TechCapsules

Trump confirms that Apple will buy chips made by Intel

Trump announced that Apple will work with Intel to design and build chips in America, prompting an 8.8% rise in Intel's stock and a 0.6% increase in Apple's. The deal, a substantial multi-year agreement, is believed to concern production of older or lower-end processors, such as M-series chips for iPad Pro and MacBook Air. The partnership follows initial rumors and test production in May 2026. Details on delivery, shipment, and deal worth remain unclear. Intel's entry into limited scale testing of the 18A-P process means full production for Apple won't start until mid-2027. Apple's deal with Intel reduces dependence on Taiwan chip production.

💡 Apple's shift to Intel for older processors frees up TSMC's capacity for newer, high-end chips, ensuring a steady supply for flagship devices. This strategic move helps Apple mitigate the global chip shortage's impact on its product lineup.

The 2nm Race Begins: Foundries Battle for AI and HPC Leadership

The three major foundries, Intel, Samsung, and TSMC, are introducing 2nm-class processes in 2026, featuring gate-all-around field-effect transistors. Intel's Panther Lake is the first shipping product with this technology, using Intel 18A and backside power delivery. Samsung's SF2 is used in the Exynos 2600 smartphone SoC, while TSMC's N2 is expected in Apple iPhones by year-end. A fourth entrant, Rapidus, is targeting 2027 entry with 2HP process technology. The first 2nm chips are PC and mobile SoCs, with AMD's Venice EPYC to be the first HPC chip transitioning to TSMC N2 in 2026, marking a significant milestone in the industry.

💡 Yield stability and manufacturing scale will determine the winner in the 2nm race, as the ability to produce reliably at volume will be crucial. Ecosystem compatibility and power delivery architecture choices will also play a key role in the foundries' success.

Chipmakers Lead a Global Tech Rally as the Iran War Premium Drains…

Confirmation of a US-Iran deal sparked a global tech rally led by chipmakers, despite the signing awaiting until Friday. The deal's announcement removed the war premium from markets, causing a risk-on rally. Stocks such as SoftBank Group, Taiwan Semiconductor Manufacturing Co., and Tokyo Electron saw significant gains, with Japan's Nikkei 225 climbing 5.5 percent. The rally was driven by the removal of the war threat, which had hung over the chip and AI trade for weeks. The deal's impact was felt across Asia, with major indexes seeing notable increases. The rally was broad, with many tech stocks seeing gains.

💡 Oil shock fears dissipate with the war's end, removing a key threat to the rally. The deal's impact on inflation concerns also boosts investor confidence.

AI Watch: Why India is caught in the middle of the US-China…

A US-led coalition pushed for AI rules at a G7 lunch, aiming to cut China out of chip and model access. Macron and Modi warned of dependence risks, with India being hit hardest due to its lack of frontier chips and models. India leads the world in daily AI use, but funds are flowing into data centers from companies like CPP, AirTrunk, and Meta-Reliance. The country's limited access to chips and models is fueling calls for state investment. India's position in the US-China battle for chips and models is precarious, with significant implications for its AI development.

💡 India's limited access to frontier chips and models hinders its ability to develop AI capabilities. State investment is crucial to mitigate dependence risks and support India's AI growth.

SEMI Smart MedTech Initiative Identifies Obstacles and Opportunities to Scale Wearable Biosensors…

The SEMI Smart MedTech Initiative has identified key obstacles hindering the widespread adoption of wearable biosensors in clinical settings. Despite rapid advancements in semiconductor technologies and edge AI, wearables struggle to scale beyond everyday wellness into clinically accepted healthcare solutions. The initiative's strategic outlook paper, Medicalizing Consumer Silicon, highlights systemic barriers such as poor integration, validation requirements, and regulatory context as primary challenges. The paper recommends collaboration across industry sectors, academia, and government to address these challenges and enable reliable and scalable adoption.

SK hynix Ships Samples of 12-Layer Next-Gen ‘HBM4E’

SK hynix has shipped samples of its 12-layer next-generation HBM4E to major customers, achieving a maximum speed of 16Gbps per pin with improved performance and efficiency. The HBM4E utilizes Advanced MR-MUF, reducing heat resistance by 17% and improving stability. This development strengthens SK hynix's AI leadership, delivering value to the market with its technological capabilities and manufacturing expertise. The company will work closely with partners for mass production, improving data processing capabilities for AI training and inference. The HBM4E reduces data transfer latency, enabling efficient processing in AI data centers and large-scale computing systems, with power efficiency up over 20 percent from previous models.

💡 By enhancing AI system performance, SK hynix's HBM4E addresses a critical bottleneck in high-bandwidth computing environments. Advanced memory solutions like HBM4E are crucial for supporting next-generation infrastructure development.