USD.AI (CHIP) Surge

Anthropic, the AI company behind Claude, is exploring the development of its own custom AI chip, according to a report from The Information. The company is in early discussions with Samsung Electronics to manufacture the chip using Samsung's most advanced 2-nanometer process and packaging technology. While the project is still in preliminary stages, including defining chip specifications, and could be abandoned, it marks a strategic step for Anthropic. The move comes as the company seeks greater control over its computing costs and hardware optimization, particularly for inference tasks to run its models more efficiently and cheaply. Samsung's potential involvement follows its participation as a strategic investor in Anthropic's recent $65 billion funding round. For Samsung, partnering with a major AI lab represents a significant opportunity for its foundry business to compete with market leader TSMC in advanced semiconductor manufacturing. Anthropic's CEO, Dario Amodei, has previously highlighted the immense financial challenge of securing enough computing power for anticipated growth, making cost-effective inference a critical focus. The company would join other tech giants like Google, Amazon, Microsoft, Meta, and OpenAI in pursuing custom AI silicon. However, analysts note this trend creates deeper interdependencies rather than independence, as US AI labs become more tightly woven into Asian semiconductor supply chains. Despite this move, Anthropic remains heavily reliant on a multi-cloud, multi-vendor strategy for its immediate computing needs. It has secured massive, long-term commitments for capacity from Amazon Web Services (Trainium chips), Google (TPUs), and even leased a large GPU cluster from xAI. For now, Nvidia continues to dominate the AI chip market, with its share reportedly growing to 74%.

Kunlunxin, Baidu's AI chip unit, is nearing a Hong Kong IPO with a reported target valuation of approximately $50 billion (about 340 billion RMB). This would make it Baidu founder Robin Li's largest IPO and potentially value the chipmaker higher than its parent company. Investor demand for cornerstone shares is intense, with access reportedly tied to commitments to purchase Kunlunxin's chips. Originally Baidu's in-house chip division, Kunlunxin was spun off in 2021 and has since attracted a prestigious investor roster including CPE, IDG Capital, and China Mobile. Its products, like the P800 accelerator card, compete in the booming AI data center market. While a key supplier to Baidu, the company now generates over half its revenue from external clients like China Mobile, which placed a major order last year. For Baidu, an early proponent of "All in AI," Kunlunxin's successful listing is crucial. It represents the most valuable underlying asset in Baidu's AI narrative at a time when the company's core large language model faces stiff competition. The IPO is seen as a pivotal move for Baidu to capitalize on the AI compute boom and secure its position in the rapidly evolving landscape.

Chip stock momentum is fading, with funds rotating from previously high-flying semiconductors toward AI hyperscale cloud giants like Microsoft, Amazon, and Meta, according to Morgan Stanley's chief equity strategist Michael Wilson. He notes this rotation is occurring against a backdrop of overall market weakness, with major indices facing continued pressure. The Philadelphia Semiconductor Index has retreated nearly 14% from its recent peak, raising valuation concerns despite its massive gains since last September. Wilson now favors hyperscalers, seeing them as more attractive within the AI ecosystem due to their strong core businesses providing a solid foundation. This group has significantly underperformed semiconductors, suggesting potential catch-up opportunity. However, he cautions these companies might soon lower capital expenditure forecasts in response to market concerns over excessive AI spending. The strategist also expects the rotation to broaden beyond tech, benefiting sectors like consumer discretionary, transportation, and biotech. This view aligns with JPMorgan's Mislav Matejka, who anticipates market leadership widening in the second half of the year. Wilson maintains a year-end S&P 500 target of 8000, implying roughly 7% upside from current levels, though near-term volatility is expected.

Market strategist Michael Wilson of Morgan Stanley notes a shift in investment flows from high-flying semiconductor stocks toward AI hyperscale cloud computing giants like Microsoft, Amazon, and Meta. He observes waning momentum in the chip sector, with the Philadelphia Semiconductor Index down nearly 14% from its recent peak amid valuation concerns, despite a 123% rally since last September. Wilson argues this rotation is occurring against a backdrop of overall market weakness, keeping pressure on major indices, though he maintains a year-end S&P 500 target of 8000, implying roughly 7% upside. The report highlights AI hyperscalers as relatively undervalued within the AI ecosystem, with a basket of such stocks compiled by UBS having fallen 2% since last September. Wilson believes their strong core businesses provide solid footing, though he cautions they may soon temper capital expenditure forecasts in response to market worries over excessive AI spending. The rotation is also expected to benefit sectors beyond tech, such as consumer discretionary, transportation, and biotech. This view aligns with JPMorgan's Mislav Matejka, who anticipates a broadening of market gains beyond the technology sector in the second half of the year.

DeepSeek, the Chinese AI company known for its algorithmic models, is secretly developing its own AI chip to reduce dependence on Nvidia, according to a Reuters report. The chip is designed specifically for AI inference, not training, and the project began approximately a year ago. Currently in early stages, DeepSeek is reportedly in discussions with chip design firms, foundries, and memory suppliers. The company, historically focused on algorithmic efficiency, has been discreetly hiring chip design engineers without public job postings. This move aligns with a global trend where major AI model companies like OpenAI and Anthropic are also pursuing custom chip development. DeepSeek founder Liang Wenfeng previously highlighted chip shortages as a challenge. While the company initially trained models on Nvidia H800s and later adapted to Huawei's Ascend chips, it now seeks greater control over its hardware foundation. Designing a competitive AI chip is a significant challenge, requiring years and substantial investment with no guarantee of success. However, DeepSeek's efforts are backed by a recent major funding round of approximately 51 billion RMB (about $7.4 billion) raised in June 2026. The funds are designated for expanding data centers based on domestic chips, developing proprietary AI chips, and recruiting top global talent. Infrastructure plans are also advancing, with job postings for data center design engineers, including projects in locations like Ulanqab, Inner Mongolia. The company remains characteristically low-key, with sources speaking anonymously and no official comment from DeepSeek itself. Nevertheless, this initiative marks a strategic expansion from software algorithms into the hardware layer that powers its AI systems.