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Tom Jones10/7/25

Trilogy Metals soars on US government’s 10% stake announcement

Shares in Trilogy Metals, a Canadian minerals exploration company, have soared as much as 200% in early trading today after the US government announced it has taken a 10% stake in the company worth $35.6 million, along with warrants to build that investment by another 7.5% down the line.

The Trump administration’s position in the company, which had five full-time employees as of November last year, reflects growing government interest in reducing America’s dependence on China for critical mineral supplies, given Trilogy Metals’ mining claims in Alaska.

In a section of the announcement subtitled “UNLOCKING ACCESS TO AMERICA’S CRITICAL MINERALS,” the White House detailed how the investment and decision to green-light the Ambler Road Project, which will open up road access to the Ambler Mining District, overturns the Biden government’s move to block the same project last year. The area reportedly has “one of the largest undeveloped copper-zinc mineral belts in the world and contains extensive deposits of copper, silver, gold, lead, cobalt, and other strategic metals.”

Similar Washington deals with mining companies like MP Materials and Lithium Americas sent those companies’ shares soaring, too. Critical Metals, meanwhile, which jumped yesterday on reports around talks of a government stake in the business, has slumped 5% in premarket trading today.

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The threat of AI disruption has dawned on the bond market

22V Research economist Peter Williams noted that medium-term rate expectations have disconnected from recent encouraging labor market data.

Apollo robot

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Michael Burry flags “troubling” jump in Nvidia’s supply commitments

“The Big Short” investor Michael Burry — famous for betting against the 2008 housing bubble — just warned of a major risk in Nvidia’s latest annual report, pointing to a sixfold surge in purchase obligations over the past year.

In a Substack post Thursday, Burry called the increase from $16.1 billion to $95.2 billion in just 12 months “troubling,” noting that Nvidia has been forced to place noncancelable purchase orders well before knowing the final demand for its AI chips. The surge is partly tied to supplier TSMC requiring longer-term contracts, he added.

'Big Short' Michael Burry warns Nvidia is taking on risk that could be 'catastrophic'

'Big Short' Michael Burry warns Nvidia is taking on risk that could be 'catastrophic'

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Matt Phillips5h

Vistra beats Q4 earnings expectations for adjusted EBITDA, but dips on income decline

Power provider Vistra, a key player in the AI energy trade, reported better-than-expected adjusted earnings results early Thursday, but shares dipped in early trading as Q4 net income dropped.

The Texas-based company, which supplies nuclear- and natural gas-fueled power to wholesale and retail markets, reported:

Net income of $233 million, a decline of 52% from Q4 2024.
Adjusted EBITDA from ongoing operations of $1.74 billion vs. the $1.71 billion expected by Wall Street analysts.
Vistra maintained previously issued guidance for full-year EBITDA from ongoing operations and adjusted free cash flow from ongoing operations.

Vistra shares soared 258% in 2024 amid a flurry of excitement over the AI energy boom. Last year was more muted, with the stock rising 17%. So far in 2026, shares were up roughly 9% before the report.

Vistra beats fourth-quarter core profit estimates on AI-driven power demand

Vistra beats fourth-quarter core profit estimates on AI-driven power demand

Net income of $233 million, a decline of 52% from Q4 2024.
Adjusted EBITDA from ongoing operations of $1.74 billion vs. the $1.71 billion expected by Wall Street analysts.
Vistra maintained previously issued guidance for full-year EBITDA from ongoing operations and adjusted free cash flow from ongoing operations.

Vistra shares soared 258% in 2024 amid a flurry of excitement over the AI energy boom. Last year was more muted, with the stock rising 17%. So far in 2026, shares were up roughly 9% before the report.

Why Nvidia’s terrific quarter is getting a terrible reaction

Nvidia’s CEO gave a deeply unsatisfying answer about his biggest customers’ ability to generate cash. But they might be investing more in AI GPUs in 2027 anyway.

Jensen Huang in front of Vera Rubin at CES 2026

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Claire Yubin Oh7h

Sandisk rises on partnership with SK Hynix to standardize memory chip architecture tailored for AI data centers

Sandisk is up 3% in premarket trading on Thursday after it began its global standardization strategy of high-bandwidth flash (HBF) memory solutions with SK Hynix.

SK Hynix commented in a press release on Thursday that “by making HBF an industry standard, together with Sandisk, we will lay the foundation for the entire AI ecosystem to grow together,” adding that the companies will set up a dedicated workstream to work on the standardization under the Open Compute Project, the world’s largest organization dealing with data center technologies.

First debuted last February, Sandisk’s HBF technology lies in between ultrafast high-bandwidth memory (HBM) and high-capacity SSDs. That is, these have more storage capacity than HBMs, but are still fast enough to be utilized in AI inferencing (albeit not as quick as HBM).

Sandisk has previously argued that this hybrid architecture is central to AI services that need user applications but require a significant amount of fast interconnect between GPUs. The latest announcement also notes that HBF technology is expected to be more cost-efficient compared to alternatives of similar scale.

The launch, which was shared in an kickoff event on Thursday evening, starts SK Hynix and Sandisk’s workflow, which was announced when the two companies signed a memorandum of understanding “to standardize the specification, define technology requirements and explore the creation of a technology ecosystem” last August, per Sandisk’s press release at the time. Ultimately, by collaborating with SK Hynix, one of the three key HBM suppliers, to standardize and commercialize the technology, Sandisk is manufacturing somewhat of a first-mover advantage to offer the system-level “AI-optimized memory architecture” required for AI inference markets, rather than focusing on the performance of a single chip element.

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