“We’re NVDA buyers ahead of the event, and while history certainly does not repeat itself, we would highlight the historically strong performance NVDA stock has shown following GTC over the past few years (3-mo post-GTC NVDA outperformed SOX by ~30%+; range: +12%-45%),” said Wells Fargo analysts, led by Aaron Rakers, in an investor note.

Tech sector investors will certainly be focused on the event, which runs from March 16-19 in San Jose, Calif. The company’s messaging highlights OpenAI (OPENAI), Google DeepMind (GOOG)(GOOGL), Meta (META), Microsoft (MSFT), and Tesla (TSLA) as participating in main stage or marquee sessions. Nvidia CEO Jensen Huang will give a keynote address at 2 p.m. ET on Monday. Huang will also moderate an industry panel at 3:30 pm ET on Wednesday.

GF Securities believes the event might not only be a catalyst for Nvidia but for the entire semiconductor sector. Nvidia is expected to reveal its second-generation co-packaged optic switch. This will likely feature Taiwan Semiconductor’s (TSM) co-packaged optic technology, but volume is not expected to ramp up until 2027, when it hits 80,000, analysts at the firm said. Other potential announcements include updates on its Feynman line of GPUs – its Kyber NVL576 line of racks.

Bank of America is also high on Nvidia ahead of the event, reiterating its Buy rating and $300 price target.

“While we don’t expect an official 2027-28 sales outlook, any color around the Rubin ramp (CY27-28) could help the currently depressed stock (at a historical low of 17x fwd PE), following a strong Blackwell ramp with $0.5Tn in cumulative sales,” said BofA analyst Vivek Arya.

Wells Fargo anticipates Nvidia providing an update on its pipeline.

“$500B+ pipeline expansion + elongation (through CY27?) + add’l context to NVDA’s disclosure that it has cumulatively deployed 9 GWs of Blackwell (vs sub-4.5 GWs on Hopper),” Rakers said. “Since shipping Blackwell in late CY24, we estimate NVDA has recognized ~$240-$250B out of the $500B+ target (through CY26)—we think an update to $600B+ would be positive. We’re also focused on whether NVDA will provide an update on its estimate of $3-$4T/annum in AI infrastructure spending by 2030.”

Stocks that could react to GTC developments include AMD (AMD), Taiwan Semiconductor, Broadcom (AVGO), Intel (INTC), Marvell (MRVL), and various networking names.

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According to the investment firm’s February Equity Strategy data, the relative weighting for the industry continued to decline among active managers, down to 0.84x, the lowest since June 2012, and down from 0.89x in January.

Despite the declines in relative weighting, the compute area of semiconductors has seen the greatest increase in ownership, led by AMD (AMD). Fund managers increased their position in AMD by 1,001 basis points on a quarter-over-quarter basis, Bank of America said.

Conversely, analog chip makers saw an average decline of 51 basis points quarter-over-quarter and 254 basis points year-over-year, with Onsemi (ON) and Microchip (MCHP) seeing 81 basis point declines. Analog Devices (ADI) was the only analog stock to see a sequential rise, up 6 basis points.

AMD’s rise, Synopsys’ fall

Delving deeper, Bank of America said that AMD is now owned by 35% of funds and is the third-most widely owned chip stock behind Nvidia (NVDA) (at 78%) and Broadcom (AVGO) (at 74%). However, it is still underweight compared to the S&P 500, at 15th among semiconductors.

On the flip side, Synopsys (SNPS) has seen the greatest decrease in ownership, down 406 basis points quarter-over-quarter, at 26% of fund managers. However, it is still the second most overweight semiconductor stock, at 1.71x relative weight, behind KLA Corp. (KLAC) at 1.79x. Lam Research (LRCX) has seen an increase in ownership, up 670 basis points quarter-over-quarter to 33% of fund managers, now the fourth highest in the group.

Other takes

Other notable takeaways from the survey include: Teradyne (TER) seeing a 28% decrease quarter-over-quarter in its relative weight, to 0.30x from 0.47x in January 2026; ownership in Micron (MU) increasing to 25% from 18%, amid the continued rise in memory prices. However, Micron’s relative weight was down 5% quarter-over-quarter to 1.24x, the lowest in over a year but still the fifth highest in semiconductors.

Other findings include Lumentum (LITE) and Skyworks Solutions (SWKS) having the most short interest (16% and 14% of the float), while Nvidia and Broadcom have the least, at roughly 1% apiece.

Long-only investors had higher net weighting in Skyworks, Qualcomm (QCOM), NXP Semiconductors (NXPI), Broadcom, and Texas Instruments (TXN), compared to hedge funds, which were more overweight in Teradyne, Lam Research, and Onsemi. Both long-only investors and hedge funds were overweight Applied Materials, Cadence Design Systems (CDNS), and Synopsys, the survey showed.

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The company said the model combines advanced reasoning capabilities to efficiently complete tasks with high accuracy for autonomous agents.

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Here are some of Wednesday’s biggest stock movers:

Biggest stock gainers

• Oracle (ORCL) +11% – Shares jumped after the company reported FQ3 results and guidance that topped Wall Street expectations. Revenue rose 22% Y/Y, driven by strong cloud demand, with cloud revenue up 44%, infrastructure revenue surging 84%, and Fusion Cloud ERP revenue rising 17%. For Q4 FY2026, Oracle expects revenue growth of 18%–20% in constant currency (19%–21% in U.S. dollars), implying $18.93B–$19.24B, around the $19.11B consensus, while adjusted EPS is projected at $1.92–$1.96, slightly above the $1.93 estimate. The company also raised its long-term outlook, saying it now expects FY2027 revenue to reach about $90B, reflecting continued momentum in its cloud business.
• Ballard Power Systems (BLDP) +7% – Shares rose after the company announced a commercial agreement with New Flyer, part of NFI Group, to supply 500 FCmove-HD+ fuel cell engines totaling 50 MW. The order marks the largest commitment from New Flyer since the partnership began, with deliveries starting in 2026 to power Xcelsior CHARGE FC hydrogen fuel cell buses across North America. Ballard said the deal strengthens its long-standing partnership with New Flyer and supports the expansion of zero-emission public transit fleets in the region.

Biggest stock losers

• Kosmos Energy (KOS) -16% – Shares plunged after the company announced a public offering of 97.5M common shares priced at $1.90 each, expected to generate gross proceeds of about $185.25M. The offering, set to close on March 12, 2026, also grants underwriters a 30-day option to purchase an additional 14.63M shares at the same price. Kosmos said it plans to use the net proceeds primarily to repay borrowings under its commercial debt facility and reduce other outstanding debt, a move aimed at strengthening its balance sheet.
• AeroVironment (AVAV) -10% – Shares declined after the company reported quarterly results that missed Wall Street expectations and lowered its full-year outlook. The company posted a Q3 operating loss of $179M, compared with a $3.1M loss a year earlier, largely due to a $151.3M goodwill impairment in its space division tied to a stop-work order on the U.S. Space Force’s SCAR program. Gross margin for the quarter declined to 24% from 38%, reflecting a higher mix of service revenue following the BlueHalo deal, along with higher amortization and purchase-accounting charges. CEO Wahid Nawabi said demand remains strong despite revenue timing issues. For FY2026, AeroVironment now expects revenue of $1.85B–$1.95B, down from $1.95B–$2.0B previously and the consensus of $1.95B, and projects a net loss of $218M–$201M, adjusted EBITDA of $265M–$285M, and adjusted EPS of $2.75–$3.10, much below the consensus of $3.24.

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The size of Nvidia’s investment into Thinking Machines was not disclosed.

Thinking Machines Lab, run by former OpenAI (OPENAI) CTO Mira Murati, said it will deploy at least one gigawatt of Nvidia’s Vera Rubin systems to support Thinking Machines’ frontier model training and platforms. Deployment is set for early next year, Thinking Machines added.

“AI is the most powerful knowledge discovery instrument in human history,” said Nvidia CEO and founder Jensen Huang in a statement. “Thinking Machines has brought together a world-class team to advance the frontier of AI. We are thrilled to partner with Thinking Machines to realize their exciting vision for the future of AI.”

“NVIDIA’s technology is the foundation on which the entire field is built,” said Mira Murati, cofounder and CEO of Thinking Machines. “This partnership accelerates our capacity to build AI that people can shape and make their own, as it shapes human potential in turn.”

In July, Thinking Machines raised $2B in a funding round that valued it at $10B. Andreessen Horowitz, also known as a16z, led the funding round, which included participation by Nvidia (NVDA), AMD (AMD), ServiceNow (NOW), Cisco Systems (CSCO), and others.

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“As promised, I bought additional 1 million shares of NVDA today,” KoGuan wrote early Saturday on X, days after disclosing his initial purchase.

The investment marks a notable shift for KoGuan, whose wealth has long been heavily tied to shares of Tesla (TSLA). It comes as global markets have weakened since the U.S. and Israel launched military operations against Iran last month, sparking a broad selloff across assets from bonds to equities and raising concerns that markets could fall further if the conflict drags on.

Shares of Nvidia (NVDA) are down about 5% this year through Friday’s close, while Tesla (TSLA) has fallen nearly 12%, compared with a decline of less than 2% for the S&P 500.

KoGuan is estimated to have spent roughly $350M on his Nvidia (NVDA) holdings based on recent closing prices. Aside from announcing the purchase, he said only that he hoped the move could “contribute a little to calm the nervous market.”

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The San Francisco-based company is currently valued at $7.5B, the report said. Together AI, founded in 2022, is already generating about $1B in annualized revenue, a figure that has nearly tripled in less than one year. The company leases Nvidia chip servers and then rents them out to AI developers. It also buys some servers for its data centers. This new round of funding is mostly for that purpose, according to people familiar with the issue.

The company has raised a total of $554M across five funding rounds, which included investments from notable tech companies such as Nvidia and Salesforce Ventures (CRM).

“To support our rapidly growing ecosystem, we’re dramatically expanding our infrastructure,” Together AI said. “We’ve secured 200 MW of power capacity and are deploying optimized clusters of NVIDIA Blackwell GPUs across multiple North American data centers. Our recent partnership with Hypertec to co-build a cluster of 36,000 NVIDIA GB200 NVL72 GPUs further strengthens our position as the leading AI Cloud provider.”

It is similar to other so-called neoclouds such as Lambda, CoreWeave (CRWV), and Nebius (NBIS).

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The proposed rules would require companies to get U.S. permission for virtually all exports of AI accelerators developed by the likes of Nvidia (NVDA) and Advanced Micro Devices (AMD), a global expansion of restrictions that currently cover about 40 countries, the report added, citing people with knowledge of the matter.

The Commerce Department, the Bureau of Industry and Security, Nvidia, and AMD did not immediately respond to a request for comment from Seeking Alpha.

These chips are desired by companies globally for use in data centers that power AI services like OpenAI’s (OPENAI) ChatGPT and Google’s (GOOG) (GOOGL) Gemini.

U.S. President Donald Trump’s team has said repeatedly that they want the world to use U.S. AI, and the draft rules are not meant to function as an Nvidia export ban. Rather, the rules would set up the U.S. government as gatekeeper for the AI industry. Companies and, in some cases, their governments would have to get the U.S. Commerce Department’s approval to buy the chips, the report noted.

How Trump’s team determines to give these licenses would then decide if countries will be able to establish critical digital infrastructure, technology that many see as key to economic growth, corporate competitiveness, and military sovereignty, according to the report.

The specific approval process would depend on how much computing power a company requires. Shipments of up to 1,000 of Nvidia’s latest GB300 graphics processing units, or GPUs, would see a largely simple review with certain exemption opportunities, the report noted.

Companies setting up larger clusters would require preclearance before seeking export licenses. These companies could face conditions like disclosing their business models or allowing the U.S. government to visit sites, depending on the specifics of the data centers in question, the report added.

For large deployments — over 200,000 of Nvidia’s GB300 chips owned by one company in one country — the host government would have to get involved. The U.S. would only approve such exports to allies that make strict security pledges and “matching” investments in U.S. AI. However, the draft rule does not specify an investment ratio.

The Trump team’s framework is not finalized, and officials across federal agencies are currently providing their input. The draft could change, or it could be shelved for other priorities, the report noted.

The Trump administration had previously criticized the Biden administration’s AI diffusion rule, which curbed AI chip sales to many countries and set caps on how much could be exported, as burdensome.

China’s AI ambitions are a big reason behind the U.S.’s AI policymaking. One focus is limiting China’s manufacturing of AI chips, which the U.S. has done by curbing exports of chipmaking equipment. In addition, under Trump, Nvidia was allowed back into China to compete against local tech giant Huawei Technologies. The new global rules would not change the White House’s approach to chip exports to China, as Trump’s team weighs how many Nvidia chips would be enough to dampen Huawei’s rise without giving China too much computing capacity, the report noted.

The U.S. could also use export licenses to curb Chinese companies’ access to AI chips overseas, as some national security experts have advocated. In some instances, they already have: ​​Trump’s team conditioned some Nvidia shipments to the UAE on companies not providing computing services to any Chinese AI firms, the report added.

Earlier this week, it was reported that U.S. officials are considering caps on the number of AI accelerators Nvidia can export to any one Chinese company to about 75,000 H200 chips.

In December 2025, Trump approved the sale of some advanced AI chips, including the H200 GPUs, to China in exchange for a 25% fee. Trump issued a proclamation in January imposing the 25% tariff on certain high-end chips, including Nvidia’s H200 and AMD’s MI325X.

The H200 is the predecessor to Nvidia’s current flagship Blackwell chips and the upcoming Vera Rubin. The Trump Administration had previously allowed Nvidia to sell a less powerful GPU, the H20, to China.

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