential market correction for AI-related stocks [24].

Investment Rating - The semiconductor production equipment industry is rated as Attractive [5][70]. Core Insights - The imminent launch of DeepSeek R2, which features 1.2 trillion parameters and significant cost efficiencies, is expected to positively impact the Japanese semiconductor production equipment (SPE) industry [3][7][11]. - The R2 model's capabilities include enhanced multilingual support, broader reinforcement learning, multi-modal functionalities, and improved inference-time scaling, which could democratize access to high-performance AI models [7][9][11]. - The development of efficient AI models like R2 is anticipated to increase demand for AI-related SPE, benefiting companies such as DISCO and Advantest [11]. Summary by Sections DeepSeek R2 Launch - DeepSeek's R2 model is reported to have 1.2 trillion parameters, a significant increase from R1's 671 billion parameters, and utilizes a hybrid Mixture-of-Experts architecture [3][7]. - The R2 model offers cost efficiencies with input costs at $0.07 per million tokens and output costs at $0.27 per million tokens, compared to R1's $0.15-0.16 and $2.19 respectively [3][7]. Industry Implications - The launch of R2 is expected to broaden the use of generative AI, leading to increased demand for AI-related SPE across the supply chain, including devices like dicers, grinders, and testers [11]. - The report reiterates an Overweight rating on DISCO and Advantest, which are positioned to benefit from the anticipated increase in demand for AI-related devices [11]. Company Ratings - DISCO (6146.T) is rated Overweight with a target P/E of 25.1x [12]. - Advantest (6857.T) is also rated Overweight, with a target P/E of 14.0x [15].