Tag Archives: NVDA

Best Stocks To Buy Today: ASTS, MU,ASML

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As a new week begins, we are closely tracking market trends to provide multi-dimensional investment opportunities by identifying hot stock movements and top performers. Below is our selection for the Best Stocks To Buy Today.

Space Investment Fever Continues: AST SpaceMobile (ASTS) Surges Over 14% After Securing Prime Contractor Status for MDA’s “SHIELD” Project.

On the news front, U.S. satellite communications company AST SpaceMobile (ASTS) jumped over 14% last Friday. This followed confirmation that the company has been awarded prime contractor status for the U.S. Missile Defense Agency’s (MDA) “SHIELD” project. Formally known as the “Scalable Homeland Innovative Enterprise Layered Defense,” this project is part of the broader “Golden Dome” strategy, designed to build a resilient, layered defense system across air, missile, space, cyber, and hybrid warfare domains.

The award stems from the U.S. government’s public release of qualified bidders for the project on January 15, 2026. Chris Ivory, Chief Commercial Officer and Head of Government Business at AST SpaceMobile, stated: “Being selected as a prime contractor for the MDA SHIELD project is a significant validation of our unique, on-orbit dual-use technology and our growing capabilities in the defense sector.”

Micron Technology (MU) Gains 7.76% as It Warns Chip Shortage Will Extend into 2027.

Micron Technology (MU), a key supplier to Nvidia (NVDA), stated that the ongoing memory chip shortage has intensified over the past quarter. The company reiterated that due to the surge in demand for high-end semiconductors required for AI infrastructure, supply constraints will persist well beyond this year.

“The shortage we are currently seeing is truly unprecedented,” said Manish Bhatia, Executive Vice President of Global Operations at Micron, during an interview. This statement followed the groundbreaking ceremony for the company’s $100 billion manufacturing site on the outskirts of Syracuse, New York. This outlook reinforces similar forecasts provided by the company in December.

Bhatia pointed out that High Bandwidth Memory (HBM), essential for manufacturing AI accelerators, is “consuming a massive amount of available industry capacity, leading to significant supply shortages for traditional sectors like mobile phones and PCs.” He added that PC and smartphone manufacturers have already begun queuing up to lock in memory chip supplies for 2026 and beyond, while autonomous vehicles and humanoid robots are expected to drive demand for these components even higher.

ASML Holding (ASML) Rises Over 2% as Semiconductor Capital Cycle Re-accelerates

On Thursday, TSMC (TSM) released financial results showing a 35% year-on-year increase in net profit for the fourth quarter of 2025, beating expectations. The company also forecasted a Q1 operating margin of 54% to 56% (market estimate: 49.7%) and a gross margin of 63% to 65% (market estimate: 59.6%). These figures demonstrate that the chipmaker is benefiting significantly from the AI boom.

This signal was interpreted by the market as a vote of confidence in the sustained expansion of the AI industry. This directly ignited the stock prices of equipment giants like ASML and Applied Materials. Dutch photolithography leader ASML (ASML) hit a historic high, with its market capitalization surpassing the $500 billion milestone—becoming only the third European company to reach this valuation.

TSMC is one of ASML’s largest individual customers, and ASML’s lithography equipment is an “absolute necessity” for TSMC’s expansion and mass production of advanced process chips. Currently the highest-valued company in Europe, ASML’s core competitiveness lies in being the world’s only manufacturer capable of producing cutting-edge EUV lithography machines. TSMC requires this equipment to manufacture chips for everything from Apple (AAPL) smartphones to Nvidia (NVDA) AI accelerators.

AI5 Chip Breakthrough: Tesla Announces Reboot of Dojo 3 Supercomputer Project to Secure Autonomous Driving Compute Independence

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Tesla CEO Elon Musk recently announced that with the design of the AI5 chip now complete, Tesla (TSLA) will reboot the development of its Dojo 3 supercomputer project. The Dojo project aims to provide massive computing power for autonomous driving systems and AI models through self-developed chips and systems, reducing reliance on external suppliers.

Analysts believe the AI5 chip will support more complex Full Self-Driving (FSD) algorithms. The progress of the chip’s mass production will directly influence the rollout speed of Tesla’s FSD features and could become a critical pillar for its robotics business.

Musk’s Announcement

On January 19, Musk posted on the social media platform X that Tesla will restart the development of the Dojo 3 supercomputer project following the completion of the AI5 chip design.

Simultaneously, he posted recruitment information seeking talent interested in “developing the world’s highest-volume chip,” requiring applicants to summarize key technical challenges they have solved in three bullet points.

In subsequent posts, Musk emphasized: “Solving the AI5 chip issue is critical for Tesla. Therefore, I had to have both teams focus on this chip’s development, and I have personally spent every Saturday on it for several months.”

Musk noted that AI5 will be an exceptionally powerful chip: a single SoC’s performance is roughly equivalent to Nvidia’s Hopper(NVDA) class, while a dual-chip configuration approaches Blackwell levels—but at a significantly lower cost and power consumption. “With AI5 progressing smoothly, we finally have some bandwidth to restart the R&D for Dojo 3,” he stated.

This marks a strategic reversal. In August 2025, reports suggested that Tesla had fully suspended the Dojo project, leading to the departure of project lead Peter Bannon. At the time, the move was interpreted as Tesla abandoning its self-developed autonomous driving chip plan.

Musk previously explained that it made little sense for Tesla to divide resources between two vastly different AI chip designs. He noted that Tesla’s AI5, AI6, and subsequent chips would excel in inference and perform well in training, and that all efforts would be concentrated there. He added that integrating multiple AI5/AI6 chips onto a single circuit board for supercomputer clusters could reduce networking complexity and costs by several orders of magnitude.

First mentioned in 2019, the Dojo project carries Tesla’s grand vision for AI. It is designed to optimize neural network models and process autonomous driving video data. Morgan Stanley previously estimated that a fully operational Dojo could potentially add billions of dollars to Tesla’s valuation.

A Decisive Battle for Autonomous Driving

Musk recently revealed that the AI5 chip for FSD is nearing design completion, while AI6 is in its early stages. Tesla aims to complete design cycles for AI7, AI8, and AI9 within a nine-month cadence.

According to previously disclosed data, the AI5 chip will deliver 2,000–2,500 TOPS of computing performance—roughly five times that of the current HW4 chip—enabling more sophisticated FSD algorithms.

Sampling and small-scale deployment of the AI5 chip are scheduled for 2026, with full mass production expected in 2027. As AI5 nears the finish line, Tesla has initiated early work on AI6, which is expected to launch in 2028. AI6 will likely continue Tesla’s foundry partnership with Samsung Electronics, utilizing a modular architecture deeply integrated with the Dojo supercomputer ecosystem to create synergy across vehicles, robots, and supercomputing.

Recent reports indicate that Samsung Electronics is accelerating preparations for AI5 production at its U.S. facilities, recruiting experienced engineers to stabilize yields and ensure a smooth manufacturing process for Tesla.

Shift to FSD Subscription Era

Alongside hardware updates, Tesla’s FSD strategy is undergoing a major shift. Musk recently announced that starting February 14, Tesla will discontinue the one-time purchase option for FSD in favor of a monthly subscription model.

This marks the end of a decade-long era of one-time buyouts (previously $8,000 in the U.S. and 64,000 RMB in China). Analysts point out that this “SaaS” (Software as a Service) approach aims to lower the barrier to entry, increase penetration, and generate recurring revenue.

Musk has hinted that the next version of FSD will achieve full autonomy, even admitting that Robotaxi driverless testing has already begun. Morgan Stanley views FSD 14.3 as a potential “Steam Engine Moment” for autonomous driving, which is shaping up to be a primary investment theme for Wall Street in 2026.

U.S. Modifies Chip Ban, Paving the Way for H200 Sales to China

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The United States has once again legally eased export controls on the sale of Nvidia’s H200 chips to China.

On January 14, the Bureau of Industry and Security (BIS), under the U.S. Department of Commerce, amended its export control regulations to relax restrictions on high-performance chips. The new thresholds allow for the export of chips with a Total Processing Performance (TPP) of less than 21,000 and a total DRAM bandwidth of less than 6,500 GB/s. This adjustment effectively creates a legal pathway for products such as Nvidia (NVDA) H200 and AMD MI325X to be exported.

A veteran researcher of technology policy noted that this adjustment constitutes a formal rule change, providing a clear legal basis for future transactions.

The revision of these regulatory details is tied to the U.S. government’s official announcement regarding the issuance of export licenses for the H200 and MI325X to mainland China. Because previous regulations—specifically the “October 7 Rule” of 2022 and the “October 17 Rule” of 2023—imposed strict limits on TPP and memory bandwidth, the act of granting new licenses would have conflicted with existing standards without these formal amendments.

“It isn’t as simple as saying ‘you can sell now’ and sales begin immediately; following formal legal procedures takes time,” explained another tech policy researcher. “Simply approving licenses without updating the export control regulations would have been inconsistent with the regulatory framework.”

New Standards and Restrictive Conditions

Records show that the “October 17 Rule” of 2023 required licenses for any chip export to mainland China or Macau that met specific criteria ($TPP \ge 4,800$, or $TPP \ge 1,600$ with a performance density $\ge 5.92$), with a policy of “presumption of denial.” That rule also introduced the concept of “Total DRAM Bandwidth,” placing any chip with a bandwidth $\ge 4,100 \text{ GB/s}$ under control.

It is important to note that the latest adjustment includes several new restrictive conditions:

  • Supply Certification: Applicants (such as Nvidia and AMD) must prove there is sufficient supply for the U.S. market and that exports to China will not delay orders for U.S. customers or impact global foundry capacity.
  • Volume Cap: Exporters must commit that the volume of products exported does not exceed 50% of their total sales within the United States.
  • Non-Military Use: The products must not be used for military purposes.
  • Third-Party Testing: Every shipment must undergo independent testing at a third-party laboratory located within the United States.

Financial Projections and Strategic Motivation

Market data indicates that Nvidia (NVDA) has reserved 660,000 CoWoS capacity units from TSMC for 2026. If 10% (66,000 wafers) is allocated to the H200—assuming 29 chips per wafer—the total output for the H200 in 2026 is expected to reach 1.9 million units. Under the BIS volume cap, the U.S. and China markets would be allocated approximately 1.266 million and 633,000 units, respectively.

Based on an estimated price of 1.4 million RMB for an 8-GPU module, the H200 could contribute over $47.6 billion in revenue to Nvidia in 2026. Of this, the China market could account for nearly $16 billion—a figure expected to exceed the combined 2025 revenue of all currently listed domestic Chinese AI chip companies.

A key factor in the decision to allow these exports is that the U.S. government will take a 25% revenue share. Based on the projected $16 billion in H200 revenue from China, the U.S. government stands to gain roughly $4 billion from export licenses for this single product alone.

“Inventory Clearing” and Ongoing Restrictions

However, many industry insiders view the BIS move to grant export licenses for the H200 as a way to help Nvidia (NVDA) clear existing inventory. Crucially, the U.S. has not lifted restrictions on the contract manufacturing (foundry) of Chinese AI chips with similar performance and specifications. In other words, the policy allows the sale of products at a certain performance level while continuing to prevent China from manufacturing its own equivalent hardware.

Simultaneously, while the executive branch adjusts regulations to facilitate H200 licenses, the U.S. legislative branch is pushing through another law.

On January 12 local time, the U.S. House of Representatives passed the Remote Access Security Act with a vote of 369 to 22 (39 abstentions). This bill aims to restrict the use of cloud platforms like Google and Amazon to remotely access advanced computing power for training AI models. This move could potentially disrupt the collaborative construction of data centers overseas.

The aforementioned researcher emphasized that if the bill is passed by the Senate and signed into law, such international projects may have to be withdrawn.